text
stringlengths
20
57.3k
labels
class label
4 classes
Title: Parameters to provide a `validate` method Body: Hi there! I'm thinking of adding a 'validate' method to the Parameter class in the OpenAPI module. This would check the given value (e.g. in a query) actually matched the type (and format, if set) of the parameter. A further possibility would be to provide a `from_request` method which searched for the value in the request structure according to where it would be found (header, query, path, etc), and returned the value - or the parameter's default if the parameter was not found in the request. What do you think? Do you want me to write that? Have fun, Paul
1medium
Title: Cannot add VRT raster layer Body: I am trying to add a layer using a RasterData object initialized with a VRT image. ``` vrt = RasterData("test.vrt") M.add_layer(vrt) ``` The layer does not appear on the map and the Jupyter server throws this error: ``` RuntimeError: `/test.vrt' does not exist in the file system, and is not recognised as a supported dataset name. ``` Am I correct in assuming that GeoNotebook supports raster layers from VRTs and if so, have I correctly gone about adding the layer?
1medium
Title: supervised.exceptions ERROR No models produced Body: 2021-05-24 18:04:12,100 supervised.exceptions ERROR No models produced. Please check your data or submit a Github issue at https://github.com/mljar/mljar-supervised/issues/new. 1_Optuna_LightGBM not trained. Stop training after the first fold. Time needed to train on the first fold 1.0 seconds. The time estimate for training on all folds is larger than total_time_limit. There was an error during 2_Optuna_Xgboost training. Please check AutoML_22\errors.md for details. There was an error during 3_Optuna_CatBoost training. Please check AutoML_22\errors.md for details. There was an error during 4_Optuna_NeuralNetwork training. Please check AutoML_22\errors.md for details. There was an error during 5_Optuna_RandomForest training. Please check AutoML_22\errors.md for details. There was an error during 6_Optuna_ExtraTrees training. Please check AutoML_22\errors.md for details. Traceback (most recent call last): File "<ipython-input-3-4182f0ec13ac>", line 1, in <module> automl.fit(X_train, y_train) File "C:\Users\bhava\Anaconda3\envs\py38\lib\site-packages\supervised\automl.py", line 337, in fit return self._fit(X, y, sample_weight, cv) File "C:\Users\bhava\Anaconda3\envs\py38\lib\site-packages\supervised\base_automl.py", line 1131, in _fit raise e File "C:\Users\bhava\Anaconda3\envs\py38\lib\site-packages\supervised\base_automl.py", line 1048, in _fit raise AutoMLException( AutoMLException: No models produced. Please check your data or submit a Github issue at https://github.com/mljar/mljar-supervised/issues/new.
1medium
Title: Investigate DirRec for RegressionModels Body: See the discussion [here](https://github.com/unit8co/darts/issues/1852#issuecomment-1607100247), and a paper [here](https://www.researchgate.net/publication/221165768_Time_Series_Prediction_using_DirRec_Strategy)
1medium
Title: Parsing YouTube videos with yt-dlp.exe on Windows with VPN Body: ### DO NOT REMOVE OR SKIP THE ISSUE TEMPLATE - [x] I understand that I will be **blocked** if I *intentionally* remove or skip any mandatory\* field ### Checklist - [x] I'm asking a question and **not** reporting a bug or requesting a feature - [x] I've looked through the [README](https://github.com/yt-dlp/yt-dlp#readme) - [x] I've verified that I have **updated yt-dlp to nightly or master** ([update instructions](https://github.com/yt-dlp/yt-dlp#update-channels)) - [x] I've searched [known issues](https://github.com/yt-dlp/yt-dlp/issues/3766) and the [bugtracker](https://github.com/yt-dlp/yt-dlp/issues?q=) for similar questions **including closed ones**. DO NOT post duplicates - [x] I've read the [guidelines for opening an issue](https://github.com/yt-dlp/yt-dlp/blob/master/CONTRIBUTING.md#opening-an-issue) ### Please make sure the question is worded well enough to be understood I have a problem parsing YouTube videos with yt-dlp.exe on Windows, and I hope someone can help me. The operating environment is as follows: 64-bit Windows 10 1809 The latest version of yt-dlp.exe (2025.1.26) VPN: "SoftEther VPN Client Management Tool", do not specify a port. Solution attempt: yt-dlp.exe releases inbound and outbound rules Run yt-dlp.exe with administrator privileges Check VPN, the status is normal, and other software can connect to the Internet normally through VPN. yt-dlp.exe uses a proxy with a specified port to parse video information normally. Download the python module of yt-dlp, release the packaged software, and connect to the Internet normally with VPN Result: The problem still exists. How can yt-dlp.exe connect to the Internet normally on Windows through a VPN proxy without specifying a port and parse YouTube videos? I really hope someone can help me, thank you! In Windows, after allowing yt-dlp.exe to enter and exit the station, the error message of the operation is shown below. ### Provide verbose output that clearly demonstrates the problem - [x] Run **your** yt-dlp command with **-vU** flag added (`yt-dlp -vU <your command line>`) - [x] If using API, add `'verbose': True` to `YoutubeDL` params instead - [x] Copy the WHOLE output (starting with `[debug] Command-line config`) and insert it below ### Complete Verbose Output ```shell [debug] Command-line config: ['-vU', 'https://www.youtube.com/watch?v=uantfXeqTHg'] [debug] Encodings: locale cp936, fs utf-8, pref cp936, out utf-8, error utf-8, screen utf-8 [debug] yt-dlp version [email protected] from yt-dlp/yt-dlp [c8541f8b1] (win_exe) [debug] Python 3.10.11 (CPython AMD64 64bit) - Windows-10-10.0.17763-SP0 (OpenSSL 1.1.1t 7 Feb 2023) [debug] exe versions: none [debug] Optional libraries: Cryptodome-3.21.0, brotli-1.1.0, certifi-2024.12.14, curl_cffi-0.5.10, mutagen-1.47.0, requests-2.32.3, sqlite3-3.40.1, urllib3-2.3.0, websockets-14.1 [debug] Proxy map: {'http': 'http://127.0.0.1:808', 'https': 'http://127.0.0.1:808', 'ftp': 'http://127.0.0.1:808'} [debug] Request Handlers: urllib, requests, websockets, curl_cffi [debug] Loaded 1837 extractors [debug] Fetching release info: https://api.github.com/repos/yt-dlp/yt-dlp/releases/latest ERROR: Unable to obtain version info (('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562DFCF40>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法 连接。'))); Please try again later or visit https://github.com/yt-dlp/yt-dlp/releases/latest [youtube] Extracting URL: https://www.youtube.com/watch?v=uantfXeqTHg [youtube] uantfXeqTHg: Downloading webpage WARNING: [youtube] Unable to download webpage: ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E740A0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')) [youtube] uantfXeqTHg: Downloading iframe API JS WARNING: [youtube] Unable to download webpage: ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E753F0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')) [youtube] uantfXeqTHg: Downloading tv player API JSON WARNING: [youtube] ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E77A30>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')). Retrying (1/3)... [youtube] uantfXeqTHg: Downloading tv player API JSON WARNING: [youtube] ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E74EB0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')). Retrying (2/3)... [youtube] uantfXeqTHg: Downloading tv player API JSON WARNING: [youtube] ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E77880>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')). Retrying (3/3)... [youtube] uantfXeqTHg: Downloading tv player API JSON WARNING: [youtube] Unable to download API page: ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E53AC0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极 拒绝,无法连接。')) (caused by ProxyError("('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E53AC0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。'))")); please report this issue on https://github.com/yt-dlp/yt-dlp/issues?q= , filling out the appropriate issue template. Confirm you are on the latest version using yt-dlp -U [youtube] uantfXeqTHg: Downloading ios player API JSON WARNING: [youtube] ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E76800>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')). Retrying (1/3)... [youtube] uantfXeqTHg: Downloading ios player API JSON WARNING: [youtube] ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E538B0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')). Retrying (2/3)... [youtube] uantfXeqTHg: Downloading ios player API JSON WARNING: [youtube] ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E75180>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')). Retrying (3/3)... [youtube] uantfXeqTHg: Downloading ios player API JSON WARNING: [youtube] Unable to download API page: ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E763B0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极 拒绝,无法连接。')) (caused by ProxyError("('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E763B0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。'))")); please report this issue on https://github.com/yt-dlp/yt-dlp/issues?q= , filling out the appropriate issue template. Confirm you are on the latest version using yt-dlp -U [youtube] uantfXeqTHg: Downloading web player API JSON WARNING: [youtube] ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E755A0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')). Retrying (1/3)... [youtube] uantfXeqTHg: Downloading web player API JSON WARNING: [youtube] ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E761A0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')). Retrying (2/3)... [youtube] uantfXeqTHg: Downloading web player API JSON WARNING: [youtube] ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E98820>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。')). Retrying (3/3)... [youtube] uantfXeqTHg: Downloading web player API JSON WARNING: [youtube] Unable to download API page: ('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E74BB0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极 拒绝,无法连接。')) (caused by ProxyError("('Unable to connect to proxy', NewConnectionError('<urllib3.connection.HTTPSConnection object at 0x0000018562E74BB0>: Failed to establish a new connection: [WinError 10061] 由于目标计算机积极拒绝,无法连接。'))")); please report this issue on https://github.com/yt-dlp/yt-dlp/issues?q= , filling out the appropriate issue template. Confirm you are on the latest version using yt-dlp -U ERROR: [youtube] uantfXeqTHg: Failed to extract any player response; please report this issue on https://github.com/yt-dlp/yt-dlp/issues?q= , filling out the appropriate issue template. Confirm you are on the latest version using yt-dlp -U File "yt_dlp\extractor\common.py", line 742, in extract File "yt_dlp\extractor\youtube.py", line 4481, in _real_extract File "yt_dlp\extractor\youtube.py", line 4445, in _download_player_responses File "yt_dlp\extractor\youtube.py", line 4087, in _extract_player_responses ```
1medium
Title: 1.7 python manage.py cry Body: Hi, it's 4:45am here, good time for a lil pip update (and some tears) ! manage.py doesn't love me anymore ``` Traceback (most recent call last): File "manage.py", line 10, in <module> execute_from_command_line(sys.argv) File "/opt/virtualenvs/diagenv/lib/python2.7/site-packages/django/core/management/__init__.py", line 338, in execute_from_command_line utility.execute() File "/opt/virtualenvs/diagenv/lib/python2.7/site-packages/django/core/management/__init__.py", line 312, in execute django.setup() File "/opt/virtualenvs/diagenv/lib/python2.7/site-packages/django/__init__.py", line 18, in setup apps.populate(settings.INSTALLED_APPS) File "/opt/virtualenvs/diagenv/lib/python2.7/site-packages/django/apps/registry.py", line 108, in populate app_config.import_models(all_models) File "/opt/virtualenvs/diagenv/lib/python2.7/site-packages/django/apps/config.py", line 198, in import_models self.models_module = import_module(models_module_name) File "/usr/lib64/python2.7/importlib/__init__.py", line 37, in import_module __import__(name) File "/opt/projects/diagenv/diagproject/app/models.py", line 13, in <module> from app import helpers File "/opt/projects/diagenv/diagproject/app/helpers.py", line 6, in <module> from rest_framework_jwt import utils File "/opt/virtualenvs/diagenv/lib/python2.7/site-packages/rest_framework_jwt/utils.py", line 6, in <module> from rest_framework_jwt.compat import get_username, get_username_field File "/opt/virtualenvs/diagenv/lib/python2.7/site-packages/rest_framework_jwt/compat.py", line 12, in <module> class Serializer(rest_framework.serializers.Serializer): AttributeError: 'module' object has no attribute 'serializers' ``` Any idea ?
1medium
Title: While updating conda(installing current version), I found some erros, how to solve it? Body: >> conda install conda=23.10.0 Result Collecting package metadata (current_repodata.json): done Solving environment: failed with initial frozen solve. Retrying with flexible solve. Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source. Collecting package metadata (repodata.json): done Solving environment: failed with initial frozen solve. Retrying with flexible solve. Solving environment: \ Found conflicts! Looking for incompatible packages. This can take several minutes. Press CTRL-C to abort. failed UnsatisfiableError: The following specifications were found to be incompatible with each other: Output in format: Requested package -> Available versionsThe following specifications were found to be incompatible with your system: - feature:/linux-64::__glibc==2.31=0 - feature:|@/linux-64::__glibc==2.31=0 Your installed version is: 2.31 Note that strict channel priority may have removed packages required for satisfiability.
1medium
Title: Missing a little f-strings interpolation Body: I think is missing an ```f``` at the beginning of the string in line 266 https://github.com/art049/odmantic/blob/f20f08f8ab1768534c1e743f7539bfe4f8c73bdd/odmantic/model.py#L265-L268
0easy
Title: Subplot margins (Chapter 1, Exercise 2) Body: Hi @rougier, There is a statement about additional figure margins for Exercise 2 solution: https://github.com/rougier/scientific-visualization-book/blob/a6e0607fa8dbcfa5e6251cd7b64b5a094ad4e0f9/code/anatomy/inch-cm.py#L13-L15 And there is a code that performs this adjustment: https://github.com/rougier/scientific-visualization-book/blob/a6e0607fa8dbcfa5e6251cd7b64b5a094ad4e0f9/code/anatomy/inch-cm.py#L27-L38 It seems that in this case we need to have 0.125 inches margin on each side (not 0.25 as in the description), and `margin=0.25` (not 0.125 as in the code) because we multiply this margin by 0.5 when we call `plt.subplots_adjust()`. Is it correct? Thank you.
1medium
Title: Accessing the localStorage of a browser Body: Does solara provide access to (read/write/modify) the browsers "localStorage" ? Thanks
1medium
Title: Analyze API-endpoint failing with example request from Postman-collection Body: So, first of all, thanks for an amazing project! I'm running the API with Docker and when I test the selection of api-requests in the postman collection, Analyze is the only one not working. The posted image data is the default from the collection. Am I missing something here? ![image](https://user-images.githubusercontent.com/10612746/211223966-91ac37ff-cd7c-4db8-8fda-d1ede649304a.png)
1medium
Title: CI: Builds fail with Numpy 1.24 Body: Builds with Python versions newer than 3.7 fail because Numpy have changed their API in release 1.24 and some package requirements aren't restrictive enough. https://github.com/horovod/horovod/actions/runs/3837009090 ``` # ... 2023-01-03T19:09:52.2227909Z #29 28.83 File "/usr/local/lib/python3.8/dist-packages/pandas/_testing.py", line 24, in <module> 2023-01-03T19:09:52.2228233Z #29 28.83 import pandas._libs.testing as _testing 2023-01-03T19:09:52.2228836Z #29 28.83 File "pandas/_libs/testing.pyx", line 10, in init pandas._libs.testing 2023-01-03T19:09:52.2229288Z #29 28.83 File "/usr/local/lib/python3.8/dist-packages/numpy/__init__.py", line 284, in __getattr__ 2023-01-03T19:09:52.2229635Z #29 28.83 raise AttributeError("module {!r} has no attribute " 2023-01-03T19:09:52.2230033Z #29 28.83 AttributeError: module 'numpy' has no attribute 'bool' ```
1medium
Title: DDP issue Body: **Bug Report Checklist** import pyarrow.parquet as pq from autogluon.multimodal import MultiModalPredictor import os train_data = pq.read_table('features_with_label.parquet').to_pandas() metric = 'f1' time_limit = 180 predictor = MultiModalPredictor(label='label', eval_metric=metric) predictor.fit(train_data, time_limit=time_limit) **Describe the bug** I am trying to use MultiModalPredictor to perform classification on combination of text and tabular data. I am running my code on "ml.p3.8xlarge" instance with kernel "conda_pytorch_py310". I am getting below eror “Lightning can’t create new processes if CUDA is already initialized. Did you manually call `torch.cuda.*` functions, have moved the model to the device, or allocated memory on the GPU any other way? Please remove any such calls, or change the selected strategy. You will have to restart the Python kernel.” **Screenshots / Logs** [error_logs.txt](https://github.com/autogluon/autogluon/files/13666797/error_logs.txt) ```python python version = Python 3.10.13 Lightning version = '2.0.9.post0' autogluon = 2.21 ```
1medium
Title: More pre-trained Faster RCNN Model? Body: Hi, according to this [page](http://models.tensorpack.com/FasterRCNN) | COCO-R101C4-MaskRCNN-Standard.npz | 196 MiB | (sha256) | | -- | -- | -- | | COCO-R50C4-MaskRCNN-Standard.npz | 128 MiB | (sha256)| | COCO-R50FPN-MaskRCNN-Standard.npz | 158 MiB | (sha256)| | ImageNet-R101-AlignPadding.npz | 158 MiB | (sha256)| | ImageNet-R50-AlignPadding.npz | 91 MiB | (sha256)| | ImageNet-R50-GroupNorm32-AlignPadding.npz | 88 MiB | (sha256)| Will you provide more pretrained model such as `COCO-R101FPN` or `COCO-R152FPN`? Thank you!
1medium
Title: [RELEASES] Replace direct links to the release details page with links to open the release flyout Body: At the time of writing I don't have a complete list of places that link to release details. There is a Release Hovercard thing that should also exist at all the callsites. In the end we want all links in the app to: - have a release hovercard, i assume this is already the case - to open the new release flyout instead of linking directly to release details or the release list page To help ease the migration the release flyout _could_ have a link along the lines of "Click here to view the old Release Details page" so people can still get back to the old thing. This is probably a good idea, but TBD right now.
1medium
Title: 🐛 [Bug]: Some images does not added to video Body: ### What happened? I found images added to video are less than the searched result image list. ### What type of browser are you seeing the problem on? Microsoft Edge ### What type of Operating System are you seeing the problem on? Windows ### Python Version 3.10 ### Application Version stable branch ### Expected Behavior images should be added properly ### Error Message ```shell got the exception stacktrace `Traceback (most recent call last): File "D:\Codebase\ContentGen\shortGPT\editing_framework\core_editing_engine.py", line 59, in generate_video clip = self.process_image_asset(asset) File "D:\Codebase\ContentGen\shortGPT\editing_framework\core_editing_engine.py", line 212, in process_image_asset clip = ImageClip(asset['parameters']['url']) File "C:\Users\1\AppData\Local\Programs\Python\Python310\lib\site-packages\moviepy\video\VideoClip.py", line 889, in __init__ img = imread(img) File "C:\Users\1\AppData\Local\Programs\Python\Python310\lib\site-packages\imageio\__init__.py", line 97, in imread return imread_v2(uri, format=format, **kwargs) File "C:\Users\1\AppData\Local\Programs\Python\Python310\lib\site-packages\imageio\v2.py", line 359, in imread with imopen(uri, "ri", **imopen_args) as file: File "C:\Users\1\AppData\Local\Programs\Python\Python310\lib\site-packages\imageio\core\imopen.py", line 196, in imopen plugin_instance = candidate_plugin(request, **kwargs) File "C:\Users\1\AppData\Local\Programs\Python\Python310\lib\site-packages\imageio\plugins\pillow.py", line 83, in __init__ with Image.open(request.get_file()): File "C:\Users\1\AppData\Local\Programs\Python\Python310\lib\site-packages\PIL\Image.py", line 2994, in open im = _open_core(fp, filename, prefix, formats) File "C:\Users\1\AppData\Local\Programs\Python\Python310\lib\site-packages\PIL\Image.py", line 2980, in _open_core im = factory(fp, filename) File "C:\Users\1\AppData\Local\Programs\Python\Python310\lib\site-packages\PIL\ImageFile.py", line 112, in __init__ self._open() File "C:\Users\1\AppData\Local\Programs\Python\Python310\lib\site-packages\PIL\ImImagePlugin.py", line 153, in _open s = s + self.fp.readline() AttributeError: 'SeekableFileObject' object has no attribute 'readline'` ``` ### Code to produce this issue. ```shell I add stacktrace code to see what exception it throws shortGPT/editing_framework/core_editing_engine.py ` elif asset_type == 'image': try: print(asset['parameters']['url']) clip = self.process_image_asset(asset) print(clip) except Exception as e: traceback.print_exc() continue` ``` ### Screenshots/Assets/Relevant links [Related imageio issue](https://github.com/imageio/imageio/issues/1007)
1medium
Title: Bug: Parsing tagged unions Body: ### Description When using tagged unions, while the correct OpenAPI schema is generated, decoding the request fails. It also doesn't work with the MsgpackDTO. It seems that the internal litestar.typing.FieldDefinition type doesn't support tagged unions. A question thou, are tagged unions meant to be supported in litestar? I would be happy to contribute to fix/implement the solution if it's meant to be there. ### URL to code causing the issue _No response_ ### MCVE ```python from typing import Annotated, Literal from litestar import Controller, Litestar, post from litestar.contrib.pydantic import PydanticDTO from pydantic import BaseModel, Field class DataA(BaseModel): name: str type: Annotated[Literal["A"], Field("A")] class DataB(BaseModel): name: str type: Annotated[Literal["B"], Field("B")] class DataContainer(BaseModel): value: Annotated[DataA | DataB, Field(discriminator="type")] class TaggedUnionExample(Controller): dto = PydanticDTO[DataContainer] @post("/data/") def post_data(self, data: DataContainer) -> str: return data.value.name app = Litestar(route_handlers=[TaggedUnionExample]) ``` ### Steps to reproduce ```bash 1. `LITESTAR_APP=example:app litestar run --debug` 2. `echo '{"value": {"type": "B", "name": "test"}}' | http post http://localhost:8000/data/` 4. See error ``` ### Screenshots ```bash "![SCREENSHOT_DESCRIPTION](SCREENSHOT_LINK.png)" ``` ### Logs ```bash Traceback (most recent call last): File ".../.venv/lib/python3.12/site-packages/litestar/middleware/exceptions/middleware.py", line 219, in __call__ await self.app(scope, receive, send) File ".../.venv/lib/python3.12/site-packages/litestar/routes/http.py", line 82, in handle response = await self._get_response_for_request( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".../.venv/lib/python3.12/site-packages/litestar/routes/http.py", line 134, in _get_response_for_request return await self._call_handler_function( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".../.venv/lib/python3.12/site-packages/litestar/routes/http.py", line 154, in _call_handler_function response_data, cleanup_group = await self._get_response_data( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".../.venv/lib/python3.12/site-packages/litestar/routes/http.py", line 178, in _get_response_data data = await kwargs["data"] ^^^^^^^^^^^^^^^^^^^^ File ".../.venv/lib/python3.12/site-packages/litestar/_kwargs/extractors.py", line 490, in dto_extractor return data_dto(connection).decode_bytes(body) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".../.venv/lib/python3.12/site-packages/litestar/contrib/pydantic/pydantic_dto_factory.py", line 100, in decode_bytes return super().decode_bytes(value) ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".../.venv/lib/python3.12/site-packages/litestar/dto/base_dto.py", line 97, in decode_bytes return backend.populate_data_from_raw(value, self.asgi_connection) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".../.venv/lib/python3.12/site-packages/litestar/dto/_codegen_backend.py", line 144, in populate_data_from_raw return self._transfer_to_model_type(self.parse_raw(raw, asgi_connection)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".../.venv/lib/python3.12/site-packages/litestar/dto/_backend.py", line 237, in parse_raw result = decode_json(value=raw, target_type=self.annotation, type_decoders=type_decoders) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File ".../.venv/lib/python3.12/site-packages/litestar/serialization/msgspec_hooks.py", line 183, in decode_json return msgspec.json.decode( ^^^^^^^^^^^^^^^^^^^^ TypeError: If a type union contains multiple Struct types, all Struct types must be tagged (via `tag` or `tag_field` kwarg) - type `typing.Annotated[typing.Union[litestar.dto._backend.PostDataDataContainer_0DataARequestBody, litestar.dto._backend.PostDataDataContainer_1DataBRequestBody], msgspec.Meta(examples=[])]` is not supported ``` ### Litestar Version 2.8.2 ### Platform - [X] Linux - [ ] Mac - [ ] Windows - [ ] Other (Please specify in the description above)
1medium
Title: where is the anti_spoofing Body: ### Description I saw anti-spoofing parameters in the documentation, but there is no such code in the actual code ### Additional Info _No response_
1medium
Title: displot instantly close upon display when using seaborn 0.11.2 with matplotlib 3.5.2 Body: I encountered a case of figure window closing instantly when trying to display a displot. To reproduce, try the following with seaborn version 0.11.2 and matplotlib version 3.5.2 ```python import seaborn import matplotlib.pyplot as plt sns.displot([0,0,1,1,2,3,3,1,0]) plt.show() ``` In seaborn version 0.11.2, a figure window will flash on the screen and instantly disappear, whereas in seaborn version 0.11.1, a histogram bar plot is displayed in a new window that persists until I closed it. After some digging, I suspect that this is due to the handling of the `backend` entry of `matplotlib.rcParams`. `rcParams["backend"]` by default is initialized with a sentinel object `matplotlib.rcsetup._auto_backend_sentinel`. The first time someone tries to access `rcParams["backend"]` , matplotlib will call `matplotlib.pyplot.switch_backend` to swap in the actual backend object. The function `matplotlib.pyplot.switch_backend`, when called, will first close all currently open figures. In seaborn version 0.11.2, `displot` will try to create a `FacetGrid` object in which to place the plot. In the constructor of `FacetGrid`, [at line 408](https://github.com/mwaskom/seaborn/blob/v0.11.2/seaborn/axisgrid.py#L408), it creates a Figure object within a context manager. As a result, the `rcParams["backend"]` gets reverted to the sentinel object upon exit from the with block. The created Figure would get automatically closed the next time the code tries to access `rcParams["backend"]`.
1medium
Title: Support for async requests or webhooks Body: <!-- ⚠️ BEFORE SUBMITTING, READ: We're excited for your request! However, here are things we are not interested in: - Decorators. - Doing the same thing in multiple ways. - Adding more layers of abstraction... tree-depth should be 1 at most. - Features that over-engineer or complicate the code internals. - Linters, and crud that complicates projects. --> ---- ## 🚀 Feature <!-- A clear and concise description of the feature proposal --> Is there currently a way to run inference and get the result by polling or a webhook callback? ### Motivation <!-- Please outline the motivation for the proposal. Is your feature request related to a problem? e.g., I'm always frustrated when [...]. If this is related to another GitHub issue, please link here too... --> If an inference takes a long time to run lets say 30 min you dont want the connection to drop because you will have to rerun the inference especially on a shaky connection. ### Pitch <!-- A clear and concise description of what you want to happen. --> A webhook callback or polling method can let us run inference as a background task based off a uuid or something the user specifies so that they can come back at a later time for the result. can also help integrations so the inference is not a blocking request. ### Alternatives <!-- A clear and concise description of any alternative solutions or features you've considered, if any. --> [Cog](https://cog.run/http/#webhooks) from replicate implements a webhook ### Additional context <!-- Add any other context or screenshots about the feature request here. -->
1medium
Title: Open IE separates auxiliary and participle into separate tuples Body: <!-- Please fill this template entirely and do not erase any of it. We reserve the right to close without a response bug reports which are incomplete. If you have a question rather than a bug, please ask on [Stack Overflow](https://stackoverflow.com/questions/tagged/allennlp) rather than posting an issue here. --> ## Description <!-- Please provide a clear and concise description of what the bug is here. --> <details> <summary><b>OpenIE separates auxiliary and participle into separate tuples. This affects the online demo and my local installation of AllenNLP.</b></summary> <p> In the sentence "He is running to the store", my understanding is that there is only one predicate and that the output of OpenIE should be a single tuple: [Arg0: He] [V: is running] [Arg1: to the store] Instead, I get two tuples where the first is simply the auxiliary: [V: is] [Arg0: He] [V: running] [Arg1: to the store] You can see the examples linked below from the online demo to see that it affects other sentences/auxiliaries too. I also noticed the SRL demo returns two predicates for the same sentence. </p> </details> ## Related issues or possible duplicates - None ## Environment Online demo, though I initially noticed this on my local installation of AllenNLP. ## Steps to reproduce https://demo.allennlp.org/open-information-extraction/s/he-has-moved-out-appartment/L1E3P1E9G4 https://demo.allennlp.org/open-information-extraction/s/he-is-running-to-store/E5E4Z1H6D9
1medium
Title: So Logfire logs are actually traces? Body: ### Question As per title: https://github.com/pydantic/logfire/blob/770780d4e0f5610bd8cbd596029d0cb1e23f25ae/logfire/_internal/main.py#L654-L670 Asking because I have been exploring OpenTelemetry recently and was disappointed to find that [the client APIs for logging in Python are still in development](https://opentelemetry.io/docs/languages/python/#status-and-releases) and seemingly unstable: ![image](https://github.com/kedro-org/kedro/assets/316517/372ada41-60b2-45d1-a98f-272247732695)
3misc
Title: DateTime comparisons behaving unexpectedly Body: <!-- Thanks for helping us improve Prisma Client Python! 🙏 Please follow the sections in the template and provide as much information as possible about your problem, e.g. by enabling additional logging output. See https://prisma-client-py.readthedocs.io/en/stable/reference/logging/ for how to enable additional logging output. --> ## Bug description <!-- A clear and concise description of what the bug is. --> A `find_many` query based on a `datetime` field returns unexpected results. `gt/gte/lt/lte` should be able to be used to specify ranges of availability (either in isolation or in combination), but diverge from what I was expecting. ## How to reproduce 1. Clone https://github.com/iiian/prisma_python_datefailure_demo 2. `prisma generate && prisma db push` to produce cli and db files the demo model: ```prisma model Demo { id Int @id created_at DateTime @default(now()) } ``` 3. open db, `sqlite3 database.db` 4. `INSERT INTO Demo (id) VALUES (1);` to create a record with the present moment in the `created_at` field 5. `SELECT * FROM Demo;` to confirm its existence ``` sqlite> SELECT * FROM Demo; 1|2022-01-08 08:01:58 ``` 6. run `python3 demo.py`, and observe test results: ### TESTS ```python today = datetime.utcnow() # 1. does a record exist who was created before the present moment? (Expecting true) print(await client.demo.find_many(where={ 'created_at': { 'lt': today } })) # 2. " " " before or at present (Expecting true) print(await client.demo.find_many(where={ 'created_at': { 'lte': today } })) # 3. does a record exist who was created after the present moment? (Expecting false) print(await client.demo.find_many(where={ 'created_at': { 'gt': today } })) # 4. " " " after or at present moment (Expecting false) print(await client.demo.find_many(where={ 'created_at': { 'gte': today } })) # 5. " " " after this morning, and before this time tomorrow (Expecting true) print(await client.demo.find_many(where={ # (I think syntax is correct? doesn't complain) 'created_at': { 'gt': datetime(year=today.year, month=today.month, day=today.day), 'lt': today + relativedelta(day=1), } })) # 6. " " " after this time tomorrow, and before this morning (impossible, so false) print(await client.demo.find_many(where={ 'created_at': { 'gt': today + relativedelta(day=1), 'lt': datetime(year=today.year, month=today.month, day=today.day) } })) # 7. after this morning, before tomorrow with and syntax (I think this is correct?, Expecting true) print(await client.demo.find_many(where={ 'AND': [ { 'created_at': { 'lt': today + relativedelta(day=1), } }, { 'created_at': { 'gt': datetime(year=today.year, month=today.month, day=today.day) } } ] })) # 8. same as sixth test case, should be impossible, just with and syntax print(await client.demo.find_many(where={ 'AND': [ { 'created_at': { 'gt': today + relativedelta(day=1), } }, { 'created_at': { 'lt': datetime(year=today.year, month=today.month, day=today.day) } } ] })) ``` ### TEST RESULTS ```bash # Test 1 [] # Test 2 [] # Test 3 [Demo(id=1, created_at=datetime.datetime(2022, 1, 8, 8, 1, 58, tzinfo=datetime.timezone.utc))] # Test 4 [Demo(id=1, created_at=datetime.datetime(2022, 1, 8, 8, 1, 58, tzinfo=datetime.timezone.utc))] # Test 5 [] # Test 6 [] # Test 7 [] # Test 8 [] ``` Prisma python, therefore, currently claiming record I created before running demo was **created after** I ran the demo. Also, seems that including `lt(e)` in the query may result in immediate loss? I haven't tried specifying a time in the future. <!-- Steps to reproduce the behavior: 1. Go to '...' 2. Change '....' 3. Run '....' 4. See error --> ## Expected behavior ### Test Result Expectations ```bash # Test 1 [Demo(id=1, created_at=datetime.datetime(2022, 1, 8, 8, 1, 58, tzinfo=datetime.timezone.utc))] # Test 2 [Demo(id=1, created_at=datetime.datetime(2022, 1, 8, 8, 1, 58, tzinfo=datetime.timezone.utc))] # Test 3 [] # Test 4 [] # Test 5 [Demo(id=1, created_at=datetime.datetime(2022, 1, 8, 8, 1, 58, tzinfo=datetime.timezone.utc))] # Test 6 [] # Test 7 [Demo(id=1, created_at=datetime.datetime(2022, 1, 8, 8, 1, 58, tzinfo=datetime.timezone.utc))] # Test 8 [] ``` ## Prisma information <!-- Your Prisma schema, Prisma Client Python queries, ... Do not include your database credentials when sharing your Prisma schema! --> ```prisma // database datasource db { provider = "sqlite" url = "file:database.db" } // generator generator client { provider = "prisma-client-py" } model Demo { id Int @id created_at DateTime @default(now()) } ``` ## Environment & setup <!-- In which environment does the problem occur --> - OS: <!--[e.g. Mac OS, Windows, Debian, CentOS, ...]--> Tested on Windows 10, and macOS Big Sur - Database: <!--[PostgreSQL, MySQL, MariaDB or SQLite]--> Sqlite3 - Python version: <!--[Run `python -V` to see your Python version]--> 3.10 Windows, 3.9 macOS - Prisma version: 3.7.0, 0.4.3 <!--[Run `prisma py version` to see your Prisma version and paste it between the ´´´]-->
1medium
Title: Wrong skeleton structure issue when trying to load a svg skeleton file Body: ### Actions before raising this issue - [X] I searched the existing issues and did not find anything similar. - [X] I read/searched [the docs](https://docs.cvat.ai/docs/) ### Steps to Reproduce Hi folks, I created a skeleton in a project using CVAT self hosted version and then exported it into a svg file. Then I created a new project and tried to upload my previous svg file as a new skeleton but I got "Wrong skeleton structure" error. Do you have any idea how to fix this issue ? Thanks a lot ![Error](https://github.com/user-attachments/assets/c54f6ac3-8c7f-4337-97aa-26156c31fc65) ### Expected Behavior The upload function should load my svg file as a new skeleton ### Possible Solution _No response_ ### Context _No response_ ### Environment CVAT installed on Windows laptop Ubuntu and Docker Desktop
1medium
Title: Where will jina write logs to when it triggers `continue_on_error`? Body: We use `post` to send request to server with parameter `continue_on_error`. `if set, a Request that causes an error will be logged only without blocking the further requests.` So where will it be logged to and what will write to the logs.
1medium
Title: Documentation in readme for allowed parameter values Body: It would be great to include the allowed parameter values in the GitHub read-me. When setting parameters for a production server I had to guess or search many of them in the Discourse forum for that kind of information. Example of questions that this documentation would avoid: - --api-keys is a flag. On the command line it's obvious. But when using LT_API_KEYS, is defining it enough? Should I put true? - Is LT_REQUIRE_API_KEY_ORIGIN a toggle, with the origin automatically detected? Or a string? I which case, can I put a wildcard there such as *.mydomain.com ?
0easy
Title: Optional GenericRel support Body: Hi, the new version (0.16), uses `GenericRel` and `ContentType` imported in `mixins.py` lines 4 and 5, however this breaks all projects that do not use `contenttype` modules, especially for those who use django as microservices... removing all django stuff (auth, contenttype, messages and etc)...
1medium
Title: 退市股的基本数据里缺行业、地域等参数,可能影响回测。 Body: 调用stock_basic接口,查询已退市股票,缺少行业、地域等数据,可能影响回测。 ![image](https://user-images.githubusercontent.com/9562970/152683120-d34285bd-7e5f-4ed4-8dde-e4899aef7155.png) 用户id:213079
1medium
Title: 404 Client Error (only on certain tickers - which are still active/not delisted) Body: ### Describe bug I have a program that cycles through a list of all the S&P500 companies to check the 'upgrades_downgrades' attribute of each one (with a for loop). It gets the tickers from a well maintained Wikipedia page (scraping with BeautifulSoup4). All the tickers are up to date (I have personally checked), are able to be found on the Yahoo Finance website and are not delisted. All the tickers are in the correct format, as I apply that after they are scraped. While most of the tickers work once the program starts iterating through them, there are a few that have been raising this 404 Client Error since maybe about a month or two ago. Again, the tickers are perfectly fine and the implementation is correct (this is evident in the fact that most of the 503 tickers get a normal response during the iteration). I will provide the full 404 Client Error I receive on some of the symbols in the debug log section. ### Simple code that reproduces your problem The simplest way to reproduce the problem is by putting a couple of the tickers I know are "bad" into a list with a few good ones and making the same type of call on them: ```python import datetime import yfinance as yf error_date = datetime.date(2024, 6, 6) list_with_some_bad_tickers = ['COF', 'CRL', 'COO', 'FANG', 'LIN', 'LULU'] tickers_data = yf.Tickers(' '.join(list_with_some_bad_tickers)) for symbol in list_with_some_bad_tickers: try: ticker = tickers_data.tickers[symbol] actions = ticker.upgrades_downgrades actions_on_error_date = actions[actions.index.date == error_date] # Do not print empty DataFrames (for tickers without analyst activity) if not actions_on_error_date.empty: # Filter the DataFrame based on multiple conditions filtered_actions = actions_on_error_date[(actions_on_error_date['Action'].isin(['up', 'init'])) & (actions_on_error_date['ToGrade'].isin(['Buy', 'Outperform', 'Overweight']))] if not filtered_actions.empty: # Print the filtered DataFrame print(f"Analyst action(s) for {symbol} on {error_date}:") print(filtered_actions) print() except Exception as e: print(f"General error fetching data for {symbol}: {e}") print() ``` ### Debug log 404 Client Error: Not Found for url: https://query2.finance.yahoo.com/v10/finance/quoteSummary/COO?modules=upgradeDowngradeHistory&corsDomain=finance.yahoo.com&formatted=false&symbol=COO&crumb=jroCz7O300G 404 Client Error: Not Found for url: https://query2.finance.yahoo.com/v10/finance/quoteSummary/LIN?modules=upgradeDowngradeHistory&corsDomain=finance.yahoo.com&formatted=false&symbol=LIN&crumb=jroCz7O300G *Note*: When running the code, the 'General error fetching data for {symbol}: 'RangeIndex' object has no attribute 'date'' that is also raised in these two instances is avoidable, and I don't think it has to do with the 404 Client Error. I did not want to make my code snippet unnecessarily long, but I do avoid that error by using pd.to_datetime() in each iteration. It has no bearing on the 404 Client Error, for which I have tried everything I know how to do and still can't catch or avoid it! **My apologies for not being more familiar with the logging/debugging process. I've been stuck on this bug for a while today and don't have the bandwidth to figure out the proper way to document this Debug log right now. ### Bad data proof I believe this would be considered the 'bad data': 404 Client Error: Not Found for url: https://query2.finance.yahoo.com/v10/finance/quoteSummary/COO?modules=upgradeDowngradeHistory&corsDomain=finance.yahoo.com&formatted=false&symbol=COO&crumb=jroCz7O300G 404 Client Error: Not Found for url: https://query2.finance.yahoo.com/v10/finance/quoteSummary/LIN?modules=upgradeDowngradeHistory&corsDomain=finance.yahoo.com&formatted=false&symbol=LIN&crumb=jroCz7O300G ### `yfinance` version yfinance 0.2.40 ### Python version 3.10.12 ### Operating system LinuxLite (Ubuntu)
1medium
Title: gp_minimize: ranges can be a different datatype than initial guess Body: I am using skopt version 0.9.0 and numpy 1.23.5 (due to an error I got that is specified in #1138). I found, after downgrading numpy from 1.24.1, that I had made an error in specifying the ranges. They were ints instead of floats. however, my initial x-guess was a float. I made a minimal example below: ```python from skopt import gp_minimize def find_sqrt(x): """find square root of value y given a guess x""" y = 12.5 x = x[0] y_guess = x**2 return abs(y_guess - y) x0 = [1.0] y0 = None res1 = gp_minimize( find_sqrt, [ (0.0, 12.0), ], n_calls=12, x0=x0, y0=y0, ) print("guesses with proper float ranges: ", res1.x_iters) res2 = gp_minimize( find_sqrt, [ (0, 12), ], n_calls=12, x0=x0, y0=y0, ) print("guesses with improper int ranges: ", res2.x_iters) ``` which outputs: ``` guesses with proper float ranges: [[1.0], [8.114281197171252], [9.021416917982528], [4.955995220826303], [6.649848371121621], [11.582469882107137], [3.953831466277097], [2.1390536274803877], [2.6277353173592157], [5.884289789665528], [3.918451377145078], [3.5048487566802144]] guesses with improper int ranges [[1.0], [6], [9], [5], [0], [11], [1], [1], [7], [3], [4], [4]] ``` If this is expected behavior and I missed something in the docs then I am fine with closing the issue, but I would think that there would be an error thrown if the first and second guesses are different datatypes for the same variable.
1medium
Title: [Bug]: Memory leak in video OP Body: ### Before Reporting 报告之前 - [X] I have pulled the latest code of main branch to run again and the bug still existed. 我已经拉取了主分支上最新的代码,重新运行之后,问题仍不能解决。 - [X] I have read the [README](https://github.com/alibaba/data-juicer/blob/main/README.md) carefully and no error occurred during the installation process. (Otherwise, we recommend that you can ask a question using the Question template) 我已经仔细阅读了 [README](https://github.com/alibaba/data-juicer/blob/main/README_ZH.md) 上的操作指引,并且在安装过程中没有错误发生。(否则,我们建议您使用Question模板向我们进行提问) ### Search before reporting 先搜索,再报告 - [X] I have searched the Data-Juicer [issues](https://github.com/alibaba/data-juicer/issues) and found no similar bugs. 我已经在 [issue列表](https://github.com/alibaba/data-juicer/issues) 中搜索但是没有发现类似的bug报告。 ### OS 系统 Ubuntu ### Installation Method 安装方式 pip ### Data-Juicer Version Data-Juicer版本 _No response_ ### Python Version Python版本 3.9 ### Describe the bug 描述这个bug 1. Video container should be closed after calling `load_data_with_context` in every video OP. 2. After the stream is decoded, the stream should be closed also. Please refer to [PyAV issue](https://github.com/PyAV-Org/PyAV/issues/1117). ### To Reproduce 如何复现 Run the `video_tagging_from_frames_mapper` OP for large dataset. ### Configs 配置信息 _No response_ ### Logs 报错日志 _No response_ ### Screenshots 截图 _No response_ ### Additional 额外信息 _No response_
2hard
Title: In certain situations, `setdefault` of a Dict returns an incorrect value. Body: The `example` function in the following code is expected to return `DictType[int64,array(float64, 1d, A)]<iv=None>({1: [1000. 0.]})`, but instead, it returns `DictType[int64,array(float64, 1d, A)]<iv=None>({1: [0. 0.]})`. The issue is resolved when the line `b = {i: 1 for i in n}` is removed. The version of `numba` being used is 0.60.0. ```python import numpy as np import numba from numba.core import types @numba.njit def example(): a = numba.typed.Dict.empty(key_type=types.int64, value_type=types.float64[:]) b = numba.typed.Dict.empty(key_type=types.int64, value_type=types.int64) n = np.array([1,2,3]) s = a.setdefault(1, np.array([0., 0.])) s[0] += 1000. s[1] = 0. b = {i: 1 for i in n} return a ```
1medium
Title: write doesn't call write_array_formula Body: Hi, I am using XlsxWriter to write array formulas. The [documentation](http://xlsxwriter.readthedocs.io/worksheet.html?#write_array_formula) claims write() should call write_array_formula() for use when it returns a single value, but it is only called by write_formula(). I am using Python version 3.6 and XlsxWriter 0.9.6 and Excel version 2010 and 2016. Here is some code that demonstrates the problem: ```python import xlsxwriter # Create a new workbook and add a worksheet workbook = xlsxwriter.Workbook('array_formula.xlsx') worksheet = workbook.add_worksheet() # Write some test data. worksheet.write('B1', 500) worksheet.write('B2', 10) worksheet.write('C1', 300) worksheet.write('C2', 15) # Write an array formula that returns a single value worksheet.write_formula('A1', '{=SUM(B1:C1*B2:C2)}') worksheet.write('A2', '{=SUM(B1:C1*B2:C2)}') workbook.close() ``` A1 is an array formula while A2 is a string.
1medium
Title: Many tests fail Body: Ubuntu 16.10 tag: 0.9.8 Building & testing with: ``` echo -------- echo Cleaning echo -------- cd git-httpie sudo -u actionmystique -H git-reset-clean-pull-checkout.sh $branch $tag echo ----------------------- echo Installing Dependencies echo ----------------------- pip install -r requirements-dev.txt -U echo -------- echo Building echo -------- sudo -u actionmystique -H python setup.py build echo --------- echo Installing echo --------- python setup.py install echo -------- echo Testing echo -------- python setup.py test ``` leads to: ``` -------- Testing -------- running test running egg_info writing requirements to httpie.egg-info/requires.txt writing httpie.egg-info/PKG-INFO writing top-level names to httpie.egg-info/top_level.txt writing dependency_links to httpie.egg-info/dependency_links.txt writing entry points to httpie.egg-info/entry_points.txt reading manifest file 'httpie.egg-info/SOURCES.txt' reading manifest template 'MANIFEST.in' writing manifest file 'httpie.egg-info/SOURCES.txt' running build_ext ============================================================================ test session starts ============================================================================ platform linux2 -- Python 2.7.12+, pytest-3.0.7, py-1.4.33, pluggy-0.4.0 -- /usr/bin/python cachedir: .cache rootdir: /home/actionmystique/src/HTTPie/git-httpie, inifile: pytest.ini plugins: xdist-1.15.0, timeout-1.2.0, httpbin-0.2.3, cov-2.4.0, catchlog-1.2.2 collected 236 items httpie/utils.py::httpie.utils.humanize_bytes PASSED tests/test_auth.py::test_basic_auth[http] PASSED tests/test_auth.py::test_digest_auth[http---auth-type] PASSED tests/test_auth.py::test_digest_auth[http--A] PASSED tests/test_auth.py::test_credentials_in_url[http] PASSED tests/test_auth.py::test_credentials_in_url_auth_flag_has_priority[http] PASSED tests/test_downloads.py::TestDownloads::test_actual_download[http] PASSED tests/test_downloads.py::TestDownloads::test_download_with_Content_Length[http] PASSED tests/test_downloads.py::TestDownloads::test_download_no_Content_Length[http] PASSED tests/test_downloads.py::TestDownloads::test_download_interrupted[http] PASSED tests/test_httpie.py::test_GET[http] PASSED tests/test_httpie.py::test_DELETE[http] PASSED tests/test_httpie.py::test_PUT[http] PASSED tests/test_httpie.py::test_POST_JSON_data[http] PASSED tests/test_httpie.py::test_POST_form[http] PASSED tests/test_httpie.py::test_POST_form_multiple_values[http] PASSED tests/test_httpie.py::test_POST_stdin[http] PASSED tests/test_httpie.py::test_headers[http] PASSED tests/test_httpie.py::test_headers_unset[http] PASSED tests/test_httpie.py::test_unset_host_header[http] SKIPPED tests/test_httpie.py::test_headers_empty_value[http] PASSED tests/test_httpie.py::test_json_input_preserve_order[http] PASSED tests/test_auth.py::test_basic_auth[https] PASSED tests/test_auth.py::test_digest_auth[https---auth-type] PASSED tests/test_auth.py::test_digest_auth[https--A] PASSED tests/test_auth.py::test_credentials_in_url[https] PASSED tests/test_auth.py::test_credentials_in_url_auth_flag_has_priority[https] PASSED tests/test_downloads.py::TestDownloads::test_actual_download[https] PASSED tests/test_downloads.py::TestDownloads::test_download_with_Content_Length[https] PASSED tests/test_downloads.py::TestDownloads::test_download_no_Content_Length[https] PASSED tests/test_downloads.py::TestDownloads::test_download_interrupted[https] PASSED tests/test_httpie.py::test_GET[https] PASSED tests/test_httpie.py::test_DELETE[https] PASSED tests/test_httpie.py::test_PUT[https] PASSED tests/test_httpie.py::test_POST_JSON_data[https] PASSED tests/test_httpie.py::test_POST_form[https] PASSED tests/test_httpie.py::test_POST_form_multiple_values[https] PASSED tests/test_httpie.py::test_POST_stdin[https] PASSED tests/test_httpie.py::test_headers[https] PASSED tests/test_httpie.py::test_headers_unset[https] PASSED tests/test_httpie.py::test_unset_host_header[https] SKIPPED tests/test_httpie.py::test_headers_empty_value[https] PASSED tests/test_httpie.py::test_json_input_preserve_order[https] PASSED tests/test_auth.py::test_password_prompt PASSED tests/test_auth.py::test_only_username_in_url[[email protected]] PASSED tests/test_auth.py::test_only_username_in_url[username:@example.org] PASSED tests/test_auth.py::test_missing_auth PASSED tests/test_auth_plugins.py::test_auth_plugin_parse_auth_false PASSED tests/test_auth_plugins.py::test_auth_plugin_require_auth_false PASSED tests/test_auth_plugins.py::test_auth_plugin_require_auth_false_and_auth_provided PASSED tests/test_auth_plugins.py::test_auth_plugin_prompt_password_false PASSED tests/test_binary.py::TestBinaryRequestData::test_binary_stdin PASSED tests/test_binary.py::TestBinaryRequestData::test_binary_file_path PASSED tests/test_binary.py::TestBinaryRequestData::test_binary_file_form PASSED tests/test_binary.py::TestBinaryResponseData::test_binary_suppresses_when_terminal PASSED tests/test_binary.py::TestBinaryResponseData::test_binary_suppresses_when_not_terminal_but_pretty PASSED tests/test_binary.py::TestBinaryResponseData::test_binary_included_and_correct_when_suitable PASSED tests/test_cli.py::TestItemParsing::test_invalid_items PASSED tests/test_cli.py::TestItemParsing::test_escape_separator PASSED tests/test_cli.py::TestItemParsing::test_backslash_before_non_special_character_does_not_escape[path=c:\windows-path-=-c:\windows] PASSED tests/test_cli.py::TestItemParsing::test_backslash_before_non_special_character_does_not_escape[path=c:\windows\-path-=-c:\windows\] PASSED tests/test_cli.py::TestItemParsing::test_backslash_before_non_special_character_does_not_escape[path\==c:\windows-path=-=-c:\windows] PASSED tests/test_cli.py::TestItemParsing::test_escape_longsep PASSED tests/test_cli.py::TestItemParsing::test_valid_items PASSED tests/test_cli.py::TestItemParsing::test_multiple_file_fields_with_same_field_name PASSED tests/test_cli.py::TestItemParsing::test_multiple_text_fields_with_same_field_name PASSED tests/test_cli.py::TestQuerystring::test_query_string_params_in_url PASSED tests/test_cli.py::TestQuerystring::test_query_string_params_items PASSED tests/test_cli.py::TestQuerystring::test_query_string_params_in_url_and_items_with_duplicates PASSED tests/test_cli.py::TestLocalhostShorthand::test_expand_localhost_shorthand PASSED tests/test_cli.py::TestLocalhostShorthand::test_expand_localhost_shorthand_with_slash PASSED tests/test_cli.py::TestLocalhostShorthand::test_expand_localhost_shorthand_with_port PASSED tests/test_cli.py::TestLocalhostShorthand::test_expand_localhost_shorthand_with_path PASSED tests/test_cli.py::TestLocalhostShorthand::test_expand_localhost_shorthand_with_port_and_slash PASSED tests/test_cli.py::TestLocalhostShorthand::test_expand_localhost_shorthand_with_port_and_path PASSED tests/test_cli.py::TestLocalhostShorthand::test_dont_expand_shorthand_ipv6_as_shorthand PASSED tests/test_cli.py::TestLocalhostShorthand::test_dont_expand_longer_ipv6_as_shorthand PASSED tests/test_cli.py::TestLocalhostShorthand::test_dont_expand_full_ipv6_as_shorthand PASSED tests/test_cli.py::TestArgumentParser::test_guess_when_method_set_and_valid PASSED tests/test_cli.py::TestArgumentParser::test_guess_when_method_not_set PASSED tests/test_cli.py::TestArgumentParser::test_guess_when_method_set_but_invalid_and_data_field PASSED tests/test_cli.py::TestArgumentParser::test_guess_when_method_set_but_invalid_and_header_field PASSED tests/test_cli.py::TestArgumentParser::test_guess_when_method_set_but_invalid_and_item_exists PASSED tests/test_cli.py::TestNoOptions::test_valid_no_options PASSED tests/test_cli.py::TestNoOptions::test_invalid_no_options PASSED tests/test_cli.py::TestIgnoreStdin::test_ignore_stdin PASSED tests/test_cli.py::TestIgnoreStdin::test_ignore_stdin_cannot_prompt_password PASSED tests/test_cli.py::TestSchemes::test_invalid_custom_scheme PASSED tests/test_cli.py::TestSchemes::test_invalid_scheme_via_via_default_scheme PASSED tests/test_cli.py::TestSchemes::test_default_scheme PASSED tests/test_config.py::test_default_options PASSED tests/test_config.py::test_default_options_overwrite PASSED tests/test_config.py::test_migrate_implicit_content_type PASSED tests/test_defaults.py::TestImplicitHTTPMethod::test_implicit_GET PASSED tests/test_defaults.py::TestImplicitHTTPMethod::test_implicit_GET_with_headers PASSED tests/test_defaults.py::TestImplicitHTTPMethod::test_implicit_POST_json PASSED tests/test_defaults.py::TestImplicitHTTPMethod::test_implicit_POST_form PASSED tests/test_defaults.py::TestImplicitHTTPMethod::test_implicit_POST_stdin PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_GET_no_data_no_auto_headers PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_POST_no_data_no_auto_headers PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_POST_with_data_auto_JSON_headers PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_GET_with_data_auto_JSON_headers PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_POST_explicit_JSON_auto_JSON_accept PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_GET_explicit_JSON_explicit_headers PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_POST_form_auto_Content_Type PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_POST_form_Content_Type_override PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_print_only_body_when_stdout_redirected_by_default PASSED tests/test_defaults.py::TestAutoContentTypeAndAcceptHeaders::test_print_overridable_when_stdout_redirected PASSED tests/test_docs.py::test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/AUTHORS.rst] FAILED tests/test_docs.py::test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/CONTRIBUTING.rst] FAILED tests/test_docs.py::test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/CHANGELOG.rst] FAILED tests/test_docs.py::test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/README.rst] FAILED tests/test_docs.py::test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/tests/README.rst] FAILED tests/test_downloads.py::TestDownloadUtils::test_Content_Range_parsing PASSED tests/test_downloads.py::TestDownloadUtils::test_Content_Disposition_parsing[attachment; filename=hello-WORLD_123.txt-hello-WORLD_123.txt] PASSED tests/test_downloads.py::TestDownloadUtils::test_Content_Disposition_parsing[attachment; filename=".hello-WORLD_123.txt"-hello-WORLD_123.txt] PASSED tests/test_downloads.py::TestDownloadUtils::test_Content_Disposition_parsing[attachment; filename="white space.txt"-white space.txt] PASSED tests/test_downloads.py::TestDownloadUtils::test_Content_Disposition_parsing[attachment; filename="\"quotes\".txt"-"quotes".txt] PASSED tests/test_downloads.py::TestDownloadUtils::test_Content_Disposition_parsing[attachment; filename=/etc/hosts-hosts] PASSED tests/test_downloads.py::TestDownloadUtils::test_Content_Disposition_parsing[attachment; filename=-None] PASSED tests/test_downloads.py::TestDownloadUtils::test_filename_from_url PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[foo.bar-0-foo.bar] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[foo.bar-1-foo.bar-1] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[foo.bar-10-foo.bar-10] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[AAAAAAAAAAAAAAAAAAAA-0-AAAAAAAAAA] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[AAAAAAAAAAAAAAAAAAAA-1-AAAAAAAA-1] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[AAAAAAAAAAAAAAAAAAAA-10-AAAAAAA-10] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[AAAAAAAAAAAAAAAAAAAA.txt-0-AAAAAA.txt] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[AAAAAAAAAAAAAAAAAAAA.txt-1-AAAA.txt-1] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[foo.AAAAAAAAAAAAAAAAAAAA-0-foo.AAAAAA] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[foo.AAAAAAAAAAAAAAAAAAAA-1-foo.AAAA-1] PASSED tests/test_downloads.py::TestDownloadUtils::test_unique_filename[foo.AAAAAAAAAAAAAAAAAAAA-10-foo.AAA-10] PASSED tests/test_errors.py::test_error PASSED tests/test_errors.py::test_error_traceback PASSED tests/test_errors.py::test_timeout PASSED tests/test_exit_status.py::test_keyboard_interrupt_during_arg_parsing_exit_status PASSED tests/test_exit_status.py::test_keyboard_interrupt_in_program_exit_status PASSED tests/test_exit_status.py::test_ok_response_exits_0 PASSED tests/test_exit_status.py::test_error_response_exits_0_without_check_status PASSED tests/test_exit_status.py::test_timeout_exit_status PASSED tests/test_exit_status.py::test_3xx_check_status_exits_3_and_stderr_when_stdout_redirected PASSED tests/test_exit_status.py::test_3xx_check_status_redirects_allowed_exits_0 PASSED tests/test_exit_status.py::test_4xx_check_status_exits_4 PASSED tests/test_exit_status.py::test_5xx_check_status_exits_5 PASSED tests/test_httpie.py::test_debug PASSED tests/test_httpie.py::test_help PASSED tests/test_httpie.py::test_version PASSED tests/test_httpie.py::test_headers_empty_value_with_value_gives_error PASSED tests/test_output.py::test_output_option[True] PASSED tests/test_output.py::test_output_option[False] PASSED tests/test_output.py::TestVerboseFlag::test_verbose PASSED tests/test_output.py::TestVerboseFlag::test_verbose_form PASSED tests/test_output.py::TestVerboseFlag::test_verbose_json PASSED tests/test_output.py::TestVerboseFlag::test_verbose_implies_all PASSED tests/test_output.py::TestColors::test_get_lexer[application/json-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[application/json+foo-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[application/foo+json-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[application/json-foo-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[application/x-json-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[foo/json-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[foo/json+bar-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[foo/bar+json-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[foo/json-foo-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[foo/x-json-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[application/vnd.comverge.grid+hal+json-False-None-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[text/plain-True-{}-JSON] PASSED tests/test_output.py::TestColors::test_get_lexer[text/plain-True-foo-Text only] PASSED tests/test_output.py::TestColors::test_get_lexer_not_found PASSED tests/test_output.py::TestPrettyOptions::test_pretty_enabled_by_default PASSED tests/test_output.py::TestPrettyOptions::test_pretty_enabled_by_default_unless_stdout_redirected PASSED tests/test_output.py::TestPrettyOptions::test_force_pretty PASSED tests/test_output.py::TestPrettyOptions::test_force_ugly PASSED tests/test_output.py::TestPrettyOptions::test_subtype_based_pygments_lexer_match PASSED tests/test_output.py::TestPrettyOptions::test_colors_option PASSED tests/test_output.py::TestPrettyOptions::test_format_option PASSED tests/test_output.py::TestLineEndings::test_CRLF_headers_only PASSED tests/test_output.py::TestLineEndings::test_CRLF_ugly_response PASSED tests/test_output.py::TestLineEndings::test_CRLF_formatted_response PASSED tests/test_output.py::TestLineEndings::test_CRLF_ugly_request PASSED tests/test_output.py::TestLineEndings::test_CRLF_formatted_request PASSED tests/test_redirects.py::test_follow_all_redirects_shown PASSED tests/test_redirects.py::test_follow_without_all_redirects_hidden[--follow] PASSED tests/test_redirects.py::test_follow_without_all_redirects_hidden[-F] PASSED tests/test_redirects.py::test_follow_all_output_options_used_for_redirects PASSED tests/test_redirects.py::test_follow_redirect_output_options PASSED tests/test_redirects.py::test_max_redirects PASSED tests/test_regressions.py::test_Host_header_overwrite PASSED tests/test_regressions.py::test_output_devnull PASSED tests/test_sessions.py::TestSessionFlow::test_session_created_and_reused PASSED tests/test_sessions.py::TestSessionFlow::test_session_update PASSED tests/test_sessions.py::TestSessionFlow::test_session_read_only PASSED tests/test_sessions.py::TestSession::test_session_ignored_header_prefixes PASSED tests/test_sessions.py::TestSession::test_session_by_path PASSED tests/test_sessions.py::TestSession::test_session_unicode PASSED tests/test_sessions.py::TestSession::test_session_default_header_value_overwritten PASSED tests/test_sessions.py::TestSession::test_download_in_session PASSED tests/test_ssl.py::test_ssl_version[ssl2.3] PASSED tests/test_ssl.py::test_ssl_version[tls1] PASSED tests/test_ssl.py::test_ssl_version[tls1.1] PASSED tests/test_ssl.py::test_ssl_version[tls1.2] PASSED tests/test_ssl.py::TestClientCert::test_cert_and_key PASSED tests/test_ssl.py::TestClientCert::test_cert_pem PASSED tests/test_ssl.py::TestClientCert::test_cert_file_not_found PASSED tests/test_ssl.py::TestClientCert::test_cert_file_invalid FAILED tests/test_ssl.py::TestClientCert::test_cert_ok_but_missing_key FAILED tests/test_ssl.py::TestServerCert::test_verify_no_OK PASSED tests/test_ssl.py::TestServerCert::test_verify_custom_ca_bundle_path PASSED tests/test_ssl.py::TestServerCert::test_self_signed_server_cert_by_default_raises_ssl_error PASSED tests/test_ssl.py::TestServerCert::test_verify_custom_ca_bundle_invalid_path FAILED tests/test_ssl.py::TestServerCert::test_verify_custom_ca_bundle_invalid_bundle pytest-httpbin server hit an exception serving request: EOF occurred in violation of protocol (_ssl.c:590) attempting to ignore so the rest of the tests can run FAILED tests/test_stream.py::test_pretty_redirected_stream PASSED tests/test_stream.py::test_encoded_stream PASSED tests/test_stream.py::test_redirected_stream PASSED tests/test_unicode.py::test_unicode_headers PASSED tests/test_unicode.py::test_unicode_headers_verbose PASSED tests/test_unicode.py::test_unicode_form_item PASSED tests/test_unicode.py::test_unicode_form_item_verbose PASSED tests/test_unicode.py::test_unicode_json_item PASSED tests/test_unicode.py::test_unicode_json_item_verbose PASSED tests/test_unicode.py::test_unicode_raw_json_item PASSED tests/test_unicode.py::test_unicode_raw_json_item_verbose PASSED tests/test_unicode.py::test_unicode_url_query_arg_item PASSED tests/test_unicode.py::test_unicode_url_query_arg_item_verbose PASSED tests/test_unicode.py::test_unicode_url PASSED tests/test_unicode.py::test_unicode_basic_auth PASSED tests/test_unicode.py::test_unicode_digest_auth PASSED tests/test_uploads.py::TestMultipartFormDataFileUpload::test_non_existent_file_raises_parse_error PASSED tests/test_uploads.py::TestMultipartFormDataFileUpload::test_upload_ok PASSED tests/test_uploads.py::TestMultipartFormDataFileUpload::test_upload_multiple_fields_with_the_same_name PASSED tests/test_uploads.py::TestRequestBodyFromFilePath::test_request_body_from_file_by_path PASSED tests/test_uploads.py::TestRequestBodyFromFilePath::test_request_body_from_file_by_path_with_explicit_content_type PASSED tests/test_uploads.py::TestRequestBodyFromFilePath::test_request_body_from_file_by_path_no_field_name_allowed PASSED tests/test_uploads.py::TestRequestBodyFromFilePath::test_request_body_from_file_by_path_no_data_items_allowed PASSED tests/test_windows.py::TestWindowsOnly::test_windows_colorized_output SKIPPED tests/test_windows.py::TestFakeWindows::test_output_file_pretty_not_allowed_on_windows PASSED tests/utils.py::utils.http PASSED ================================================================================= FAILURES ================================================================================== _______________________________________________ test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/AUTHORS.rst] ________________________________________________ filename = '/home/actionmystique/src/HTTPie/git-httpie/AUTHORS.rst' @pytest.mark.skipif(not has_docutils(), reason='docutils not installed') @pytest.mark.parametrize('filename', filenames) def test_rst_file_syntax(filename): p = subprocess.Popen( ['rst2pseudoxml.py', '--report=1', '--exit-status=1', filename], stderr=subprocess.PIPE, stdout=subprocess.PIPE ) err = p.communicate()[1] > assert p.returncode == 0, err.decode('utf8') E AssertionError: Traceback (most recent call last): E File "/usr/local/bin/rst2pseudoxml.py", line 17, in <module> E from docutils.core import publish_cmdline, default_description E File "/usr/local/lib/python2.7/dist-packages/docutils/__init__.py", line 68, in <module> E class ApplicationError(StandardError): E NameError: name 'StandardError' is not defined E E assert 1 == 0 E + where 1 = <subprocess.Popen object at 0x7f6c45daf8d0>.returncode tests/test_docs.py:39: AssertionError _____________________________________________ test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/CONTRIBUTING.rst] _____________________________________________ filename = '/home/actionmystique/src/HTTPie/git-httpie/CONTRIBUTING.rst' @pytest.mark.skipif(not has_docutils(), reason='docutils not installed') @pytest.mark.parametrize('filename', filenames) def test_rst_file_syntax(filename): p = subprocess.Popen( ['rst2pseudoxml.py', '--report=1', '--exit-status=1', filename], stderr=subprocess.PIPE, stdout=subprocess.PIPE ) err = p.communicate()[1] > assert p.returncode == 0, err.decode('utf8') E AssertionError: Traceback (most recent call last): E File "/usr/local/bin/rst2pseudoxml.py", line 17, in <module> E from docutils.core import publish_cmdline, default_description E File "/usr/local/lib/python2.7/dist-packages/docutils/__init__.py", line 68, in <module> E class ApplicationError(StandardError): E NameError: name 'StandardError' is not defined E E assert 1 == 0 E + where 1 = <subprocess.Popen object at 0x7f6c44de4950>.returncode tests/test_docs.py:39: AssertionError ______________________________________________ test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/CHANGELOG.rst] _______________________________________________ filename = '/home/actionmystique/src/HTTPie/git-httpie/CHANGELOG.rst' @pytest.mark.skipif(not has_docutils(), reason='docutils not installed') @pytest.mark.parametrize('filename', filenames) def test_rst_file_syntax(filename): p = subprocess.Popen( ['rst2pseudoxml.py', '--report=1', '--exit-status=1', filename], stderr=subprocess.PIPE, stdout=subprocess.PIPE ) err = p.communicate()[1] > assert p.returncode == 0, err.decode('utf8') E AssertionError: Traceback (most recent call last): E File "/usr/local/bin/rst2pseudoxml.py", line 17, in <module> E from docutils.core import publish_cmdline, default_description E File "/usr/local/lib/python2.7/dist-packages/docutils/__init__.py", line 68, in <module> E class ApplicationError(StandardError): E NameError: name 'StandardError' is not defined E E assert 1 == 0 E + where 1 = <subprocess.Popen object at 0x7f6c44e22c90>.returncode tests/test_docs.py:39: AssertionError ________________________________________________ test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/README.rst] ________________________________________________ filename = '/home/actionmystique/src/HTTPie/git-httpie/README.rst' @pytest.mark.skipif(not has_docutils(), reason='docutils not installed') @pytest.mark.parametrize('filename', filenames) def test_rst_file_syntax(filename): p = subprocess.Popen( ['rst2pseudoxml.py', '--report=1', '--exit-status=1', filename], stderr=subprocess.PIPE, stdout=subprocess.PIPE ) err = p.communicate()[1] > assert p.returncode == 0, err.decode('utf8') E AssertionError: Traceback (most recent call last): E File "/usr/local/bin/rst2pseudoxml.py", line 17, in <module> E from docutils.core import publish_cmdline, default_description E File "/usr/local/lib/python2.7/dist-packages/docutils/__init__.py", line 68, in <module> E class ApplicationError(StandardError): E NameError: name 'StandardError' is not defined E E assert 1 == 0 E + where 1 = <subprocess.Popen object at 0x7f6c44de4e10>.returncode tests/test_docs.py:39: AssertionError _____________________________________________ test_rst_file_syntax[/home/actionmystique/src/HTTPie/git-httpie/tests/README.rst] _____________________________________________ filename = '/home/actionmystique/src/HTTPie/git-httpie/tests/README.rst' @pytest.mark.skipif(not has_docutils(), reason='docutils not installed') @pytest.mark.parametrize('filename', filenames) def test_rst_file_syntax(filename): p = subprocess.Popen( ['rst2pseudoxml.py', '--report=1', '--exit-status=1', filename], stderr=subprocess.PIPE, stdout=subprocess.PIPE ) err = p.communicate()[1] > assert p.returncode == 0, err.decode('utf8') E AssertionError: Traceback (most recent call last): E File "/usr/local/bin/rst2pseudoxml.py", line 17, in <module> E from docutils.core import publish_cmdline, default_description E File "/usr/local/lib/python2.7/dist-packages/docutils/__init__.py", line 68, in <module> E class ApplicationError(StandardError): E NameError: name 'StandardError' is not defined E E assert 1 == 0 E + where 1 = <subprocess.Popen object at 0x7f6c44e1cfd0>.returncode tests/test_docs.py:39: AssertionError ___________________________________________________________________ TestClientCert.test_cert_file_invalid ___________________________________________________________________ self = <test_ssl.TestClientCert instance at 0x7f6c3d403998>, httpbin_secure = <SecureServer(<class 'pytest_httpbin.serve.SecureServer'>, started 140102906935040)> def test_cert_file_invalid(self, httpbin_secure): with pytest.raises(SSLError): http(httpbin_secure + '/get', > '--cert', __file__) tests/test_ssl.py:62: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/utils.py:207: in http exit_status = main(args=args, **kwargs) httpie/core.py:227: in main log_error=log_error, httpie/core.py:99: in program final_response = get_response(args, config_dir=env.config.directory) httpie/client.py:70: in get_response response = requests_session.request(**kwargs) /usr/local/lib/python2.7/dist-packages/requests/sessions.py:488: in request resp = self.send(prep, **send_kwargs) /usr/local/lib/python2.7/dist-packages/requests/sessions.py:609: in send r = adapter.send(request, **kwargs) /usr/local/lib/python2.7/dist-packages/requests/adapters.py:423: in send timeout=timeout /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:600: in urlopen chunked=chunked) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:345: in _make_request self._validate_conn(conn) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:844: in _validate_conn conn.connect() /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connection.py:326: in connect ssl_context=context) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/util/ssl_.py:322: in ssl_wrap_socket context.load_cert_chain(certfile, keyfile) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/contrib/pyopenssl.py:416: in load_cert_chain self._ctx.use_certificate_file(certfile) /usr/local/lib/python2.7/dist-packages/OpenSSL/SSL.py:740: in use_certificate_file _raise_current_error() _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ exception_type = <class 'OpenSSL.SSL.Error'> def exception_from_error_queue(exception_type): """ Convert an OpenSSL library failure into a Python exception. When a call to the native OpenSSL library fails, this is usually signalled by the return value, and an error code is stored in an error queue associated with the current thread. The err library provides functions to obtain these error codes and textual error messages. """ errors = [] while True: error = lib.ERR_get_error() if error == 0: break errors.append(( text(lib.ERR_lib_error_string(error)), text(lib.ERR_func_error_string(error)), text(lib.ERR_reason_error_string(error)))) > raise exception_type(errors) E Error: [('PEM routines', 'PEM_read_bio', 'no start line'), ('SSL routines', 'SSL_CTX_use_certificate_file', 'PEM lib')] /usr/local/lib/python2.7/dist-packages/OpenSSL/_util.py:54: Error --------------------------------------------------------------------------- Captured stderr call ---------------------------------------------------------------------------- http: error: Error: [('PEM routines', 'PEM_read_bio', 'no start line'), ('SSL routines', 'SSL_CTX_use_certificate_file', 'PEM lib')] ----------------------------------------------------------------------------- Captured log call ----------------------------------------------------------------------------- connectionpool.py 818 DEBUG Starting new HTTPS connection (1): 127.0.0.1 ________________________________________________________________ TestClientCert.test_cert_ok_but_missing_key ________________________________________________________________ self = <test_ssl.TestClientCert instance at 0x7f6c3d2b9b00>, httpbin_secure = <SecureServer(<class 'pytest_httpbin.serve.SecureServer'>, started 140102906935040)> def test_cert_ok_but_missing_key(self, httpbin_secure): with pytest.raises(SSLError): http(httpbin_secure + '/get', > '--cert', CLIENT_CERT) tests/test_ssl.py:67: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/utils.py:207: in http exit_status = main(args=args, **kwargs) httpie/core.py:227: in main log_error=log_error, httpie/core.py:99: in program final_response = get_response(args, config_dir=env.config.directory) httpie/client.py:70: in get_response response = requests_session.request(**kwargs) /usr/local/lib/python2.7/dist-packages/requests/sessions.py:488: in request resp = self.send(prep, **send_kwargs) /usr/local/lib/python2.7/dist-packages/requests/sessions.py:609: in send r = adapter.send(request, **kwargs) /usr/local/lib/python2.7/dist-packages/requests/adapters.py:423: in send timeout=timeout /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:600: in urlopen chunked=chunked) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:345: in _make_request self._validate_conn(conn) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:844: in _validate_conn conn.connect() /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connection.py:326: in connect ssl_context=context) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/util/ssl_.py:322: in ssl_wrap_socket context.load_cert_chain(certfile, keyfile) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/contrib/pyopenssl.py:419: in load_cert_chain self._ctx.use_privatekey_file(keyfile or certfile) /usr/local/lib/python2.7/dist-packages/OpenSSL/SSL.py:798: in use_privatekey_file self._raise_passphrase_exception() /usr/local/lib/python2.7/dist-packages/OpenSSL/SSL.py:777: in _raise_passphrase_exception _raise_current_error() _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ exception_type = <class 'OpenSSL.SSL.Error'> def exception_from_error_queue(exception_type): """ Convert an OpenSSL library failure into a Python exception. When a call to the native OpenSSL library fails, this is usually signalled by the return value, and an error code is stored in an error queue associated with the current thread. The err library provides functions to obtain these error codes and textual error messages. """ errors = [] while True: error = lib.ERR_get_error() if error == 0: break errors.append(( text(lib.ERR_lib_error_string(error)), text(lib.ERR_func_error_string(error)), text(lib.ERR_reason_error_string(error)))) > raise exception_type(errors) E Error: [('PEM routines', 'PEM_read_bio', 'no start line'), ('SSL routines', 'SSL_CTX_use_PrivateKey_file', 'PEM lib')] /usr/local/lib/python2.7/dist-packages/OpenSSL/_util.py:54: Error --------------------------------------------------------------------------- Captured stderr call ---------------------------------------------------------------------------- http: error: Error: [('PEM routines', 'PEM_read_bio', 'no start line'), ('SSL routines', 'SSL_CTX_use_PrivateKey_file', 'PEM lib')] ----------------------------------------------------------------------------- Captured log call ----------------------------------------------------------------------------- connectionpool.py 818 DEBUG Starting new HTTPS connection (1): 127.0.0.1 _________________________________________________________ TestServerCert.test_verify_custom_ca_bundle_invalid_path __________________________________________________________ self = <test_ssl.TestServerCert instance at 0x7f6c45eab638>, httpbin_secure = <SecureServer(<class 'pytest_httpbin.serve.SecureServer'>, started 140102906935040)> def test_verify_custom_ca_bundle_invalid_path(self, httpbin_secure): with pytest.raises(SSLError): > http(httpbin_secure.url + '/get', '--verify', '/__not_found__') tests/test_ssl.py:89: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/utils.py:207: in http exit_status = main(args=args, **kwargs) httpie/core.py:227: in main log_error=log_error, httpie/core.py:99: in program final_response = get_response(args, config_dir=env.config.directory) httpie/client.py:70: in get_response response = requests_session.request(**kwargs) /usr/local/lib/python2.7/dist-packages/requests/sessions.py:488: in request resp = self.send(prep, **send_kwargs) /usr/local/lib/python2.7/dist-packages/requests/sessions.py:609: in send r = adapter.send(request, **kwargs) /usr/local/lib/python2.7/dist-packages/requests/adapters.py:423: in send timeout=timeout /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:600: in urlopen chunked=chunked) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:345: in _make_request self._validate_conn(conn) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:844: in _validate_conn conn.connect() /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connection.py:326: in connect ssl_context=context) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/util/ssl_.py:308: in ssl_wrap_socket context.load_verify_locations(ca_certs, ca_cert_dir) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/contrib/pyopenssl.py:411: in load_verify_locations self._ctx.load_verify_locations(cafile, capath) /usr/local/lib/python2.7/dist-packages/OpenSSL/SSL.py:669: in load_verify_locations _raise_current_error() _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ exception_type = <class 'OpenSSL.SSL.Error'> def exception_from_error_queue(exception_type): """ Convert an OpenSSL library failure into a Python exception. When a call to the native OpenSSL library fails, this is usually signalled by the return value, and an error code is stored in an error queue associated with the current thread. The err library provides functions to obtain these error codes and textual error messages. """ errors = [] while True: error = lib.ERR_get_error() if error == 0: break errors.append(( text(lib.ERR_lib_error_string(error)), text(lib.ERR_func_error_string(error)), text(lib.ERR_reason_error_string(error)))) > raise exception_type(errors) E Error: [('system library', 'fopen', 'No such file or directory'), ('BIO routines', 'BIO_new_file', 'no such file'), ('x509 certificate routines', 'X509_load_cert_crl_file', 'system lib')] /usr/local/lib/python2.7/dist-packages/OpenSSL/_util.py:54: Error --------------------------------------------------------------------------- Captured stderr call ---------------------------------------------------------------------------- http: error: Error: [('system library', 'fopen', 'No such file or directory'), ('BIO routines', 'BIO_new_file', 'no such file'), ('x509 certificate routines', 'X509_load_cert_crl_file', 'system lib')] ----------------------------------------------------------------------------- Captured log call ----------------------------------------------------------------------------- connectionpool.py 818 DEBUG Starting new HTTPS connection (1): 127.0.0.1 ________________________________________________________ TestServerCert.test_verify_custom_ca_bundle_invalid_bundle _________________________________________________________ self = <test_ssl.TestServerCert instance at 0x7f6c3d2e27e8>, httpbin_secure = <SecureServer(<class 'pytest_httpbin.serve.SecureServer'>, started 140102906935040)> def test_verify_custom_ca_bundle_invalid_bundle(self, httpbin_secure): with pytest.raises(SSLError): > http(httpbin_secure.url + '/get', '--verify', __file__) tests/test_ssl.py:93: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ tests/utils.py:207: in http exit_status = main(args=args, **kwargs) httpie/core.py:227: in main log_error=log_error, httpie/core.py:99: in program final_response = get_response(args, config_dir=env.config.directory) httpie/client.py:70: in get_response response = requests_session.request(**kwargs) /usr/local/lib/python2.7/dist-packages/requests/sessions.py:488: in request resp = self.send(prep, **send_kwargs) /usr/local/lib/python2.7/dist-packages/requests/sessions.py:609: in send r = adapter.send(request, **kwargs) /usr/local/lib/python2.7/dist-packages/requests/adapters.py:423: in send timeout=timeout /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:600: in urlopen chunked=chunked) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:345: in _make_request self._validate_conn(conn) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connectionpool.py:844: in _validate_conn conn.connect() /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/connection.py:326: in connect ssl_context=context) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/util/ssl_.py:308: in ssl_wrap_socket context.load_verify_locations(ca_certs, ca_cert_dir) /usr/local/lib/python2.7/dist-packages/requests/packages/urllib3/contrib/pyopenssl.py:411: in load_verify_locations self._ctx.load_verify_locations(cafile, capath) /usr/local/lib/python2.7/dist-packages/OpenSSL/SSL.py:669: in load_verify_locations _raise_current_error() _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ exception_type = <class 'OpenSSL.SSL.Error'> def exception_from_error_queue(exception_type): """ Convert an OpenSSL library failure into a Python exception. When a call to the native OpenSSL library fails, this is usually signalled by the return value, and an error code is stored in an error queue associated with the current thread. The err library provides functions to obtain these error codes and textual error messages. """ errors = [] while True: error = lib.ERR_get_error() if error == 0: break errors.append(( text(lib.ERR_lib_error_string(error)), text(lib.ERR_func_error_string(error)), text(lib.ERR_reason_error_string(error)))) > raise exception_type(errors) E Error: [] /usr/local/lib/python2.7/dist-packages/OpenSSL/_util.py:54: Error --------------------------------------------------------------------------- Captured stderr call ---------------------------------------------------------------------------- http: error: Error: [] ----------------------------------------------------------------------------- Captured log call ----------------------------------------------------------------------------- connectionpool.py 818 DEBUG Starting new HTTPS connection (1): 127.0.0.1 ========================================================================== pytest-warning summary =========================================================================== WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_auth.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_binary.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_cli.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_config.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_defaults.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_downloads.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_exit_status.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_httpie.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_output.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_sessions.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_stream.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_uploads.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor WC1 /home/actionmystique/src/HTTPie/git-httpie/tests/test_windows.py cannot collect test class 'TestEnvironment' because it has a __init__ constructor =================================================== 9 failed, 224 passed, 3 skipped, 13 pytest-warnings in 14.51 seconds ==================================================== ```
2hard
Title: Cannot append elements to shell array while using tqdm Body: - [ ] I have marked all applicable categories: + [ ] exception-raising bug + [ ] visual output bug + [x] Command-line unintentional behaviour - [x] I have visited the [source website], and in particular read the [known issues] - [x] I have searched through the [issue tracker] for duplicates - [x] I have mentioned version numbers, operating system and environment, where applicable: ```bash python -c "import tqdm, sys; print(tqdm.__version__, sys.version, sys.platform)" 4.60.0 3.8.0 (default, Oct 6 2020, 11:07:52) [GCC 10.2.0] linux ``` [source website]: https://github.com/tqdm/tqdm/ [known issues]: https://github.com/tqdm/tqdm/#faq-and-known-issues [issue tracker]: https://github.com/tqdm/tqdm/issues?q= I have encountered an issue where elements are not appended to shell arrays when using the tqdm bar from the terminal. The following example produces an empty array ``` $ test_arr=() total=10 for i in $(seq $total) do echo "$i" test_arr+=("$i") done | tqdm --total $total --null echo "Size of array: ${#test_arr[@]}" echo "with elements: ${test_arr[@]}" 100%|████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 242445.32it/s] Size of array: 0 with elements: ``` Whereas the elements are properly added if you remove the bar ``` $ test_arr=() total=10 for i in $(seq $total) do echo "$i" test_arr+=("$i") done echo "Size of array: ${#test_arr[@]}" echo "with elements: ${test_arr[@]}" 1 2 3 4 5 6 7 8 9 10 Size of array: 10 with elements: 1 2 3 4 5 6 7 8 9 10 ```
1medium
Title: RuntimeError: dictionary changed size during iteration Body: While using below function for multiple stocks (ticks) in below i am getting this error. Please suggest resolution yf.download(ticks, period="1d", interval="1m", rounding=False, prepost=True, ignore_tz=False, progress=False) File "/home/user/doc/lib/python3.11/site-packages/yfinance/utils.py", line 105, in wrapper result = func(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "/home/user/doc/lib/python3.11/site-packages/yfinance/multi.py", line 193, in download for ticker in shared._TRACEBACKS: RuntimeError: dictionary changed size during iteration
1medium
Title: Add repeat() for iterable datasets Body: ### Feature request It would be useful to be able to straightforwardly repeat iterable datasets indefinitely, to provide complete control over starting and ending of iteration to the user. An IterableDataset.repeat(n) function could do this automatically ### Motivation This feature was discussed in this issue https://github.com/huggingface/datasets/issues/7147, and would resolve the need to use the hack of interleave datasets with probability 0 as a simple way to achieve this functionality. An additional benefit might be the simplification of the use of iterable datasets in a distributed setting: If the user can assume that datasets will repeat indefinitely, then issues around different numbers of samples appearing on different devices (e.g. https://github.com/huggingface/datasets/issues/6437, https://github.com/huggingface/datasets/issues/6594, https://github.com/huggingface/datasets/issues/6623, https://github.com/huggingface/datasets/issues/6719) can potentially be straightforwardly resolved by simply doing: ids.repeat(None).take(n_samples_per_epoch) ### Your contribution I'm not familiar enough with the codebase to assess how straightforward this would be to implement. If it might be very straightforward, I could possibly have a go.
1medium
Title: Splitting up API library into multiple files Body: I've tried several different ways to split up the API files into separate python source but have come up empty. I love the additions to flask-restplus but it appears that only the classes within the main python file are seen. Is there a good example of how to do this? In Flask-Restful it was a bit simpler as you could just add the resource and point to a different python file that got imported.
1medium
Title: Reloadium debugger shows filtered log messages in django Body: ## Describe the bug* Django app running in Pycharm 2023.2, Windows 11 If debugging with native debugger, log messages that are filtered do not appear in the console. If debugging with reloadium, they do appear and clutter the console. Also, normal messages are duplicated in a different format. ## To Reproduce Steps to reproduce the behavior: In settings.py, create a LOGGING = entry Example: ``` LOGGING = { 'version': 1, 'disable_existing_loggers': False, 'filters': { 'skip_static_requests': { '()': 'django.utils.log.CallbackFilter', 'callback': skip_static_requests }, }, 'handlers': { 'console': { 'level': 'INFO', 'filters': ['skip_static_requests'], 'class': 'logging.StreamHandler', 'stream': sys.stdout, 'formatter': 'verbose', }, ... ``` ## Expected behavior Filtered messages should not display in console. Also, messages should not duplicate if they are not filtered. ## Screenshots ![image](https://github.com/reloadware/reloadium/assets/14006401/b53a2e8f-18de-4f49-bf4a-888241ec655b) The Red messages should not appear and do not when using native debugger. Additionally, they are not formatted according to the settings. The messages in Green are normal and formatted as per the settings LOGGING entry.
1medium
Title: [numba.cuda] StructModel + FP16 fails with CUDA because make_attribute_wrapper assumes default_manager Body: This ```python from numba import cuda from numba import types from numba.extending import models, make_attribute_wrapper, lower_builtin, as_numba_type, type_callable from numba.cuda.models import register_model from numba.core import cgutils import numba.cuda.cudaimpl class float16x2(object): pass class float16x2Type(types.Type): def __init__(self): super(float16x2Type, self).__init__(name='float16x2') float16x2_type = float16x2Type() ## Type inference (Python --> FE type) as_numba_type.register(float16x2, float16x2_type) @type_callable(float16x2) def type_float16x2(context): def typer(x, y): if all(isinstance(v, types.Float) for v in [x, y]): return float16x2_type return typer ### Lowering (FE types --> LLVM) # Data model @register_model(float16x2Type) class float16x2TypeModel(models.StructModel): def __init__(self, dmm, fe_type): members = [(f, types.float16) for f in ['x', 'y']] models.StructModel.__init__(self, dmm, fe_type, members) for field in ['x', 'y']: make_attribute_wrapper(float16x2Type, field, field) # Constructors @lower_builtin(float16x2, types.Float, types.Float) def impl(context, builder, sig, args): typ = sig.return_type obj = cgutils.create_struct_proxy(typ)(context, builder) x, y = args x = numba.cuda.cudaimpl.float_to_float16_cast(context, builder, sig.args[0], types.float16, x) y = numba.cuda.cudaimpl.float_to_float16_cast(context, builder, sig.args[1], types.float16, y) obj.x, obj.y = x, y return obj._getvalue() @cuda.jit def f(): a = float16x2(1.0, 2.0) print(a.y) f[1, 1, 0, 0]() cuda.synchronize() ``` fails with ``` numba.core.errors.TypingError: Failed in cuda mode pipeline (step: nopython frontend) Internal error at resolving type of attribute "y" of "a". <class '__main__.float16x2Type'> During: typing of get attribute at [redacted] (54) Enable logging at debug level for details. File "[redacted]", line 54: def f(): <source elided> a = float16x2(1.0, 2.0) print(a.y) ^ ``` The reason seems to be that `make_attribute_wrapper` [here](https://github.com/numba/numba/blob/main/numba/core/extending.py#L279C38-L279C53) uses ``` from numba.core.datamodel import default_manager ``` and, as such, assumes the default data model. This means for FP16 it will uses this generic data model [here](https://github.com/numba/numba/blob/7b7137a1f2bf003e8aa42255f571d0947654e7ce/numba/core/datamodel/models.py#L363) instead of the CUDA specific one from [here](https://github.com/numba/numba/blob/7b7137a1f2bf003e8aa42255f571d0947654e7ce/numba/cuda/models.py#L35) cc @gmarkall
2hard
Title: Inconsistent behavior with dcc.Store initial values and prevent_initial_call Body: ``` dash 2.16.1 dash-bootstrap-components 1.6.0 dash-core-components 2.0.0 dash-html-components 2.0.0 dash-iconify 0.1.2 dash-mantine-components 0.12.1 dash-table 5.0.0 ``` **description** There appears to be an inconsistency in how dcc.Store components behave with different initial values when using prevent_initial_call=True. **Expected behavior** When using `prevent_initial_call=True`, callbacks should not be triggered on initial load for any dcc.Store, regardless of initial value. **Actual behavior** A callback with `prevent_initial_call=True` is triggered for a dcc.Store initialized with None, but not for one initialized with an empty dictionary {}. Minimal reproducible example: ``` import dash from dash import dcc, html, Input, Output, State app = dash.Dash(__name__) app.layout = html.Div([ dcc.Store(id='store_none', data=None), dcc.Store(id='store', data={}), html.H3("none store"), html.Div(id='output none store', children="Not called yet"), html.H3("store"), html.Div(id='output store', children="Not called yet"), ]) @app.callback( Output('output none store', 'children'), Input('store_none', 'data'), prevent_initial_call=True ) def on_store_none(store_none): return "called" @app.callback( Output('output store', 'children'), Input("store", "data"), prevent_initial_call=True ) def on_store(store): return "called" if __name__ == '__main__': app.run_server(debug=True) ``` **Screenshots** ![image](https://github.com/plotly/dash/assets/119524982/54275299-006c-473d-a42e-f853b3a3b54e)
1medium
Title: The web version is not working Body: ![Image](https://github.com/user-attachments/assets/e7034e86-03b7-438a-b345-30b7f0804c95) Trying to search and it loads forever.
1medium
Title: Interactive plots with Plotly: Link broken 404 error! Body: ## Tried to see the nbviewer: Interactive plots with Plotly clicking in the link you offer ## https://nbviewer.jupyter.org/github/plotly/python-user-guide/blob/master/Index.ipynb # got: 404 : Not Found You are requesting a page that does not exist! The remote resource was not found.
1medium
Title: tensorflow.python.framework.errors_impl.FailedPreconditionError: Error while reading resource variable localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/F_2_2/kernel) Body: ``` from PIL import Image import numpy as np import tensorflow as tf from .models import RDN from .models import RRDN global gra global rrdn global rdn # gra = tf.Graph() rrdn = RRDN(weights='gans') rdn = RDN(weights='psnr-large') gra = tf.get_default_graph() # g = tf.Session(graph=graph) def get_gan_output(img_path, by_patch_of_size=50): img = Image.open(img_path).convert("RGB") lr_img = np.array(img) with gra.as_default(): sr_img = rrdn.predict(lr_img, by_patch_of_size=50) return sr_img def get_2x_output(img_path, by_patch_of_size=50): img = Image.open(img_path).convert("RGB") lr_img = np.array(img) with gra.as_default(): sr_img = rdn.predict(lr_img, by_patch_of_size=50) return sr_img ``` Calling any of these function from a different .py file causes the error. File ``` "D:\data\deep_learning_projects\app\projects\main\service\superresolution\get_output.py", line 29, in get_2x_output sr_img = rdn.predict(lr_img, by_patch_of_size=50) File "D:\data\deep_learning_projects\venv\lib\site-packages\ISR\models\imagemodel.py", line 41, in predict batch = self.model.predict(patches[i: i + batch_size]) File "D:\data\deep_learning_projects\venv\lib\site-packages\tensorflow_core\python\keras\engine\training.py", line 908, in predict use_multiprocessing=use_multiprocessing) File "D:\data\deep_learning_projects\venv\lib\site-packages\tensorflow_core\python\keras\engine\training_arrays.py", line 723, in predict callbacks=callbacks) File "D:\data\deep_learning_projects\venv\lib\site-packages\tensorflow_core\python\keras\engine\training_arrays.py", line 394, in model_iteration batch_outs = f(ins_batch) File "D:\data\deep_learning_projects\venv\lib\site-packages\tensorflow_core\python\keras\backend.py", line 3476, in __call__ run_metadata=self.run_metadata) File "D:\data\deep_learning_projects\venv\lib\site-packages\tensorflow_core\python\client\session.py", line 1472, in __call__ run_metadata_ptr) tensorflow.python.framework.errors_impl.FailedPreconditionError: Error while reading resource variable F_2_2/kernel from Container: localhost. This could mean that the variable was uninitialized. Not found: Container localhost does not exist. (Could not find resource: localhost/F_2_2/kernel) [[{{node F_2_2/Conv2D/ReadVariableOp}}]] ``` I am running this in tensorflow 1.15.0. But this is running perfectly in colab even in case of 1.15.0 but not running on local system.
1medium
Title: Training crashes during pretraining Body: After extracting the version 01_04_2021, I immediately ran the pretraining with default options. I set the target iterations to 500,000. After loading and training for a while it crashes, I restarted it each time reducing batch size and it still crashes. The final output: Initializing models: 100%|#############################################| 5/5 [00:03<00:00, 1.64it/s] Loaded 15843 packed faces from D:\DeepFaceLab_NVIDIA_01_04_2021\_internal\pretrain_CelebA Sort by yaw: 100%|################################################| 128/128 [00:00<00:00, 295.61it/s] Sort by yaw: 100%|################################################| 128/128 [00:00<00:00, 289.58it/s] =============== Model Summary =============== == == == Model name: basic_SAEHD == == == == Current iteration: 91392 == == == ==------------- Model Options -------------== == == == resolution: 128 == == face_type: wf == == models_opt_on_gpu: True == == archi: liae-ud == == ae_dims: 256 == == e_dims: 64 == == d_dims: 64 == == d_mask_dims: 22 == == masked_training: True == == eyes_mouth_prio: False == == uniform_yaw: True == == adabelief: True == == lr_dropout: n == == random_warp: False == == true_face_power: 0.0 == == face_style_power: 0.0 == == bg_style_power: 0.0 == == ct_mode: rct == == clipgrad: True == == pretrain: True == == autobackup_hour: 1 == == write_preview_history: False == == target_iter: 500000 == == random_flip: True == == batch_size: 4 == == gan_power: 0.0 == == gan_patch_size: 16 == == gan_dims: 16 == == == ==-------------- Running On ---------------== == == == Device index: 0 == == Name: GeForce RTX 2060 == == VRAM: 6.00GB == == == ============================================= Starting. Target iteration: 500000. Press "Enter" to stop training and save model. [18:32:21][#094491][0288ms][0.4154][0.3854] [18:47:21][#097587][0281ms][0.4149][0.3843] [19:02:21][#100685][0300ms][0.4120][0.3807] [19:17:22][#103782][0305ms][0.4106][0.3801] Error: 46][#104277][0275ms][0.4674][0.3715] Traceback (most recent call last): File "D:\DeepFaceLab_NVIDIA_01_04_2021\_internal\DeepFaceLab\mainscripts\Trainer.py", line 130, in trainerThread iter, iter_time = model.train_one_iter() File "D:\DeepFaceLab_NVIDIA_01_04_2021\_internal\DeepFaceLab\models\ModelBase.py", line 462, in train_one_iter losses = self.onTrainOneIter() File "D:\DeepFaceLab_NVIDIA_01_04_2021\_internal\DeepFaceLab\models\Model_SAEHD\Model.py", line 676, in onTrainOneIter (warped_dst, target_dst, target_dstm, target_dstm_em) ) = self.generate_next_samples() File "D:\DeepFaceLab_NVIDIA_01_04_2021\_internal\DeepFaceLab\models\ModelBase.py", line 449, in generate_next_samples sample.append ( generator.generate_next() ) File "D:\DeepFaceLab_NVIDIA_01_04_2021\_internal\DeepFaceLab\samplelib\SampleGeneratorBase.py", line 21, in generate_next self.last_generation = next(self) File "D:\DeepFaceLab_NVIDIA_01_04_2021\_internal\DeepFaceLab\samplelib\SampleGeneratorFace.py", line 112, in __next__ return next(generator) File "D:\DeepFaceLab_NVIDIA_01_04_2021\_internal\DeepFaceLab\core\joblib\SubprocessGenerator.py", line 73, in __next__ gen_data = self.cs_queue.get() File "multiprocessing\queues.py", line 94, in get File "multiprocessing\connection.py", line 216, in recv_bytes File "multiprocessing\connection.py", line 318, in _recv_bytes File "multiprocessing\connection.py", line 340, in _get_more_data MemoryError System Information: Edition Windows 10 Home Version 20H2 Installed on ‎7/‎21/‎2020 OS build 19042.746 Experience Windows Feature Experience Pack 120.2212.551.0 Processor AMD Ryzen 7 4800H with Radeon Graphics 2.90 GHz Installed RAM 16.0 GB (15.4 GB usable) nvcc output: nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2020 NVIDIA Corporation Built on Mon_Oct_12_20:54:10_Pacific_Daylight_Time_2020 Cuda compilation tools, release 11.1, V11.1.105 Build cuda_11.1.relgpu_drvr455TC455_06.29190527_0 nvidia-smi output: Thu Jan 14 19:53:32 2021 +-----------------------------------------------------------------------------+ | NVIDIA-SMI 460.89 Driver Version: 460.89 CUDA Version: 11.2 | |-------------------------------+----------------------+----------------------+ | GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC | | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | | | | MIG M. | |===============================+======================+======================| | 0 GeForce RTX 2060 WDDM | 00000000:01:00.0 Off | N/A | | N/A 44C P8 9W / N/A | 164MiB / 6144MiB | 0% Default | | | | N/A | +-------------------------------+----------------------+----------------------+ +-----------------------------------------------------------------------------+ | Processes: | | GPU GI CI PID Type Process name GPU Memory | | ID ID Usage | |=============================================================================| | No running processes found | +-----------------------------------------------------------------------------+
2hard
Title: DeepSpeed inference load the whole model to cpu numerous times Body: Hi when I use DeepSpeed to inference ,when running GPU = 4,model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16) will be loaded four times. This takes up a lot of CPU memory.Is there a way to load the model only once?
1medium
Title: Opencv channel swap in ImageSinks Body: ### Search before asking - [X] I have searched the Supervision [issues](https://github.com/roboflow/supervision/issues) and found no similar feature requests. ### Description Hello I realize opencv used BGR instead of RGB, and therefore, the following code will cause channel swap: ```python with sv.ImageSink(target_dir_path=output_dir, overwrite=True) as sink: annotated_img = box_annotator.annotate( scene=np.array(Image.open(img_dir).convert("RGB")), detections=results, labels=labels, ) sink.save_image( image=annotated_img, image_name="test.jpg" ) ``` Unless I use `cv2.cvtColor(annotated_img, cv2.COLOR_RGB2BGR)` . This also happens with video sinks and other places using `Opencv` for image writing. I wonder if it is possible to add this conversion by default or at least mention this in the docs? Thanks a lot! ### Use case For savings with `ImageSink()` ### Additional _No response_ ### Are you willing to submit a PR? - [X] Yes I'd like to help by submitting a PR!
1medium
Title: Please delete this issue Body: -snip-
3misc
Title: Create a better Example notebook Body: Currently the example notebook is more geared towards understanding the implementaiton details, than how to use ipytest effectively.
1medium
Title: [PR] Fix Windows Compatibility Body: > <a href="https://github.com/damc-dev"><img align="left" height="50" src="https://avatars0.githubusercontent.com/u/3859789?v=4"></a> A pull request by [damc-dev](https://github.com/damc-dev) at _2019-11-06 01:44:29+00:00_ > Original URL: https://github.com/zalando-incubator/kopf/pull/220 > Merged by [nolar](https://github.com/nolar) at _2019-11-12 10:30:08+00:00_ When running kopf on Windows it fails due to NotImplementedError thrown by add_signal_handler method in asyncio > Issue : #219 # Description In the asyncio docs it appears that the [add_signal_handler](https://docs.python.org/3/library/asyncio-eventloop.html#asyncio.loop.add_signal_handler) method is only available in Unix which is why it throws a NotImplementedError when kopf is run on Windows. This PR should fix Windows compatibility by catching NotImplementedError thrown by asyncio and continuing. # Types of Changes * Bug fix (non-breaking change which fixes an issue) --- > <a href="https://github.com/nolar"><img align="left" height="30" src="https://avatars0.githubusercontent.com/u/544296?v=4"></a> Commented by [nolar](https://github.com/nolar) at _2019-11-13 18:25:01+00:00_ > &nbsp; Released as [`kopf==0.23rc1`](https://github.com/nolar/kopf/releases/tag/0.23rc1). [damc-dev](https://github.com/damc-dev) Thank you for you contribution! 😉
1medium
Title: [serve] proxy memory leak Body: ### What happened + What you expected to happen Seeing memory growth in the proxy actor over time indicating a memory leak: <img width="1357" alt="Image" src="https://github.com/user-attachments/assets/e0fd6e84-6e92-4e7c-91e2-4169ffc0bee2" /> ### Versions / Dependencies Ray 2.41 ### Reproduction script n/a ### Issue Severity None
2hard
Title: Fix french translation Body: French translation which seems ta have been automaticaly generated contains mistakes. I propose to fix some of them ### Environment Flask-Appbuilder version: 3.4.3
1medium
Title: Markercluster, disable cluster at zoomlevel Body: This issue was rasied by another person last year. But it seems to be no answer. I come aross the same issue and wonder if this can be done Markercluster or folium [https://github.com/python-visualization/folium/issues/1485]
1medium
Title: Renderer should be configurable on a per-router or per-endpoint basis Body: **Is your feature request related to a problem? Please describe.** I am trying to export metrics of my application via `prometheus_client`. Prometheus will consume plain-text data from any HTTP endpoint and parse it. All my endpoints are JSON, except the metrics endpoint, which should be plaintext. **Describe the solution you'd like** I'd like to be able to, ideally, set my renderer on a per-endpoint basis: ```python @router.get("/", renderer=MyRenderer) def endpoint(request): ... ``` Alternatively, I would be OK with having the router itself take a renderer: ```python router = Router(renderer=MyRenderer) ``` What I have done now works, but seems like a hack, I bypass the renderer selection when bypassing `create_response` by returning an `HttpResponse` ```python @router.get("/", response=str) def endpoint(request): return HttpResponse("some plain text", status=200, content_type="text/plain") ```
1medium
Title: Incorrect version requirement in 0.27.0 for asyncpg Body: New 0.27.0 version [passes record_class](https://github.com/CanopyTax/asyncpgsa/blob/b9e928ce4a27a2c3964c69cfe5a3189290f1fdaa/asyncpgsa/connection.py#L96) thus being incompatible with asyncpg<0.22.0, but declaration in setup.py [states the opposite](https://github.com/CanopyTax/asyncpgsa/blob/master/setup.py#L13). Probably mistyped `<=` instead of `>=`?
1medium
Title: Change Config and UserConfig to allow recursive nesting of dictionaries Body: ### Describe the type of feature and its functionality. Currently both Config and User config are defined as arbitrary dictionaries with string keys and Scalar values. This requires the user to have knowledge of what the string keys are in order to access the values they packed into the config. Why not allow the values to also include dictionaries so long as the end values are always Scalars. This can be done with a recursive typing definition. It would allow more organized config and userconfig dictionaries. Furthermore we have a specific use case where we need to pass a highly nested dictionary loaded from a json file from the server to the client. There are too many key-value pairs to make it worth it to unnest the whole thing. Right now we are getting around it by serializing the dictionary so that it can be passed as a scalar Bytes value and then unserializing it on the client. Ideally we could skip the serialization step. However, the UserConfig type used in the Context class does not allow bytes values. We are not making use of the Context objects yet, but are considering it as a good way to store state information. Although one of the state objects is another nested dictionary. I think this is a good change so long as it does not significantly interfere with other parts of the library. There might even be some other dictionary types in flwr.common.typing that could benefit from a recursive definition. Namely the Properties type and perhaps even the Metrics type. Although you might need to modify the aggregation function to recursively search the dictionary until it finds a scalar value to aggregate, but that would be worth the hassle in my opinion to allow more organized dictionary types ### Describe step by step what files and adjustments are you planning to include. For python, I believe the change is simple. Not sure if there would be any downstream effects. Here is an example of some changes to flwr.common.typing ```python Metrics = dict[str, Union[Scalar, 'Metrics']] Config = dict[str, Union[Scalar, 'Config']] Properties = dict[str, Union[Scalar, 'Properties']] UserConfig = dict[str, Union[UserConfigValue, 'UserConfig']] ``` ### Is there something else you want to add? _No response_
1medium
Title: [BUG] dcc.Dropdown use outdated styles for react-virtualized-select (cursor should be pointer) Body: ![image](https://user-images.githubusercontent.com/72201/196037000-51156c03-c2bd-4601-8796-3f56186fcc6b.png) Cursor should be "pointer". The underlying library [has fixed this](https://github.com/bvaughn/react-virtualized-select/commit/b2c5fe394ec3145319bde37158d05b3508fbf84a) and dash use a version which includes the fix (3.1.3), but the stylesheet is ["hardcoded"](https://github.com/plotly/dash/blob/dev/components/dash-core-components/src/components/css/react-virtualized-select%403.1.0.css) to 3.1.0 ``` > conda list | grep dash dash 2.6.1 pyhd8ed1ab_0 conda-forge dash-bootstrap-components 1.2.1 pyhd8ed1ab_0 conda-forge dash-core-components 2.0.0 pypi_0 pypi dash-daq 0.5.0 pypi_0 pypi dash-html-components 2.0.0 pypi_0 pypi dash-table 5.0.0 pypi_0 pypi ```
1medium
Title: 原来你们都在这里,哈哈㊙️㊙️㊙️ Body: 全网黑科技收藏了:[https://wxbug.cn/](https://wxbug.cn/)
3misc
Title: Dependencies issues with Allure Body: Hi, While trying to install pytest-allure plugin I caught the following issues : Could not find a version that matches allure-pytest Tried: 2.0.0b1, 2.0.0b1, 2.0.0b2, 2.0.0b2, 2.1.0b1, 2.1.0b1, 2.1.1b1, 2.1.1b1, 2.2.1b1, 2.2.1b1, 2.2.2b2, 2.2.2b2, 2.2.3b1, 2.2.3b1, 2.2.4b1, 2.2.4b1, 2.3.1b1, 2.3.1b1, 2.3.2b1, 2.3.2b1 There are incompatible versions in the resolved dependencies. Need your help :(
1medium
Title: Data Generation Overlap for Multiple DataFrames Body: #### Concurrent Data Generation Strategies for Multiple DataFrames I realize this may be a difficult functionality to implement, but at a high level I am thinking about the best way to use pandera data generation in unit tests for testing functions that involve some merging across multiple datasets. In one of my use cases I have a function that merges two dataframes on their shared timestamp column. I have pandera schemas defined for both of these dataframes, the timestamp data should be at an hourly frequency. So I am wondering if you have any thoughts about how I could ensure that when data is generated, they have the same date range so that the function which contains a merge operation can be effectively tested. I guess one workaround would be to define a function that generates a date range with length equal to the length of the dataframe, and then overwrite the timestamp column in both dataframes. But maybe you all have some different ideas or I'm missing how to do this already? Thanks! I can add the enhancement label if it's appropriate.
2hard
Title: [Bug] when i run print(TTS().list_models()) I get <TTS.utils.manage.ModelManager object at 0x7fa9d4c5a7a0> Body: ### Describe the bug was found in coqui tts V0.22.0 not sure why its happening the but when i run print(TTS().list_models()) i get <TTS.utils.manage.ModelManager object at 0x7fa9d4c5a7a0> ### To Reproduce When i run print(TTS().list_models()) I get <TTS.utils.manage.ModelManager object at 0x7fa9d4c5a7a0> ### Expected behavior It should be giving me a list of all of the models but it doesn't ### Logs _No response_ ### Environment ```shell Seems to occur in what I,ve tested being python 3.11 and 3.10 ``` ### Additional context I found a fix tho
0easy
Title: error: Unexpected keyword argument "astext_type" for "JSONB" Body: I'm getting `error: Unexpected keyword argument "astext_type" for "JSONB"` in my alembic migrations on lines like: `sa.Column("data", postgresql.JSONB(astext_type=sa.Text()), nullable=True),` Looking at the [__init__](https://github.com/sqlalchemy/sqlalchemy/blob/rel_1_4_0b1/lib/sqlalchemy/dialects/postgresql/json.py#L183) function of the JSON class that JSONB inherits it has a keyword argument astext_type. Can't find the __init__ function for JSON/JSONB in this repo. So, am I doing something wrong or is there something not implemented or whatnot? Thanks!
1medium
Title: Auto Restart when chips show as dashes `-` Body: i hope it will be auto restart function on this software, once the page is refresh and if any running chip XXXXX it will be auto restart for them.
1medium
Title: Issue using branca colormap with folium.raster_layers.ImageOverlay Body: **Describe the bug** Exhausted my troubleshooting - I believe this is in fact a bug, hopefully I'm not wrong! I think there is a bug attempting to use a branca colormap (of type branca.colormap.LinearColormap) with an ImageOverlay raster layer. Here is the error I receive when running the code below: ``` --------------------------------------------------------------------------- IndexError Traceback (most recent call last) ~\AppData\Local\Temp/ipykernel_26316/1517857374.py in <module> 13 14 # Add the raster overlay to the map ---> 15 image = folium.raster_layers.ImageOverlay( 16 name="Random Image", 17 image = rand_img, c:\users\ianmp\git_repos\ce-api-endpoint-tests\venv\lib\site-packages\folium\raster_layers.py in __init__(self, image, bounds, origin, colormap, mercator_project, pixelated, name, overlay, control, show, **kwargs) 258 ) 259 --> 260 self.url = image_to_url(image, origin=origin, colormap=colormap) 261 262 def render(self, **kwargs): c:\users\ianmp\git_repos\ce-api-endpoint-tests\venv\lib\site-packages\folium\utilities.py in image_to_url(image, colormap, origin) 137 url = 'data:image/{};base64,{}'.format(fileformat, b64encoded) 138 elif 'ndarray' in image.__class__.__name__: --> 139 img = write_png(image, origin=origin, colormap=colormap) 140 b64encoded = base64.b64encode(img).decode('utf-8') 141 url = 'data:image/png;base64,{}'.format(b64encoded) c:\users\ianmp\git_repos\ce-api-endpoint-tests\venv\lib\site-packages\folium\utilities.py in write_png(data, origin, colormap) 200 if nblayers == 1: 201 arr = np.array(list(map(colormap, arr.ravel()))) --> 202 nblayers = arr.shape[1] 203 if nblayers not in [3, 4]: 204 raise ValueError('colormap must provide colors of r' IndexError: tuple index out of range ``` **To Reproduce** Below is a self-contained code snippet which reproduces the issue. I have substituted in a random numpy array (of a particular size) to replace a raster image I was using so that you can easily reproduce this. The error is the same using either the raster or the random array. ``` import branca import branca.colormap as cm import folium from folium import plugins import numpy as np # Create an array of random values to simulate a raster image array rand_img = np.random.rand(333, 443) # Set the image bounds (WGS84 lon/lats) bbox = [-128.5831, 31.3986, -112.7140, 43.0319] # Create a folium map object m = folium.Map(location=[39.3, -118.4], zoom_start=5, height=500) # Define a Branca colormap for the colorbar vmin = 0.2 vmax = 0.8 palette = ['red', 'orange', 'yellow', 'cyan', 'blue', 'darkblue'][::-1] cmap = cm.LinearColormap(colors=palette, vmin=vmin, vmax=vmax, caption='Image Colormap') # Add the raster overlay to the map image = folium.raster_layers.ImageOverlay( name="Random Image", image = rand_img, bounds=[[bbox[1], bbox[0]], [bbox[3], bbox[2]]], interactive=True, colormap=cmap, overlay=True) image.add_to(m) # Add a layer control panel to the map m.add_child(folium.LayerControl()) m.add_child(cmap) # Add fullscreen button plugins.Fullscreen().add_to(m) # Display the map display(m) ``` **Expected behavior** I expected the image to appear on the folium map, with a color palette as specified (dark blue values for 0.2 and below, red values for 0.8 and above, and other values linearly spaced in between). **Environment (please complete the following information):** - Jupyter Notebook - Python version 3.9.5 - folium version 0.12.1.post1 (also experienced on 0.12.1) - branca version 0.4.2 **Additional context** If you remove the colormap from the `folium.raster_layers.ImageOverlay()` call, the image plots just fine on the map, and the colormap will appear as a colorbar, but the image will just be in greyscale. **Possible solutions** No solutions yet, but I think the error lies in the line identified in the stack trace ([l212 in utilities.py](https://github.com/AntonioLopardo/folium/blob/master/utilities.py#L212)). If nblayers is already known to be 1 (mono/singleband image, i.e. a NxM array), I am not sure why it grabs the array shape (which at this point is single-dimensional) and tries to reset the nblayers value.
2hard
Title: Allow column names to pass through when fitting `narwhals` dataframes Body: ### Describe the workflow you want to enable Currently when fitting with a `narwhals` DataFrame, the feature names do not pass through because it does not implement a `__dataframe__` method. Example: ```python import narwhals as nw import pandas as pd import polars as pl from sklearn.preprocessing import StandardScaler df_pd = pd.DataFrame({"a": [0, 1, 2], "b": [3, 4, 5]}) df_pl = pl.DataFrame(df_pd) df_nw = nw.from_native(df_pd) s_pd, s_pl, s_nw = StandardScaler(), StandardScaler(), StandardScaler() s_pd.fit(df_pd) s_pl.fit(df_pl) s_nw.fit(df_nw) print(s_pd.feature_names_in_) print(s_pl.feature_names_in_) print(s_nw.feature_names_in_) ``` **Expected output** ``` ['a' 'b'] ['a' 'b'] ['a' 'b'] ``` **Actual output** ``` ['a' 'b'] ['a' 'b'] AttributeError: 'StandardScaler' object has no attribute 'feature_names_in_' ``` All other attributes on `s_nw` are what I'd expect. ### Describe your proposed solution This should be easy enough to implement by adding another check within `sklearn.utils.validation._get_feature_names`: 1. Add `_is_narwhals_df` method, borrowing logic from [`_is_pandas_df`](https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/utils/validation.py#L2343) ```python def _is_narwhals_df(X): """Return True if the X is a narwhals dataframe.""" try: nw = sys.modules["narwhals"] except KeyError: return False return isinstance(X, nw.DataFrame) ``` 2. Add an additional check to [`_get_feature_names`](https://github.com/scikit-learn/scikit-learn/blob/main/sklearn/utils/validation.py#L2393-L2408): ```python elif _is_narwhals_df(X): feature_names = np.asarray(X.columns, dtype=object) ``` ### Describe alternatives you've considered, if relevant _No response_ ### Additional context https://github.com/narwhals-dev/narwhals/issues/355#issuecomment-2734066008
0easy
Title: compatible with BasicTeX? Body: Question: I was just looking at this [requirement](https://github.com/3b1b/manim/blame/master/README.md#L21) and wondering Is this compatible with [BasicTeX](https://www.tug.org/mactex/morepackages.html)?
3misc
Title: Move prompt templates to separate files Body: ### 🚀 The feature Currently we have prompt's content is stored in class body mixed with other code: [`GeneratePythonCodePrompt`](https://github.com/gventuri/pandas-ai/blob/a8a15052eff658667d4eeccbe2431bc31911919d/pandasai/prompts/generate_python_code.py#L42) [`CorrectErrorPrompt`](https://github.com/gventuri/pandas-ai/blob/a8a15052eff658667d4eeccbe2431bc31911919d/pandasai/prompts/correct_error_prompt.py#L25) My suggestion is to move those template strings to separate files stored in specific directory. We could implement one more class extending base `Prompt` containing a method that would read content from a file. Then, make `GeneratePythonCodePrompt` and `CorrectErrorPrompt` inherit the new class, and they would only contain an attribute representing a path to the template. ### Motivation, pitch This would enhance readibility of sources, segregate business logic from data. ### Alternatives _No response_ ### Additional context _No response_
1medium
Title: how to find the end token in _sample_mask? Body: https://github.com/zihangdai/xlnet/blob/5cd50bc451436e188a8e7fea15358d5a8c916b72/data_utils.py#L369 why isn't _is_start_piece(sp.IdToPiece(seg[end].item()))? Should it check the end of n-grams?
2hard
Title: Incorrectly strips tuple brackets from single entry tuple Body: <!-- Please make sure that the bug is not already fixed either in newer versions or the current development version. To confirm this, you have three options: 1. Update Black's version if a newer release exists: `pip install -U black` 2. Use the online formatter at <https://black.vercel.app/?version=main>, which will use the latest main branch. 3. Or run _Black_ on your machine: - create a new virtualenv (make sure it's the same Python version); - clone this repository; - run `pip install -e .[d]`; - run `pip install -r test_requirements.txt` - make sure it's sane by running `python -m pytest`; and - run `black` like you did last time. --> **Describe the bug** <!-- A clear and concise description of what the bug is. --> Black strips () from a tuple containing a single entry. **To Reproduce** <!-- Minimal steps to reproduce the behavior with source code and Black's configuration. --> For example, take this code: ```python class Transaction(Model): __table_args__ = (UniqueConstraint("entry_a_id", "entry_b_id")) ``` Black produces: ```python class Transaction(Model): __table_args__ = UniqueConstraint("entry_a_id", "entry_b_id") ``` This doesn't work with SQLAlchemy's expectation, causing errors: > sqlalchemy.exc.ArgumentError: __table_args__ value must be a tuple, dict, or None **Expected behavior** The () are not stripped. **Environment** <!-- Please complete the following information: --> - Black's version: tested using online main & local 24.3.0 - OS and Python version: your website & Python (CPython) 3.11.5 **Additional context** This is the specific thing that it breaks for me https://docs.sqlalchemy.org/en/20/orm/declarative_tables.html#orm-declarative-table-configuration
1medium
Title: [Documentation Question] Upsizing segmentation masks Body: I'm curious how a type uint segmentation mask is able to be resized larger. The only method that makes sense to me would be KNN, but the docs say, "Note that segmentation maps are handled internally as heatmaps (one per class) and as such can be resized using cubic interpolation." But wouldn't cubic interpolation fill intermediate pixels with float values instead of only using the integer values present in the original mask?
3misc
Title: Capturing events from interactive plotly line drawing Body: ### Checklist - [x] I have searched the [existing issues](https://github.com/streamlit/streamlit/issues) for similar feature requests. - [x] I added a descriptive title and summary to this issue. ### Summary A way to be able to draw lines in plots and get the coordinates of that line would be very useful. In plotly, line drawing is implemented and is should fire a specific event, but streamlit has no way of accessing that event. ### Why? I was working on a dashboard with a plot of 2D probability densities of my data. A great way to understand this specific data is to "select" features that stand out in this probability density and find instances in the underlying data which is close to that feature. In my case, the features are lines of varying shapes and can always be thought of as the plot of a function y=f(x). As such, the easiest way to find instances that are close to the feature is to draw a simple line over the feature and calculate the distance to that line for all instances in my dataset. The trick is then to get the coordinates of a line that I draw on a heatmap plot. The closest I can get currently is to draw a lasso around a thin slice, but that gives more complexity to the "search", since my target line now has a thickness. I'm sure that there's plenty more cases where it makes sense to get the coordinates of a line drawn on a plot or an image. ### How? Interactive line drawing in plotly is described [here](https://plotly.com/python/shapes/#drawing-shapes-with-a-mouse-on-cartesian-plots). For my use-case, the `drawopenpath` option is the most suitable. Reading in plotly's documentation, this will send a `relayout` event, but that doesn't seem to trigger anything on the streamlit side. Short example of what I tried: ``` import streamlit as st import plotly.graph_objects as go fig = go.Figure() fig.add_scatter(x=[0, 1, 2, 3], y=[1,2, 4, 6]) events = st.plotly_chart( fig, on_select="rerun", config={ 'modeBarButtonsToAdd': [ 'drawopenpath', ] } ) events ``` ### Additional Context _No response_
1medium
Title: RoBERTa need vocab.json in hugging face Transformers Body: In hugging face, the `RobertaTokenizer` need a vocal file that is json format, would you tell how to fix? Otherwise release a json format vocab? PS:transformers version is 3.2.0 Best regards!
1medium
Title: pdoc does not seem to play nicely with GitPython when in a package Body: #### Problem Description pdoc is unable to import package that uses GitPython. We've noticed this issue in a large application, and I have created a minimal example that has been able to reproduce the issue here: https://github.com/cquick01/pdoc-test Our larger application runs fine when running normally, and that other `pdoc3` tool has no issues. So it is definitely something that `pdoc` is doing differently than the rest. When commenting out references to GitPython in our larger application, `pdoc` then runs successfully across our entire package. #### Steps to reproduce the behavior: 1. Follow README in https://github.com/cquick01/pdoc-test 2. See errors ``` Warn: Error loading test_package: Traceback (most recent call last): File "/home/cquick/test/venv/lib/python3.10/site-packages/git/__init__.py", line 87, in <module> refresh() File "/home/cquick/test/venv/lib/python3.10/site-packages/git/__init__.py", line 78, in refresh if not FetchInfo.refresh(): File "/home/cquick/test/venv/lib/python3.10/site-packages/git/remote.py", line 304, in refresh if Git().version_info[:2] >= (2, 10): File "/home/cquick/test/venv/lib/python3.10/site-packages/git/cmd.py", line 679, in version_info return self._version_info File "/home/cquick/test/venv/lib/python3.10/site-packages/git/cmd.py", line 638, in __getattr__ return LazyMixin.__getattr__(self, name) File "/home/cquick/test/venv/lib/python3.10/site-packages/gitdb/util.py", line 253, in __getattr__ self._set_cache_(attr) File "/home/cquick/test/venv/lib/python3.10/site-packages/git/cmd.py", line 659, in _set_cache_ version_numbers = process_version.split(' ')[2] IndexError: list index out of range The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/cquick/test/venv/lib/python3.10/site-packages/pdoc/extract.py", line 207, in load_module return importlib.import_module(module) File "/home/cquick/.pyenv/versions/3.10.6/lib/python3.10/importlib/__init__.py", line 126, in import_module return _bootstrap._gcd_import(name[level:], package, level) File "<frozen importlib._bootstrap>", line 1050, in _gcd_import File "<frozen importlib._bootstrap>", line 1027, in _find_and_load File "<frozen importlib._bootstrap>", line 1006, in _find_and_load_unlocked File "<frozen importlib._bootstrap>", line 688, in _load_unlocked File "<frozen importlib._bootstrap_external>", line 883, in exec_module File "<frozen importlib._bootstrap>", line 241, in _call_with_frames_removed File "/home/cquick/test/test_package/__init__.py", line 1, in <module> import git File "/home/cquick/test/venv/lib/python3.10/site-packages/git/__init__.py", line 89, in <module> raise ImportError('Failed to initialize: {0}'.format(exc)) from exc ImportError: Failed to initialize: list index out of range The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/cquick/test/venv/lib/python3.10/site-packages/pdoc/extract.py", line 250, in walk_packages2 module = load_module(mod.name) File "/home/cquick/.pyenv/versions/3.10.6/lib/python3.10/contextlib.py", line 79, in inner return func(*args, **kwds) File "/home/cquick/test/venv/lib/python3.10/site-packages/pdoc/extract.py", line 209, in load_module raise RuntimeError(f"Error importing {module}") from e RuntimeError: Error importing test_package (/home/cquick/test/venv/lib/python3.10/site-packages/pdoc/extract.py:252) pdoc server ready at http://localhost:8080 ``` #### System Information Paste the output of "pdoc --version" here. ``` pdoc --version pdoc: 12.0.2 Python: 3.10.6 Platform: Linux-5.10.102.1-microsoft-standard-WSL2-x86_64-with-glibc2.35 ``` Will try to provide more info if needed.
2hard
Title: ReadTheDocs needs updating Body: Thanks for your error report and we appreciate it a lot. **Checklist** 1. I have searched related issues but cannot get the expected help. 2. I have read the [FAQ documentation](https://mmdetection.readthedocs.io/en/latest/faq.html) but cannot get the expected help. 3. The bug has not been fixed in the latest version. **Describe the bug** Some readthedocs sections are not populating in v3. Have to use v2.28 or earlier. Additionally, https://mmdetection.readthedocs.io/en/latest/faq.html in the issue template is not found. **Reproduction** ![image](https://github.com/user-attachments/assets/c038bf9c-c286-4eaa-b6b1-5c2451092f7a) 1. What command or script did you run? ``` https://mmdetection.readthedocs.io/en/latest/api.html ```
1medium
Title: I have 2 table. which have (one to many relationship). User and Car , one user can buy many cars .when i deleted Parent(User) child(cars) related with that parents must be deletd but when i deleted the child parents should not be deleted. Body: ### First Check - [X] I added a very descriptive title to this issue. - [X] I used the GitHub search to find a similar issue and didn't find it. - [X] I searched the SQLModel documentation, with the integrated search. - [X] I already searched in Google "How to X in SQLModel" and didn't find any information. - [X] I already read and followed all the tutorial in the docs and didn't find an answer. - [X] I already checked if it is not related to SQLModel but to [Pydantic](https://github.com/samuelcolvin/pydantic). - [X] I already checked if it is not related to SQLModel but to [SQLAlchemy](https://github.com/sqlalchemy/sqlalchemy). ### Commit to Help - [X] I commit to help with one of those options 👆 ### Example Code ```python class UserInSchema(SQLModel): name: str phone: str class User(UserInSchema, table=True): __tablename__ = "user_data" id: Optional[int] = Field(default=None, primary_key=True) cars: List["Car"] = Relationship(back_populates="user") class CarInSchema(SQLModel): name: str color: str class Car(CarInSchema, table=True): __tablename__ = "car_data" id: Optional[int] = Field(default=None, primary_key=True) # user_id = int = Field(sa_column=Column(Integer, ForeignKey("hero.id", ondelete="CASCADE"))) user_id: int = Field(default=None, foreign_key="user_data.id") user: Optional[User] = Relationship(back_populates="cars", sa_relationship_kwargs={"cascade":"all , delete"}) ``` ### Description one to many relationship b/w user and car..means that one user can buy many cars ..when I deleted parents which is User the childs related with that parents are deleted which work correctly but when i deleted the child ,all childs and parent which is related with that child are also deleted , But i don,t want that.. ### Operating System Linux ### Operating System Details _No response_ ### SQLModel Version 0.0.6 ### Python Version 3.9.13 ### Additional Context _No response_
1medium
Title: Only output should be kept for keep_output and init_cell Body: Currently, `nbstripout` ignores `keep_output` and `init_cell` cells entirely. However, this means that lots of stuff beyond the output stays, such as `execution_count`. I think keeping this does not meet the design goals, and it can cause Git conflicts. Feature request: Treat these two types of cells normally, except keep the output.
1medium
Title: Error while running "Follow the likers of photos of users" Body: <!-- Did you know that we have a Discord channel ? Join us: https://discord.gg/FDETsht --> <!-- Is this a Feature Request ? Please, check out our Wiki first https://github.com/timgrossmann/InstaPy/wiki --> ## Expected Behavior it should follow the Amount of of likers of a post specified. ## Current Behavior it says, "Liked button now found, might be a video" and skips the picture ## Possible Solution (optional) ## InstaPy configuration session.follow_likers(['alkaramstudio' , 'khaadi'], photos_grab_amount = 2, follow_likers_per_photo = 15, randomize=True, sleep_delay=10, interact=False)
1medium
Title: [Bug]: Torch is not able to use GPU Body: ### Checklist - [ ] The issue exists after disabling all extensions - [ ] The issue exists on a clean installation of webui - [X] The issue is caused by an extension, but I believe it is caused by a bug in the webui - [ ] The issue exists in the current version of the webui - [ ] The issue has not been reported before recently - [X] The issue has been reported before but has not been fixed yet ### What happened? Webui isn't working after I installed a model and related extension. Model : reffusion (https://theally.notion.site/Quick-n-Dirty-Riffusion-txt2audio-Tutorial-18e57df9ef214c3280efc5998bbf774d) Extension : https://github.com/enlyth/sd-webui-riffusion my cmd showing 'RuntimeError: Torch is not able to use GPU; add --skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check' After I add '--skip-torch-cuda-test' in variable, generating image took forever. I guess WebUI is not using GPU. I already updated latest CUDA and cuDNN after this issue occurred, but still it isn't work. ### Steps to reproduce the problem 1. Install both model and related extension above 2. restart WebUI 3. See error message 4. Depression ### What should have happened? WebUI should work as always worked. ### What browsers do you use to access the UI ? Google Chrome ### Sysinfo I couldn't open WebUI page without adding variable '--skip-torch-cuda-test'. After adding it, I got this. { "Platform": "Windows-10-10.0.19045-SP0", "Python": "3.10.8", "Version": "v1.4.0-RC-2397-g1c0a0c4c", "Commit": "1c0a0c4c26f78c32095ebc7f8af82f5c04fca8c0", "Script path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui", "Data path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui", "Extensions dir": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions", "Checksum": "67e854c290bf0df6bf2c6814a8e7781b8a57940a6cb7891b446b8b84b880dab1", "Commandline": [ "launch.py", "--skip-torch-cuda-test", "--xformers", "--deepdanbooru", "--autolaunch" ], "Torch env info": "'NoneType' object has no attribute 'splitlines'", "Exceptions": [ { "exception": "'NoneType' object has no attribute 'lowvram'", "traceback": [ [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\call_queue.py, line 57, f", "res = list(func(*args, **kwargs))" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\call_queue.py, line 36, f", "res = func(*args, **kwargs)" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\txt2img.py, line 109, txt2img", "processed = processing.process_images(p)" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\processing.py, line 832, process_images", "sd_models.reload_model_weights()" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\sd_models.py, line 860, reload_model_weights", "sd_model = reuse_model_from_already_loaded(sd_model, checkpoint_info, timer)" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\sd_models.py, line 793, reuse_model_from_already_loaded", "send_model_to_cpu(sd_model)" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\sd_models.py, line 662, send_model_to_cpu", "if m.lowvram:" ] ] }, { "exception": "Torch not compiled with CUDA enabled", "traceback": [ [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\sd_models.py, line 620, get_sd_model", "load_model()" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\sd_models.py, line 770, load_model", "with devices.autocast(), torch.no_grad():" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\devices.py, line 218, autocast", "if has_xpu() or has_mps() or cuda_no_autocast():" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\devices.py, line 28, cuda_no_autocast", "device_id = get_cuda_device_id()" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\devices.py, line 40, get_cuda_device_id", ") or torch.cuda.current_device()" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\venv\\lib\\site-packages\\torch\\cuda\\__init__.py, line 674, current_device", "_lazy_init()" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\venv\\lib\\site-packages\\torch\\cuda\\__init__.py, line 239, _lazy_init", "raise AssertionError(\"Torch not compiled with CUDA enabled\")" ] ] }, { "exception": "No module named 'fonts'", "traceback": [ [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\scripts.py, line 508, load_scripts", "script_module = script_loading.load_module(scriptfile.path)" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\script_loading.py, line 13, load_module", "module_spec.loader.exec_module(module)" ], [ "<frozen importlib._bootstrap_external>, line 883, exec_module", "" ], [ "<frozen importlib._bootstrap>, line 241, _call_with_frames_removed", "" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-daam-master\\scripts\\daam_script.py, line 21, <module>", "from scripts.daam import trace, utils" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-daam-master\\scripts\\daam\\__init__.py, line 3, <module>", "from .utils import *" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-daam-master\\scripts\\daam\\utils.py, line 9, <module>", "from fonts.ttf import Roboto" ] ] }, { "exception": "No module named 'fonts'", "traceback": [ [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\scripts.py, line 508, load_scripts", "script_module = script_loading.load_module(scriptfile.path)" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\script_loading.py, line 13, load_module", "module_spec.loader.exec_module(module)" ], [ "<frozen importlib._bootstrap_external>, line 883, exec_module", "" ], [ "<frozen importlib._bootstrap>, line 241, _call_with_frames_removed", "" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-daam\\scripts\\daam_script.py, line 21, <module>", "from scripts.daam import trace, utils" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-daam\\scripts\\daam\\__init__.py, line 3, <module>", "from .utils import *" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-daam\\scripts\\daam\\utils.py, line 9, <module>", "from fonts.ttf import Roboto" ] ] }, { "exception": "cannot import name 'get_correct_sampler' from 'modules.processing' (A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\processing.py)", "traceback": [ [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\scripts.py, line 508, load_scripts", "script_module = script_loading.load_module(scriptfile.path)" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\modules\\script_loading.py, line 13, load_module", "module_spec.loader.exec_module(module)" ], [ "<frozen importlib._bootstrap_external>, line 883, exec_module", "" ], [ "<frozen importlib._bootstrap>, line 241, _call_with_frames_removed", "" ], [ "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\AI-WEBUI-scripts-Random\\scripts\\Random grid.py, line 27, <module>", "from modules.processing import process_images, Processed, get_correct_sampler, StableDiffusionProcessingTxt2Img" ] ] } ], "CPU": { "model": "Intel64 Family 6 Model 151 Stepping 2, GenuineIntel", "count logical": 20, "count physical": 12 }, "RAM": { "total": "48GB", "used": "13GB", "free": "35GB" }, "Extensions": [ { "name": "AI-WEBUI-scripts-Random", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\AI-WEBUI-scripts-Random", "version": "b9faf99c", "branch": "main", "remote": "https://github.com/mkco5162/AI-WEBUI-scripts-Random" }, { "name": "openpose-editor", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\openpose-editor", "version": "c9357715", "branch": "master", "remote": "https://github.com/fkunn1326/openpose-editor.git" }, { "name": "sd-dynamic-prompts", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\sd-dynamic-prompts", "version": "1567e787", "branch": "main", "remote": "https://github.com/adieyal/sd-dynamic-prompts" }, { "name": "sd-webui-3d-open-pose-editor-main", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\sd-webui-3d-open-pose-editor-main", "version": "", "branch": null, "remote": null }, { "name": "sd-webui-additional-networks", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\sd-webui-additional-networks", "version": "e9f3d622", "branch": "main", "remote": "https://github.com/kohya-ss/sd-webui-additional-networks.git" }, { "name": "sd-webui-controlnet", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\sd-webui-controlnet", "version": "3b4eedd9", "branch": "main", "remote": "https://github.com/Mikubill/sd-webui-controlnet" }, { "name": "sd-webui-regional-prompter", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\sd-webui-regional-prompter", "version": "50493ec0", "branch": "main", "remote": "https://github.com/hako-mikan/sd-webui-regional-prompter.git" }, { "name": "sd_dreambooth_extension", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\sd_dreambooth_extension", "version": "45a12fe5", "branch": "main", "remote": "https://github.com/d8ahazard/sd_dreambooth_extension.git" }, { "name": "stable-diffusion-webui-daam", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-daam", "version": "3a4fe7a2", "branch": "master", "remote": "https://github.com/Bing-su/stable-diffusion-webui-daam" }, { "name": "stable-diffusion-webui-daam-master", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-daam-master", "version": "", "branch": null, "remote": null }, { "name": "stable-diffusion-webui-images-browser", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-images-browser", "version": "a42c7a30", "branch": "main", "remote": "https://github.com/yfszzx/stable-diffusion-webui-images-browser" }, { "name": "stable-diffusion-webui-localization-ko_KR", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-localization-ko_KR", "version": "78431bea", "branch": "main", "remote": "https://github.com/36DB/stable-diffusion-webui-localization-ko_KR.git" }, { "name": "stable-diffusion-webui-wd14-tagger", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\stable-diffusion-webui-wd14-tagger", "version": "e72d984b", "branch": "master", "remote": "https://github.com/picobyte/stable-diffusion-webui-wd14-tagger" }, { "name": "tag-autocomplete", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\tag-autocomplete", "version": "3eef536b", "branch": "main", "remote": "https://github.com/DominikDoom/a1111-sd-webui-tagcomplete" } ], "Inactive extensions": [ { "name": "adetailer", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\adetailer", "version": "910bf3b9", "branch": "main", "remote": "https://github.com/Bing-su/adetailer.git" }, { "name": "gif2gif", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\gif2gif", "version": "5121851e", "branch": "main", "remote": "https://github.com/LonicaMewinsky/gif2gif.git" }, { "name": "sd-webui-animatediff", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\sd-webui-animatediff", "version": "f20f57f6", "branch": "master", "remote": "https://github.com/continue-revolution/sd-webui-animatediff.git" }, { "name": "sd-webui-openpose-editor", "path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\sd-webui-openpose-editor", "version": "cebe13e0", "branch": "main", "remote": "https://github.com/huchenlei/sd-webui-openpose-editor" } ], "Environment": { "COMMANDLINE_ARGS": " --skip-torch-cuda-test --xformers --deepdanbooru --autolaunch", "GRADIO_ANALYTICS_ENABLED": "False" }, "Config": { "samples_save": true, "samples_format": "png", "samples_filename_pattern": "", "grid_save": true, "grid_format": "png", "grid_extended_filename": false, "grid_only_if_multiple": true, "n_rows": -1, "enable_pnginfo": true, "save_txt": false, "save_images_before_face_restoration": false, "jpeg_quality": 80, "export_for_4chan": true, "use_original_name_batch": false, "save_selected_only": true, "do_not_add_watermark": false, "outdir_samples": "", "outdir_txt2img_samples": "outputs/txt2img-images", "outdir_img2img_samples": "outputs/img2img-images", "outdir_extras_samples": "outputs/extras-images", "outdir_grids": "", "outdir_txt2img_grids": "outputs/txt2img-grids", "outdir_img2img_grids": "outputs/img2img-grids", "outdir_save": "log/images", "save_to_dirs": false, "grid_save_to_dirs": false, "use_save_to_dirs_for_ui": false, "directories_filename_pattern": "", "directories_max_prompt_words": 8, "ESRGAN_tile": 192, "ESRGAN_tile_overlap": 8, "realesrgan_enabled_models": [ "R-ESRGAN x4+", "R-ESRGAN x4+ Anime6B", "R-ESRGAN 4x+ Anime6B" ], "SWIN_tile": 192, "SWIN_tile_overlap": 8, "ldsr_steps": 100, "upscaler_for_img2img": "R-ESRGAN 4x+ Anime6B", "face_restoration_model": null, "code_former_weight": 0.5, "face_restoration_unload": false, "memmon_poll_rate": 8, "samples_log_stdout": false, "multiple_tqdm": true, "sd_model_checkpoint": "0.7(flosbbwmix_v20) + 0.3(furrytoonmix_v10).safetensors [1ac5ad6e51]", "sd_hypernetwork": "None", "img2img_color_correction": false, "save_images_before_color_correction": false, "img2img_fix_steps": false, "enable_quantization": false, "enable_emphasis": true, "use_old_emphasis_implementation": false, "enable_batch_seeds": true, "comma_padding_backtrack": 20, "filter_nsfw": false, "CLIP_stop_at_last_layers": 2, "random_artist_categories": [], "interrogate_keep_models_in_memory": false, "interrogate_use_builtin_artists": true, "interrogate_clip_num_beams": 1, "interrogate_clip_min_length": 24, "interrogate_clip_max_length": 48, "interrogate_clip_dict_limit": 1500.0, "interrogate_deepbooru_score_threshold": 0.5, "show_progressbar": true, "show_progress_every_n_steps": 0, "return_grid": true, "do_not_show_images": false, "add_model_hash_to_info": true, "add_model_name_to_info": false, "font": "", "js_modal_lightbox": true, "js_modal_lightbox_initially_zoomed": true, "show_progress_in_title": true, "hide_samplers": [ "LMS", "Heun", "DPM2 a", "DPM2 Karras", "LMS Karras", "DPM fast", "DPM adaptive", "PLMS", "DPM2 a Karras", "DPM2" ], "eta_ddim": 0, "eta_ancestral": 0.2, "ddim_discretize": "uniform", "s_churn": 0, "s_tmin": 0, "s_noise": 0.2, "eta_noise_seed_delta": 0, "unload_models_when_training": true, "dataset_filename_word_regex": "", "dataset_filename_join_string": " ", "training_image_repeats_per_epoch": 100, "sd_hypernetwork_strength": 1, "quicksettings": "sd_model_checkpoint", "interrogate_return_ranks": false, "deepbooru_sort_alpha": true, "deepbooru_use_spaces": false, "deepbooru_escape": true, "grid_prevent_empty_spots": false, "use_scale_latent_for_hires_fix": false, "training_write_csv_every": 500.0, "sd_checkpoint_cache": 0, "localization": "ko_KR", "show_progress_grid": true, "disable_weights_auto_swap": false, "quicksettings_list": [ "sd_model_checkpoint" ], "sd_checkpoint_hash": "1ac5ad6e51854ac5bde68340bed3530912254b0e34c112f442ad50e63f66af6e", "disabled_extensions": [ "adetailer", "gif2gif", "sd-webui-animatediff", "sd-webui-openpose-editor" ], "disable_all_extensions": "none", "restore_config_state_file": "", "save_images_add_number": true, "grid_zip_filename_pattern": "", "grid_text_active_color": "#000000", "grid_text_inactive_color": "#999999", "grid_background_color": "#ffffff", "save_images_before_highres_fix": false, "save_mask": false, "save_mask_composite": false, "webp_lossless": false, "img_downscale_threshold": 4.0, "target_side_length": 4000.0, "img_max_size_mp": 200.0, "use_upscaler_name_as_suffix": false, "save_init_img": false, "temp_dir": "", "clean_temp_dir_at_start": false, "save_incomplete_images": false, "outdir_init_images": "outputs/init-images", "ldsr_cached": false, "SCUNET_tile": 256, "SCUNET_tile_overlap": 8, "face_restoration": false, "auto_launch_browser": "Local", "show_warnings": false, "show_gradio_deprecation_warnings": true, "print_hypernet_extra": false, "list_hidden_files": true, "disable_mmap_load_safetensors": false, "hide_ldm_prints": true, "api_enable_requests": true, "api_forbid_local_requests": true, "api_useragent": "", "pin_memory": true, "save_optimizer_state": false, "save_training_settings_to_txt": true, "training_xattention_optimizations": false, "training_enable_tensorboard": false, "training_tensorboard_save_images": false, "training_tensorboard_flush_every": 120.0, "sd_checkpoints_limit": 1, "sd_checkpoints_keep_in_cpu": true, "sd_unet": "Automatic", "upcast_attn": false, "randn_source": "GPU", "tiling": false, "hires_fix_refiner_pass": "second pass", "sdxl_crop_top": 0.0, "sdxl_crop_left": 0.0, "sdxl_refiner_low_aesthetic_score": 2.5, "sdxl_refiner_high_aesthetic_score": 6.0, "sd_vae_checkpoint_cache": 0, "sd_vae": "kl-f8-anime2.ckpt", "sd_vae_overrides_per_model_preferences": true, "auto_vae_precision": true, "sd_vae_encode_method": "Full", "sd_vae_decode_method": "Full", "inpainting_mask_weight": 1, "initial_noise_multiplier": 1, "img2img_extra_noise": 0, "img2img_background_color": "#ffffff", "img2img_editor_height": 720, "img2img_sketch_default_brush_color": "#ffffff", "img2img_inpaint_mask_brush_color": "#ffffff", "img2img_inpaint_sketch_default_brush_color": "#ffffff", "return_mask": false, "return_mask_composite": false, "cross_attention_optimization": "Automatic", "s_min_uncond": 0, "token_merging_ratio": 0, "token_merging_ratio_img2img": 0, "token_merging_ratio_hr": 0, "pad_cond_uncond": true, "persistent_cond_cache": true, "batch_cond_uncond": true, "use_old_karras_scheduler_sigmas": false, "no_dpmpp_sde_batch_determinism": false, "use_old_hires_fix_width_height": false, "dont_fix_second_order_samplers_schedule": false, "hires_fix_use_firstpass_conds": false, "use_old_scheduling": false, "lora_functional": false, "interrogate_clip_skip_categories": [], "deepbooru_filter_tags": "", "extra_networks_show_hidden_directories": true, "extra_networks_hidden_models": "When searched", "extra_networks_default_multiplier": 1, "extra_networks_card_width": 0.0, "extra_networks_card_height": 0.0, "extra_networks_card_text_scale": 1, "extra_networks_card_show_desc": true, "extra_networks_add_text_separator": " ", "ui_extra_networks_tab_reorder": "", "textual_inversion_print_at_load": false, "textual_inversion_add_hashes_to_infotext": true, "sd_lora": "None", "lora_preferred_name": "Alias from file", "lora_add_hashes_to_infotext": true, "lora_show_all": false, "lora_hide_unknown_for_versions": [], "lora_in_memory_limit": 0, "gradio_theme": "Default", "gradio_themes_cache": true, "gallery_height": "", "send_seed": true, "send_size": true, "js_modal_lightbox_gamepad": false, "js_modal_lightbox_gamepad_repeat": 250.0, "samplers_in_dropdown": true, "dimensions_and_batch_together": true, "keyedit_precision_attention": 0.1, "keyedit_precision_extra": 0.05, "keyedit_delimiters": ".,\\/!?%^*;:{}=`~()", "keyedit_move": true, "ui_tab_order": [], "hidden_tabs": [], "ui_reorder_list": [], "hires_fix_show_sampler": false, "hires_fix_show_prompts": false, "disable_token_counters": false, "extra_options_txt2img": [], "extra_options_img2img": [], "extra_options_cols": 1, "extra_options_accordion": false, "add_user_name_to_info": false, "add_version_to_infotext": true, "infotext_styles": "Apply if any", "live_previews_enable": true, "live_previews_image_format": "png", "show_progress_type": "Approx NN", "live_preview_allow_lowvram_full": false, "live_preview_content": "Prompt", "live_preview_refresh_period": 1000.0, "live_preview_fast_interrupt": false, "s_tmax": 0, "k_sched_type": "Automatic", "sigma_min": 0.0, "sigma_max": 0.0, "rho": 0.0, "always_discard_next_to_last_sigma": false, "sgm_noise_multiplier": false, "uni_pc_variant": "bh1", "uni_pc_skip_type": "time_uniform", "uni_pc_order": 3, "uni_pc_lower_order_final": true, "postprocessing_enable_in_main_ui": [], "postprocessing_operation_order": [], "upscaling_max_images_in_cache": 5, "canvas_hotkey_zoom": "Alt", "canvas_hotkey_adjust": "Ctrl", "canvas_hotkey_move": "F", "canvas_hotkey_fullscreen": "S", "canvas_hotkey_reset": "R", "canvas_hotkey_overlap": "O", "canvas_show_tooltip": true, "canvas_auto_expand": true, "canvas_blur_prompt": false, "canvas_disabled_functions": [ "Overlap" ], "images_history_preload": false, "images_record_paths": true, "images_delete_message": true, "images_history_page_columns": 6.0, "images_history_page_rows": 6.0, "images_history_pages_perload": 20.0, "tagger_out_filename_fmt": "[name].[output_extension]", "tagger_count_threshold": 100, "tagger_batch_recursive": true, "tagger_auto_serde_json": true, "tagger_store_images": false, "tagger_weighted_tags_files": false, "tagger_verbose": false, "tagger_repl_us": true, "tagger_repl_us_excl": "0_0, (o)_(o), +_+, +_-, ._., <o>_<o>, <|>_<|>, =_=, >_<, 3_3, 6_9, >_o, @_@, ^_^, o_o, u_u, x_x, |_|, ||_||", "tagger_escape": false, "tagger_batch_size": 1024.0, "tagger_hf_cache_dir": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\models\\interrogators", "tac_tagFile": "danbooru.csv", "tac_active": true, "tac_activeIn.txt2img": true, "tac_activeIn.img2img": true, "tac_activeIn.negativePrompts": true, "tac_activeIn.thirdParty": true, "tac_activeIn.modelList": "", "tac_activeIn.modelListMode": "Blacklist", "tac_slidingPopup": true, "tac_maxResults": 5.0, "tac_showAllResults": false, "tac_resultStepLength": 100.0, "tac_delayTime": 100.0, "tac_useWildcards": true, "tac_sortWildcardResults": true, "tac_useEmbeddings": true, "tac_includeEmbeddingsInNormalResults": false, "tac_useHypernetworks": true, "tac_useLoras": true, "tac_useLycos": true, "tac_showWikiLinks": false, "tac_showExtraNetworkPreviews": true, "tac_replaceUnderscores": true, "tac_escapeParentheses": true, "tac_appendComma": true, "tac_appendSpace": true, "tac_alwaysSpaceAtEnd": true, "tac_modelKeywordCompletion": "Never", "tac_modelKeywordLocation": "Start of prompt", "tac_wildcardCompletionMode": "To next folder level", "tac_alias.searchByAlias": true, "tac_alias.onlyShowAlias": false, "tac_translation.translationFile": "None", "tac_translation.oldFormat": false, "tac_translation.searchByTranslation": true, "tac_translation.liveTranslation": false, "tac_extra.extraFile": "extra-quality-tags.csv", "tac_extra.addMode": "Insert before", "tac_chantFile": "demo-chants.json", "tac_keymap": "{\n \"MoveUp\": \"ArrowUp\",\n \"MoveDown\": \"ArrowDown\",\n \"JumpUp\": \"PageUp\",\n \"JumpDown\": \"PageDown\",\n \"JumpToStart\": \"Home\",\n \"JumpToEnd\": \"End\",\n \"ChooseSelected\": \"Enter\",\n \"ChooseFirstOrSelected\": \"Tab\",\n \"Close\": \"Escape\"\n}", "tac_colormap": "{\n \"danbooru\": {\n \"-1\": [\"red\", \"maroon\"],\n \"0\": [\"lightblue\", \"dodgerblue\"],\n \"1\": [\"indianred\", \"firebrick\"],\n \"3\": [\"violet\", \"darkorchid\"],\n \"4\": [\"lightgreen\", \"darkgreen\"],\n \"5\": [\"orange\", \"darkorange\"]\n },\n \"e621\": {\n \"-1\": [\"red\", \"maroon\"],\n \"0\": [\"lightblue\", \"dodgerblue\"],\n \"1\": [\"gold\", \"goldenrod\"],\n \"3\": [\"violet\", \"darkorchid\"],\n \"4\": [\"lightgreen\", \"darkgreen\"],\n \"5\": [\"tomato\", \"darksalmon\"],\n \"6\": [\"red\", \"maroon\"],\n \"7\": [\"whitesmoke\", \"black\"],\n \"8\": [\"seagreen\", \"darkseagreen\"]\n }\n}", "tac_refreshTempFiles": "Refresh TAC temp files", "dp_ignore_whitespace": false, "dp_write_raw_template": false, "dp_write_prompts_to_file": false, "dp_parser_variant_start": "{", "dp_parser_variant_end": "}", "dp_parser_wildcard_wrap": "__", "dp_limit_jinja_prompts": false, "dp_auto_purge_cache": false, "dp_wildcard_manager_no_dedupe": false, "dp_wildcard_manager_no_sort": false, "dp_wildcard_manager_shuffle": false, "dp_magicprompt_default_model": "Gustavosta/MagicPrompt-Stable-Diffusion", "dp_magicprompt_batch_size": 1, "ad_max_models": 2, "ad_save_previews": true, "ad_save_images_before": false, "ad_only_seleted_scripts": true, "ad_script_names": "dynamic_prompting,dynamic_thresholding,wildcard_recursive,wildcards,lora_block_weight", "ad_bbox_sortby": "None", "animatediff_model_path": "A:\\Stable Defusion\\WEBUI0.66.2\\stable-diffusion-webui\\extensions\\sd-webui-animatediff\\model", "animatediff_optimize_gif_palette": true, "animatediff_optimize_gif_gifsicle": true, "animatediff_xformers": "Optimize attention layers with xformers", "tac_modelSortOrder": "Name", "control_net_allow_script_control": false, "additional_networks_extra_lora_path": "", "additional_networks_sort_models_by": "name", "additional_networks_reverse_sort_order": false, "additional_networks_model_name_filter": "", "additional_networks_xy_grid_model_metadata": "", "additional_networks_hash_thread_count": 1.0, "additional_networks_back_up_model_when_saving": true, "additional_networks_show_only_safetensors": false, "additional_networks_show_only_models_with_metadata": "disabled", "additional_networks_max_top_tags": 20.0, "additional_networks_max_dataset_folders": 20.0, "control_net_detectedmap_dir": "detected_maps", "control_net_models_path": "", "control_net_modules_path": "", "control_net_unit_count": 3, "control_net_model_cache_size": 2, "control_net_inpaint_blur_sigma": 7, "control_net_no_detectmap": false, "control_net_detectmap_autosaving": false, "control_net_sync_field_args": true, "controlnet_show_batch_images_in_ui": false, "controlnet_increment_seed_during_batch": false, "controlnet_disable_openpose_edit": false, "controlnet_disable_photopea_edit": false, "controlnet_photopea_warning": true, "controlnet_ignore_noninpaint_mask": false, "controlnet_clip_detector_on_cpu": false, "tac_wildcardExclusionList": "", "tac_skipWildcardRefresh": false, "tac_useLoraPrefixForLycos": true, "tac_useStyleVars": false, "openpose3d_use_online_version": false, "regprp_debug": false, "regprp_hidepmask": false, "SWIN_torch_compile": false, "hypertile_enable_unet": false, "hypertile_enable_unet_secondpass": false, "hypertile_max_depth_unet": 3, "hypertile_max_tile_unet": 256, "hypertile_swap_size_unet": 3, "hypertile_enable_vae": false, "hypertile_max_depth_vae": 3, "hypertile_max_tile_vae": 128, "hypertile_swap_size_vae": 3, "controlnet_control_type_dropdown": false, "tac_frequencySort": true, "tac_frequencyFunction": "Logarithmic (weak)", "tac_frequencyMinCount": 3, "tac_frequencyMaxAge": 30, "tac_frequencyRecommendCap": 10, "tac_frequencyIncludeAlias": false }, "Startup": { "total": 35.643954038619995, "records": { "initial startup": 0.014950990676879883, "prepare environment/checks": 0.010963201522827148, "prepare environment/git version info": 0.0627896785736084, "prepare environment/torch GPU test": 0.001993417739868164, "prepare environment/clone repositores": 0.1445159912109375, "prepare environment/install requirements": 7.762157440185547, "prepare environment/run extensions installers/AI-WEBUI-scripts-Random": 0.0009968280792236328, "prepare environment/run extensions installers/openpose-editor": 0.0, "prepare environment/run extensions installers/sd-dynamic-prompts": 0.15795183181762695, "prepare environment/run extensions installers/sd-webui-3d-open-pose-editor-main": 0.18438172340393066, "prepare environment/run extensions installers/sd-webui-additional-networks": 0.0, "prepare environment/run extensions installers/sd-webui-controlnet": 0.12956738471984863, "prepare environment/run extensions installers/sd-webui-regional-prompter": 0.0, "prepare environment/run extensions installers/sd_dreambooth_extension": 9.188960075378418, "prepare environment/run extensions installers/stable-diffusion-webui-daam": 0.25730133056640625, "prepare environment/run extensions installers/stable-diffusion-webui-daam-master": 0.25215673446655273, "prepare environment/run extensions installers/stable-diffusion-webui-images-browser": 0.0, "prepare environment/run extensions installers/stable-diffusion-webui-localization-ko_KR": 0.0, "prepare environment/run extensions installers/stable-diffusion-webui-wd14-tagger": 6.892964124679565, "prepare environment/run extensions installers/tag-autocomplete": 0.0, "prepare environment/run extensions installers": 17.064280033111572, "prepare environment": 25.04669976234436, "launcher": 0.0029897689819335938, "import torch": 4.869890928268433, "import gradio": 0.552384614944458, "setup paths": 0.6129496097564697, "import ldm": 0.004982948303222656, "import sgm": 0.0, "initialize shared": 0.13554716110229492, "other imports": 0.4644455909729004, "opts onchange": 0.0039865970611572266, "setup SD model": 0.0, "setup codeformer": 0.0009968280792236328, "setup gfpgan": 0.009966611862182617, "set samplers": 0.0, "list extensions": 0.0029900074005126953, "restore config state file": 0.0, "list SD models": 0.26636576652526855, "list localizations": 0.0009965896606445312, "load scripts/custom_code.py": 0.004983425140380859, "load scripts/img2imgalt.py": 0.0, "load scripts/loopback.py": 0.0009965896606445312, "load scripts/outpainting_mk_2.py": 0.0, "load scripts/poor_mans_outpainting.py": 0.0, "load scripts/postprocessing_codeformer.py": 0.000997304916381836, "load scripts/postprocessing_gfpgan.py": 0.0, "load scripts/postprocessing_upscale.py": 0.0, "load scripts/prompt_matrix.py": 0.0009961128234863281, "load scripts/prompts_from_file.py": 0.0, "load scripts/sd_upscale.py": 0.0, "load scripts/xyz_grid.py": 0.0019931793212890625, "load scripts/ldsr_model.py": 0.7614519596099854, "load scripts/lora_script.py": 0.14751935005187988, "load scripts/scunet_model.py": 0.020929813385009766, "load scripts/swinir_model.py": 0.018936634063720703, "load scripts/hotkey_config.py": 0.0, "load scripts/extra_options_section.py": 0.0, "load scripts/hypertile_script.py": 0.03986644744873047, "load scripts/hypertile_xyz.py": 0.0009970664978027344, "load scripts/postprocessing_autosized_crop.py": 0.0, "load scripts/postprocessing_caption.py": 0.0, "load scripts/postprocessing_create_flipped_copies.py": 0.0, "load scripts/postprocessing_focal_crop.py": 0.0019931793212890625, "load scripts/postprocessing_split_oversized.py": 0.0009968280792236328, "load scripts/soft_inpainting.py": 0.0, "load scripts/Random dynamic_prompting.py": 0.0009965896606445312, "load scripts/Random grid.py": 0.0019931793212890625, "load scripts/Random.py": 0.0, "load scripts/main.py": 0.11461639404296875, "load scripts/dynamic_prompting.py": 0.09268975257873535, "load scripts/openpose_editor.py": 0.03189373016357422, "load scripts/additional_networks.py": 0.08571290969848633, "load scripts/addnet_xyz_grid_support.py": 0.0, "load scripts/lora_compvis.py": 0.0, "load scripts/metadata_editor.py": 0.0009965896606445312, "load scripts/model_util.py": 0.004983186721801758, "load scripts/safetensors_hack.py": 0.0, "load scripts/util.py": 0.0, "load scripts/adapter.py": 0.0, "load scripts/api.py": 0.5023193359375, "load scripts/batch_hijack.py": 0.0009965896606445312, "load scripts/cldm.py": 0.0, "load scripts/controlnet.py": 0.11062979698181152, "load scripts/controlnet_diffusers.py": 0.0009965896606445312, "load scripts/controlnet_lllite.py": 0.0, "load scripts/controlnet_lora.py": 0.0, "load scripts/controlnet_model_guess.py": 0.0009965896606445312, "load scripts/controlnet_sparsectrl.py": 0.0, "load scripts/controlnet_version.py": 0.0, "load scripts/enums.py": 0.0009965896606445312, "load scripts/external_code.py": 0.0, "load scripts/global_state.py": 0.0, "load scripts/hook.py": 0.0009968280792236328, "load scripts/infotext.py": 0.0, "load scripts/logging.py": 0.0, "load scripts/lvminthin.py": 0.0, "load scripts/movie2movie.py": 0.0009968280792236328, "load scripts/supported_preprocessor.py": 0.0009965896606445312, "load scripts/utils.py": 0.0, "load scripts/xyz_grid_support.py": 0.0, "load scripts/attention.py": 0.0, "load scripts/latent.py": 0.0029900074005126953, "load scripts/regions.py": 0.0009965896606445312, "load scripts/rp.py": 0.021926403045654297, "load scripts/rps.py": 0.014950275421142578, "load scripts/__init__.py": 0.0009968280792236328, "load scripts/daam_script.py": 0.010963678359985352, "load scripts/images_history.py": 0.0408632755279541, "load scripts/tagger.py": 0.0627896785736084, "load scripts/model_keyword_support.py": 0.002990245819091797, "load scripts/shared_paths.py": 0.0, "load scripts/tag_autocomplete_helper.py": 0.07176041603088379, "load scripts/tag_frequency_db.py": 0.0009958744049072266, "load scripts/comments.py": 0.01694321632385254, "load scripts/refiner.py": 0.0009970664978027344, "load scripts/sampler.py": 0.0, "load scripts/seed.py": 0.0, "load scripts": 2.206629514694214, "load upscalers": 0.0029897689819335938, "refresh VAE": 0.0009968280792236328, "refresh textual inversion templates": 0.0, "scripts list_optimizers": 0.001993417739868164, "scripts list_unets": 0.0, "reload hypernetworks": 0.0, "initialize extra networks": 0.008969783782958984, "scripts before_ui_callback": 0.0019931793212890625, "create ui": 0.8292255401611328, "gradio launch": 0.5890524387359619, "add APIs": 0.004983425140380859, "app_started_callback/lora_script.py": 0.0, "app_started_callback/api.py": 0.0019936561584472656, "app_started_callback/tagger.py": 0.0019927024841308594, "app_started_callback/tag_autocomplete_helper.py": 0.0029900074005126953, "app_started_callback": 0.00697636604309082 } }, "Packages": [ "-itsandbytes==0.41.2.post2", "-orch==2.3.0", "-rotobuf==3.20.0", "absl-py==1.4.0", "accelerate==0.21.0", "addict==2.4.0", "aenum==3.1.15", "aiofiles==23.2.1", "aiohttp==3.8.5", "aiosignal==1.3.1", "albumentations==1.4.3", "altair==5.1.1", "antlr4-python3-runtime==4.9.3", "anyio==3.7.1", "astunparse==1.6.3", "async-timeout==4.0.3", "attrs==23.1.0", "av==10.0.0", "basicsr==1.4.2", "beautifulsoup4==4.12.2", "bitsandbytes==0.43.1", "blendmodes==2022", "boltons==23.0.0", "cachetools==5.3.1", "certifi==2023.7.22", "cffi==1.16.0", "chardet==5.2.0", "charset-normalizer==3.2.0", "clean-fid==0.1.35", "click==8.1.7", "clip==1.0", "colorama==0.4.6", "coloredlogs==15.0.1", "colorlog==6.8.2", "contourpy==1.1.0", "cssselect2==0.7.0", "cycler==0.11.0", "cython==3.0.8", "dadaptation==3.2", "deepdanbooru==1.0.2", "deprecation==2.1.0", "depth-anything==2024.1.22.0", "diffusers==0.26.3", "discord-webhook==1.3.0", "diskcache==5.6.3", "dsine==2024.3.23", "dynamicprompts==0.31.0", "easydict==1.12", "einops==0.4.1", "embreex==2.17.7.post4", "exceptiongroup==1.1.3", "facexlib==0.3.0", "fastapi==0.94.0", "ffmpy==0.3.1", "filelock==3.12.4", "filterpy==1.4.5", "flatbuffers==23.5.26", "fonttools==4.42.1", "frozenlist==1.4.0", "fsspec==2023.9.0", "ftfy==6.1.1", "future==0.18.3", "fvcore==0.1.5.post20221221", "gast==0.4.0", "gdown==4.7.1", "geffnet==1.0.2", "gfpgan==1.3.8", "gitdb==4.0.10", "gitpython==3.1.43", "glob2==0.5", "google-auth-oauthlib==1.0.0", "google-auth==2.23.0", "google-pasta==0.2.0", "gradio-client==0.5.0", "gradio==3.41.2", "grpcio==1.58.0", "h11==0.12.0", "h5py==3.9.0", "handrefinerportable==2024.2.12.0", "httpcore==0.15.0", "httpx==0.24.1", "huggingface-hub==0.20.3", "humanfriendly==10.0", "idna==3.4", "imageio==2.31.3", "importlib-metadata==6.8.0", "importlib-resources==6.0.1", "inflection==0.5.1", "insightface==0.7.3", "intel-openmp==2021.4.0", "iopath==0.1.9", "jinja2==3.1.2", "joblib==1.3.2", "jsonmerge==1.8.0", "jsonschema-specifications==2023.7.1", "jsonschema==4.19.0", "keras==2.13.1", "kiwisolver==1.4.5", "kornia==0.6.7", "lark==1.1.2", "lazy-loader==0.3", "libclang==16.0.6", "lightning-utilities==0.9.0", "llvmlite==0.42.0", "lmdb==1.4.1", "lpips==0.1.4", "lxml==5.1.0", "mapbox-earcut==1.0.1", "markdown-it-py==3.0.0", "markdown==3.4.4", "markupsafe==2.1.3", "matplotlib==3.6.2", "mdurl==0.1.2", "mediapipe==0.10.5", "mkl==2021.4.0", "mpmath==1.3.0", "multidict==6.0.4", "networkx==3.1", "numba==0.59.1", "numpy==1.24.3", "oauthlib==3.2.2", "omegaconf==2.2.3", "onnx==1.15.0", "onnxruntime-gpu==1.15.1", "open-clip-torch==2.20.0", "opencv-contrib-python==4.8.0.76", "opencv-python-headless==4.9.0.80", "opencv-python==4.8.0.76", "opt-einsum==3.3.0", "orjson==3.9.7", "packaging==23.1", "pandas==2.1.0", "piexif==1.1.3", "pillow-avif-plugin==1.4.3", "pillow==9.5.0", "pip==22.2.2", "platformdirs==3.10.0", "portalocker==2.8.2", "prettytable==3.9.0", "protobuf==3.20.3", "psutil==5.9.5", "py-cpuinfo==9.0.0", "pyasn1-modules==0.3.0", "pyasn1==0.5.0", "pycollada==0.8", "pycparser==2.21", "pydantic==1.10.12", "pydub==0.25.1", "pygifsicle==1.0.7", "pygments==2.16.1", "pyparsing==3.1.1", "pyreadline3==3.4.1", "pysocks==1.7.1", "python-dateutil==2.8.2", "python-multipart==0.0.6", "pytorch-lightning==1.9.4", "pytorch-optimizer==2.12.0", "pytz==2023.3.post1", "pywavelets==1.4.1", "pywin32==306", "pyyaml==6.0.1", "qudida==0.0.4", "realesrgan==0.3.0", "referencing==0.30.2", "regex==2023.8.8", "reportlab==4.1.0", "requests-oauthlib==1.3.1", "requests==2.31.0", "resize-right==0.0.2", "rich==13.6.0", "rpds-py==0.10.3", "rsa==4.9", "rtree==1.2.0", "safetensors==0.4.2", "scikit-image==0.21.0", "scikit-learn==1.4.1.post1", "scipy==1.11.2", "seaborn==0.13.0", "semantic-version==2.10.0", "send2trash==1.8.2", "sentencepiece==0.1.99", "setuptools==63.2.0", "shapely==2.0.3", "six==1.16.0", "smmap==5.0.0", "sniffio==1.3.0", "sounddevice==0.4.6", "soupsieve==2.5", "spandrel==0.1.6", "starlette==0.26.1", "support-developer==1.0.5", "svg.path==6.3", "svglib==1.5.1", "sympy==1.12", "tabulate==0.9.0", "tb-nightly==2.15.0a20230915", "tbb==2021.12.0", "tensorboard-data-server==0.7.1", "tensorboard==2.13.0", "tensorflow-estimator==2.13.0", "tensorflow-intel==2.13.0", "tensorflow-io-gcs-filesystem==0.31.0", "tensorflow==2.13.0", "termcolor==2.3.0", "thop==0.1.1.post2209072238", "threadpoolctl==3.3.0", "tifffile==2023.8.30", "timm==0.9.2", "tinycss2==1.2.1", "tokenizers==0.13.3", "tomesd==0.1.3", "tomli==2.0.1", "toolz==0.12.0", "torch==2.0.1", "torchdiffeq==0.2.3", "torchmetrics==1.1.2", "torchsde==0.2.6", "torchvision==0.15.2+cu118", "tqdm==4.65.0", "trampoline==0.1.2", "transformers==4.30.2", "trimesh==4.1.3", "typing-extensions==4.5.0", "tzdata==2023.3", "ultralytics==8.0.194", "urllib3==1.26.16", "uvicorn==0.23.2", "vhacdx==0.0.5", "wcwidth==0.2.6", "webencodings==0.5.1", "websockets==11.0.3", "werkzeug==2.3.7", "wheel==0.41.2", "wrapt==1.15.0", "xformers==0.0.20", "xxhash==3.4.1", "yacs==0.1.8", "yapf==0.40.1", "yarl==1.9.2", "zipp==3.16.2" ] } ### Console logs ```Shell venv "A:\Stable Defusion\WEBUI0.66.2\stable-diffusion-webui\venv\Scripts\Python.exe" Python 3.10.8 (tags/v3.10.8:aaaf517, Oct 11 2022, 16:50:30) [MSC v.1933 64 bit (AMD64)] Version: v1.4.0-RC-2397-g1c0a0c4c Commit hash: 1c0a0c4c26f78c32095ebc7f8af82f5c04fca8c0 Traceback (most recent call last): File "A:\Stable Defusion\WEBUI0.66.2\stable-diffusion-webui\launch.py", line 48, in <module> main() File "A:\Stable Defusion\WEBUI0.66.2\stable-diffusion-webui\launch.py", line 39, in main prepare_environment() File "A:\Stable Defusion\WEBUI0.66.2\stable-diffusion-webui\modules\launch_utils.py", line 386, in prepare_environment raise RuntimeError( RuntimeError: Torch is not able to use GPU; add --skip-torch-cuda-test to COMMANDLINE_ARGS variable to disable this check ``` ### Additional information I have updated my GPU driver recently. I already updated latest CUDA and cuDNN after this issue occurred, but still it isn't work.
2hard
Title: [Extensibility] Bring an "hookable" way to make third-party libraries possible Body: One missing part needed by the community to provide external directives is a way to configure the directive. Here is a draft of the API to provide configuration. ## No more `Directive` abstract class The Directive classes won't extend any tartiflette abstract classes. Instead, you will have to implement the methods you want to support depending on the feature you want to compliant with. _(see above regarding the feature set)_ **from** ```python from tartiflette.directive import Directive, CommonDirective @Directive("myDirective") class MyDirective(CommonDirective): pass ``` **to** ```python from tartiflette.directive import Directive @Directive("myDirective") class MyDirective: pass ``` ## Pass configuration at build time to a third party library This is currently impossible to configure a directive/scalar (pass configuration as API Key, URL etc ...). The directives are a set of static methods (the same behavior is applied on every engine contained in your application). ### Why adding a configuration to `Directive`/`Scalar`? The Tartiflette DNA is to provide as much as possible an extensible Engine. We decided to base our extensibility on the Directive feature of the GraphQL Specification. It will allow the developers to hook some behaviors at different stages _(build and execution time)_ of the Engine. Here are some interesting features which could be created: * Directive to apply JSON Schema validation on `input` types. * Directive to add monitoring on specific fields * Directive to apply access rules on fields (e.g `@auth`) with **dynamic introspection** which will allow the developer to hide the fields from the introspection. * Directive to map the resolution of a field dirrectly to the result of an AWS Lambda / GCP Function and so one... let your imagination take you away. ### Configuration proposal ```python engine = Engine( sdl, modules=[ "yourapp.query_resolvers", "yourapp.mutation_resolvers", { "name": "tartiflette_external_lib", "config": { "your": "configuration", "foo": { "bar": "baz" } } } ] ) ``` Based on the current `modules` property _(which currently allow **only** string)_, add a new kind of entry with that shape. ```json { "name": "string", "config": "dict" } ``` ### How to deal with the configuration within a third party library? This configuration will helps the tartiflette users to configure the library third party librarythey want to use. For the Tartiflette developers, they will have to handle this configuration within their packages. The idea is to give ability to the tartiflette developers to provide Tartiflette _objects_ _(directives, scalars, resolvers and so on)_ to the community, **easily**. #### Context **Package name**: tartiflette-directive-validators-jsonschema **Package main module name**: tartiflette_directive_validators_jsonschema #### Access the configuration at `bake` time. The `Engine` will guess the method named `bake(schema_name: str, config: dict)` at the root level of the module. **e.g ./tartiflette_directive_validators_jsonschema/__init__.py** ```python from tartiflette import Directive from tartiflette_directive_validators_jsonschema.validate_by_ref import ValidateByRef async def bake(schema_name: str, config: dict) -> str: sdl = """ directive @validateByRef( ref: String! ) on ARGUMENT_DEFINITION """ Directive("validateByRef", schema_name=schema_name)(ValidateByRef(config)) return sdl ``` **e.g ./tartiflette_directive_validators_jsonschema/validate_by_ref.py** ```python class ValidateByRef: def __init__(self, config): # API Key ... # File path ... pass async def on_argument_execution( self, directive_args: Dict[str, Any], next_directive: Callable, argument_definition: "GraphQLArgument", args: Dict[str, Any], ctx: Optional[Dict[str, Any]], info: "Info", ) -> Any: pass ```
2hard
Title: Update Documentation for Flask >= 1.1.0 and Werkzeug >= 0.15.0 Body: > d-kahara commented 2 hours ago • > For anyone that's encountered this issue lately > This has changed > > from werkzeug.contrib.fixers import ProxyFix > app.wsgi_app = ProxyFix(app.wsgi_app) > > This is what you need: > > from werkzeug.middleware.proxy_fix import ProxyFix > app.wsgi_app = ProxyFix(app.wsgi_app, x_proto=1, x_host=1) > > @noirbizarre perhaps this could also be rectified in the todo example? This appears to be a refactor in Werkzeug 0.15.X series. This version is taken by flask >= 1.1.0 We should look at updating our example and documentation, along with compatibility notes. Sidebar, we should also consider locking to more specific versions of dependencies in case of breaking changes (since Flask 1.0.0 came out, and we're allowing >0.8.0. Some big changes happened in there :) )
1medium
Title: High Memory consumption on ASR inferencing Body: ## ❓ Questions and Help #### What is your question? High memory consumption on ASR inferencing on a 16GB RAM server. It used up the system RAM up to 15.67GB and cause the whole server to hang. ![image (1)](https://github.com/facebookresearch/fairseq/assets/51883244/b0e990a0-a5c8-4430-834c-d98955a0b1ce) #### What's your environment? - fairseq Version (e.g., 1.0 or main): main - PyTorch Version (e.g., 1.0) - OS (e.g., Linux): Linux - How you installed fairseq (`pip`, source): source - Build command you used (if compiling from source): ``` cd /path/to/fairseq-py/ python examples/mms/asr/infer/mms_infer.py --model "/path/to/asr/model" --lang lang_code \ --audio "/path/to/audio_1.wav" ``` - Python version: 3.8 - CUDA/cuDNN version: None - GPU models and configuration: None - Any other relevant information: I am using docker.
2hard
Title: 微信发送信息频率上限? Body: # 请问有人知道微信发送信息频率上限是多少吗? 自己的机器人碰到的问题... 希望大家可以来帮助讨论下 先谢过啦 ## 简单介绍下背景: &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;功能上基本上就是群发,且群发的信息对不同人是不一样的。 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;然后希望能够越准时越好(比如元旦,最好就是1月1日00:00发送,微信上貌似就显示到分钟,所以有60s的时间来发送,好友大概120个的样子) &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;当时我做的就是无脑for发送(由于使用nodejs写的,所以所有信息几乎是同时发送的,不会等待前一条发送成功才发送下一条) &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;一直都没有问题,好像是从去年开始,微信开始提示:"发送消息过于频繁,等待对方接受你的好友请求后再发。" ## 原因就是发送消息过于频繁了,于是想到几个解决方案 ### 由于我是用nodejs,所以为了减少并发(同时发送)的数量,则 * 把所有要发送的信息放到一个queue * 等到收到系统收到信息的提示后,再发送下一个 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;_这个做法应该和python发送的过程一样了,都是堵塞(等待发送结果才做决定)的方法, 但是实际上这种方法连续发送60条会被提示(不知道各位有没有用python试验过)_<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;_然后对于这种方法,我尝试过发送60条,休息15s左右,还能发送40条,然后会被提示,用此方法应该可以测试出要多久可以恢复60条?_ ### 直接用js的timeout(或者interval),硬设定间隔发送,每x秒发送一条。 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;_试过1000(也就是1s)没有问题,在500(也就是没0.5s发送一条)的时候,连续发送120条左右就提示错误了_<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;_上述的120条是指给同一用户发送,我试过分成4个,结果是1人上限是30条左右,所以由此推出微信应该限制是发送请求的数量和具体对象是谁无关。_<br> &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;_这个测试中,感觉微信设定指标的条件好像有些模糊,因为在无脑发送(在这边中其实对应的是时间间隔为0),也能发送到60条,而每个0.5s是能发送120条,似乎这边有一个 发送频率-发生数量 的函数在?_ ## 不知道各位有什么想法? ## 关于这个问题的? ## 亦或是关于如何测试出微信限制的规则的? 感激不尽!!!
2hard
Title: DatePickerSingle not compatible with Internet Explorer 11 Body: DatePickerSingle examples from the Dash user guide https://dash.plot.ly/dash-core-components/datepickersingle are not working with Internet Explorer 11 (tested version: 11.175.18362.0 with updates: 11.0.130). A selected date in the calendar won't update the text in the input field. Possible Solution: Regarding this issue https://github.com/airbnb/react-dates/issues/1639, please consider an update of react-dates to version >= 20.2.0
1medium
Title: Schema default value not used Body: Trying to set a default value for a Schema inside of a Parameter. It does not seem to be getting picked up in Swagger when I use the "Try it out" functionality. My schema looks like this: ``` @swagger_auto_schema( operation_id="Get a mission plan", responses={ 200: 'test'}, manual_parameters=[ openapi.Parameter( name='Organization', in_=openapi.IN_HEADER, description="Organization name", required=True, schema=openapi.Schema( type=openapi.TYPE_STRING, default="Organization 1", ) ) ] ) ``` Perhaps providing a more in depth example in testproj, that uses more of the OpenApi parameters, would be helpful. From what I read [here](https://swagger.io/docs/specification/adding-examples/) it seems the example field should be used rather than default, but it does not seem to be an available field in the Schema class?
1medium
Title: New Chrome break the remote_debug? Body: After update to chrome Version 126.0.6478.62, remote_debug in seleniumbase is broken, with WARNING: Unable to get screenshot! <img width="348" alt="image" src="https://github.com/seleniumbase/SeleniumBase/assets/1127820/36f5fe04-7c3e-478b-83c5-4f60d626244a">
1medium
Title: [RFC] Add description text to the fields Body: There will be 2 ways to add a description to a field on the schema first: usign Doc() PEP 727 https://github.com/tiangolo/fastapi/blob/typing-doc/typing_doc.md ```py field: Annotated[str, Doc("This field is important")] ``` The above adds a Docstring to the schema that can be extracted by Dynaconf to generate template files and documentation. --- second: Docstrings, this method is not standardized but has an advantage of being recognized by LSPs ```py field: str """This field is important""" ``` To extract this one and turn into a `Doc` inside the annotated type the following snippet can be used: ```py import inspect import re class Database: host: str """this is a hostname""" port: int """this is port""" def extract_docstrings(cls): source = inspect.getsource(cls) pattern = re.compile(r"(\w+):\s*\w+\n\s*\"\"\"(.*?)\"\"\"", re.DOTALL) docstrings = dict(pattern.findall(source)) return docstrings docstrings = extract_docstrings(Database) for attr, doc in docstrings.items(): print(f"{attr}: {doc}") # Output should be: # host: this is a hostname # port: this is port ```
1medium
Title: lora不和基础模型合并,单独使用PeftModel加载可以吗,两者有区别吗 Body: ### 提交前必须检查以下项目 - [X] 请确保使用的是仓库最新代码(git pull),一些问题已被解决和修复。 - [X] 由于相关依赖频繁更新,请确保按照[Wiki](https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki)中的相关步骤执行 - [X] 我已阅读[FAQ章节](https://github.com/ymcui/Chinese-LLaMA-Alpaca/wiki/常见问题)并且已在Issue中对问题进行了搜索,没有找到相似问题和解决方案 - [X] 第三方插件问题:例如[llama.cpp](https://github.com/ggerganov/llama.cpp)、[text-generation-webui](https://github.com/oobabooga/text-generation-webui)、[LlamaChat](https://github.com/alexrozanski/LlamaChat)等,同时建议到对应的项目中查找解决方案 - [X] 模型正确性检查:务必检查模型的[SHA256.md](https://github.com/ymcui/Chinese-LLaMA-Alpaca/blob/main/SHA256.md),模型不对的情况下无法保证效果和正常运行 ### 问题类型 模型转换和合并 ### 基础模型 Alpaca-Plus-13B ### 操作系统 Linux ### 详细描述问题 我看lora介绍是单独加载一下,而我看到本项目是需要将lora和原模型进行合并后才能使用,这两者有什么区别吗 ### 依赖情况(代码类问题务必提供) 无 ### 运行日志或截图 无
1medium
Title: Proofread topic 4 Body: - Fix issues - Fix typos - Correct the translation where needed - Add images where necessary
0easy
Title: Wait for a socket and an event Body: Hi, Is it possible to wait for both a socket and an event? Something like this: ```python s = socket.socket() e = gevent.event.Event() gevent.wait([s, e]) # Either the socket or the event is ready ``` This code is obviously not valid, but I wonder if there's some trick or workaround to make it work.
1medium
Title: Fix Ivy Failing Test: torch - linalg.adjoint Body: To-do List: https://github.com/unifyai/ivy/issues/27501
2hard
Title: Stuck in filters Body: How to use filters here? If you added some examples it will be helpful. For example if we want to filter user table by first_name, last_name, email or status, How we can achieve?
1medium
Title: docker_network state:absent destroys networks with containers still attached, contrary to the documentation Body: ### Summary When I run a playbook which declares the state of an existing docker_network with connected containers to be absent, I expect the deletion to fail as documented [here](https://docs.ansible.com/ansible/2.9/modules/docker_network_module.html#parameter-state) > If a network has connected containers, it cannot be deleted. Instead the network is deleted leaving the container running but without the network. ### Issue Type Bug Report ### Component Name docker_network ### Ansible Version ```console $ ansible --version ansible [core 2.18.1] config file = None configured module search path = ['/Users/simon/.ansible/plugins/modules', '/usr/share/ansible/plugins/modules'] ansible python module location = /opt/homebrew/Cellar/ansible/11.1.0/libexec/lib/python3.13/site-packages/ansible ansible collection location = /Users/simon/.ansible/collections:/usr/share/ansible/collections executable location = /opt/homebrew/bin/ansible python version = 3.13.1 (main, Dec 3 2024, 17:59:52) [Clang 16.0.0 (clang-1600.0.26.4)] (/opt/homebrew/Cellar/ansible/11.1.0/libexec/bin/python) jinja version = 3.1.4 libyaml = True ``` ### Configuration ```console # if using a version older than ansible-core 2.12 you should omit the '-t all' $ ansible-config dump --only-changed -t all CONFIG_FILE() = None GALAXY_SERVERS: ``` ### OS / Environment MacOS 14.7.1 ### Steps to Reproduce <!--- Paste example playbooks or commands between quotes below --> Playbook 1 ```yaml --- - name: Deploy Nginx in a Docker container hosts: localhost become: true tasks: - name: Create a user-defined Docker network community.docker.docker_network: name: custom_network state: present - name: Deploy an Nginx container community.docker.docker_container: name: nginx_container image: nginx:latest state: started networks: - name: custom_network ports: - "8080:80" - name: Verify the Nginx container is running ansible.builtin.shell: "docker ps | grep nginx_container" register: nginx_status - name: Display the status of the Nginx container ansible.builtin.debug: msg: "{{ nginx_status.stdout_lines }}" - name: Verify the network exists ansible.builtin.shell: "docker network list | grep custom_network" register: network_list - name: Display the network list ansible.builtin.debug: msg: "{{ network_list.stdout_lines }}" ``` Playbook 2 ```yaml - name: Deploy Nginx in a Docker container hosts: localhost become: true tasks: - name: Create a user-defined Docker network community.docker.docker_network: name: custom_network state: absent - name: Verify the Nginx container is running ansible.builtin.shell: "docker ps | grep nginx_container" register: nginx_status - name: Display the status of the Nginx container ansible.builtin.debug: msg: "{{ nginx_status.stdout_lines }}" - name: Verify the network exists ansible.builtin.shell: "docker network list | grep custom_network" register: network_list failed_when: network_list.rc not in [0,1] - name: Display the network list ansible.builtin.debug: msg: "{{ network_list.stdout_lines }}" ``` ### Expected Results I expected `custom_network` to remain in existence after running playbook2, but in fact it is gone. Output below is from playbook 2 only showing it disconnecting the container and deleting the network contrary to the docs. ### Actual Results ```console ansible-playbook [core 2.18.1] config file = None configured module search path = ['/Users/simon/.ansible/plugins/modules', '/usr/share/ansible/plugins/modules'] ansible python module location = /opt/homebrew/Cellar/ansible/11.1.0/libexec/lib/python3.13/site-packages/ansible ansible collection location = /Users/simon/.ansible/collections:/usr/share/ansible/collections executable location = /opt/homebrew/bin/ansible-playbook python version = 3.13.1 (main, Dec 3 2024, 17:59:52) [Clang 16.0.0 (clang-1600.0.26.4)] (/opt/homebrew/Cellar/ansible/11.1.0/libexec/bin/python) jinja version = 3.1.4 libyaml = True No config file found; using defaults BECOME password: setting up inventory plugins Loading collection ansible.builtin from host_list declined parsing /etc/ansible/hosts as it did not pass its verify_file() method Skipping due to inventory source not existing or not being readable by the current user script declined parsing /etc/ansible/hosts as it did not pass its verify_file() method auto declined parsing /etc/ansible/hosts as it did not pass its verify_file() method Skipping due to inventory source not existing or not being readable by the current user yaml declined parsing /etc/ansible/hosts as it did not pass its verify_file() method Skipping due to inventory source not existing or not being readable by the current user ini declined parsing /etc/ansible/hosts as it did not pass its verify_file() method Skipping due to inventory source not existing or not being readable by the current user toml declined parsing /etc/ansible/hosts as it did not pass its verify_file() method [WARNING]: No inventory was parsed, only implicit localhost is available [WARNING]: provided hosts list is empty, only localhost is available. Note that the implicit localhost does not match 'all' Loading collection community.docker from /opt/homebrew/Cellar/ansible/11.1.0/libexec/lib/python3.13/site-packages/ansible_collections/community/docker Loading callback plugin default of type stdout, v2.0 from /opt/homebrew/Cellar/ansible/11.1.0/libexec/lib/python3.13/site-packages/ansible/plugins/callback/default.py Skipping callback 'default', as we already have a stdout callback. Skipping callback 'minimal', as we already have a stdout callback. Skipping callback 'oneline', as we already have a stdout callback. PLAYBOOK: playbook2.yml ************************************************************************************************************************************************************** Positional arguments: playbook2.yml verbosity: 4 connection: ssh become_method: sudo become_ask_pass: True tags: ('all',) inventory: ('/etc/ansible/hosts',) forks: 5 1 plays in playbook2.yml PLAY [Deploy Nginx in a Docker container] ******************************************************************************************************************************************** TASK [Gathering Facts] *************************************************************************************************************************************************************** task path: /Users/simon/source/docker-net-test/playbook2.yml:1 <127.0.0.1> ESTABLISH LOCAL CONNECTION FOR USER: simon <127.0.0.1> EXEC /bin/sh -c 'echo ~simon && sleep 0' <127.0.0.1> EXEC /bin/sh -c '( umask 77 && mkdir -p "` echo /Users/simon/.ansible/tmp `"&& mkdir "` echo /Users/simon/.ansible/tmp/ansible-tmp-1734524728.427339-80135-269737139249987 `" && echo ansible-tmp-1734524728.427339-80135-269737139249987="` echo /Users/simon/.ansible/tmp/ansible-tmp-1734524728.427339-80135-269737139249987 `" ) && sleep 0' Using module file /opt/homebrew/Cellar/ansible/11.1.0/libexec/lib/python3.13/site-packages/ansible/modules/setup.py <127.0.0.1> PUT /Users/simon/.ansible/tmp/ansible-local-80114wwv6suld/tmp6_rh6wfo TO /Users/simon/.ansible/tmp/ansible-tmp-1734524728.427339-80135-269737139249987/AnsiballZ_setup.py <127.0.0.1> EXEC /bin/sh -c 'chmod u+x /Users/simon/.ansible/tmp/ansible-tmp-1734524728.427339-80135-269737139249987/ /Users/simon/.ansible/tmp/ansible-tmp-1734524728.427339-80135-269737139249987/AnsiballZ_setup.py && sleep 0' <127.0.0.1> EXEC /bin/sh -c 'sudo -H -S -p "[sudo via ansible, key=voprbglpsmdpzxuuqzxmnvrkiilabelz] password:" -u root /bin/sh -c '"'"'echo BECOME-SUCCESS-voprbglpsmdpzxuuqzxmnvrkiilabelz ; /opt/homebrew/Cellar/ansible/11.1.0/libexec/bin/python /Users/simon/.ansible/tmp/ansible-tmp-1734524728.427339-80135-269737139249987/AnsiballZ_setup.py'"'"' && sleep 0' <127.0.0.1> EXEC /bin/sh -c 'rm -f -r /Users/simon/.ansible/tmp/ansible-tmp-1734524728.427339-80135-269737139249987/ > /dev/null 2>&1 && sleep 0' ok: [localhost] TASK [Create a user-defined Docker network] ****************************************************************************************************************************************** task path: /Users/simon/source/docker-net-test/playbook2.yml:5 <127.0.0.1> ESTABLISH LOCAL CONNECTION FOR USER: simon <127.0.0.1> EXEC /bin/sh -c 'echo ~simon && sleep 0' <127.0.0.1> EXEC /bin/sh -c '( umask 77 && mkdir -p "` echo /Users/simon/.ansible/tmp `"&& mkdir "` echo /Users/simon/.ansible/tmp/ansible-tmp-1734524731.379621-80176-130326662296446 `" && echo ansible-tmp-1734524731.379621-80176-130326662296446="` echo /Users/simon/.ansible/tmp/ansible-tmp-1734524731.379621-80176-130326662296446 `" ) && sleep 0' Using module file /opt/homebrew/Cellar/ansible/11.1.0/libexec/lib/python3.13/site-packages/ansible_collections/community/docker/plugins/modules/docker_network.py <127.0.0.1> PUT /Users/simon/.ansible/tmp/ansible-local-80114wwv6suld/tmp1pa1la08 TO /Users/simon/.ansible/tmp/ansible-tmp-1734524731.379621-80176-130326662296446/AnsiballZ_docker_network.py <127.0.0.1> EXEC /bin/sh -c 'chmod u+x /Users/simon/.ansible/tmp/ansible-tmp-1734524731.379621-80176-130326662296446/ /Users/simon/.ansible/tmp/ansible-tmp-1734524731.379621-80176-130326662296446/AnsiballZ_docker_network.py && sleep 0' <127.0.0.1> EXEC /bin/sh -c 'sudo -H -S -p "[sudo via ansible, key=abwuehlmpshpuexxxxkrpipbnvllrqge] password:" -u root /bin/sh -c '"'"'echo BECOME-SUCCESS-abwuehlmpshpuexxxxkrpipbnvllrqge ; /opt/homebrew/Cellar/ansible/11.1.0/libexec/bin/python /Users/simon/.ansible/tmp/ansible-tmp-1734524731.379621-80176-130326662296446/AnsiballZ_docker_network.py'"'"' && sleep 0' <127.0.0.1> EXEC /bin/sh -c 'rm -f -r /Users/simon/.ansible/tmp/ansible-tmp-1734524731.379621-80176-130326662296446/ > /dev/null 2>&1 && sleep 0' changed: [localhost] => { "actions": [ "Disconnected container nginx_container", "Removed network custom_network" ], "changed": true, "invocation": { "module_args": { "api_version": "auto", "appends": false, "attachable": null, "ca_path": null, "client_cert": null, "client_key": null, "config_from": null, "config_only": null, "connected": [], "debug": false, "docker_host": "unix:///var/run/docker.sock", "driver": "bridge", "driver_options": {}, "enable_ipv6": null, "force": false, "internal": null, "ipam_config": null, "ipam_driver": null, "ipam_driver_options": null, "labels": {}, "name": "custom_network", "scope": null, "state": "absent", "timeout": 60, "tls": false, "tls_hostname": null, "use_ssh_client": false, "validate_certs": false } } } TASK [Verify the Nginx container is running] ***************************************************************************************************************************************** task path: /Users/simon/source/docker-net-test/playbook2.yml:10 <127.0.0.1> ESTABLISH LOCAL CONNECTION FOR USER: simon <127.0.0.1> EXEC /bin/sh -c 'echo ~simon && sleep 0' <127.0.0.1> EXEC /bin/sh -c '( umask 77 && mkdir -p "` echo /Users/simon/.ansible/tmp `"&& mkdir "` echo /Users/simon/.ansible/tmp/ansible-tmp-1734524732.229014-80201-42969956857922 `" && echo ansible-tmp-1734524732.229014-80201-42969956857922="` echo /Users/simon/.ansible/tmp/ansible-tmp-1734524732.229014-80201-42969956857922 `" ) && sleep 0' Using module file /opt/homebrew/Cellar/ansible/11.1.0/libexec/lib/python3.13/site-packages/ansible/modules/command.py <127.0.0.1> PUT /Users/simon/.ansible/tmp/ansible-local-80114wwv6suld/tmpq8absk6k TO /Users/simon/.ansible/tmp/ansible-tmp-1734524732.229014-80201-42969956857922/AnsiballZ_command.py <127.0.0.1> EXEC /bin/sh -c 'chmod u+x /Users/simon/.ansible/tmp/ansible-tmp-1734524732.229014-80201-42969956857922/ /Users/simon/.ansible/tmp/ansible-tmp-1734524732.229014-80201-42969956857922/AnsiballZ_command.py && sleep 0' <127.0.0.1> EXEC /bin/sh -c 'sudo -H -S -p "[sudo via ansible, key=ddgjsezyvpqdwfppjqtpwvsrdjslddel] password:" -u root /bin/sh -c '"'"'echo BECOME-SUCCESS-ddgjsezyvpqdwfppjqtpwvsrdjslddel ; /opt/homebrew/Cellar/ansible/11.1.0/libexec/bin/python /Users/simon/.ansible/tmp/ansible-tmp-1734524732.229014-80201-42969956857922/AnsiballZ_command.py'"'"' && sleep 0' <127.0.0.1> EXEC /bin/sh -c 'rm -f -r /Users/simon/.ansible/tmp/ansible-tmp-1734524732.229014-80201-42969956857922/ > /dev/null 2>&1 && sleep 0' changed: [localhost] => { "changed": true, "cmd": "docker ps | grep nginx_container", "delta": "0:00:00.055873", "end": "2024-12-18 12:25:32.658854", "invocation": { "module_args": { "_raw_params": "docker ps | grep nginx_container", "_uses_shell": true, "argv": null, "chdir": null, "creates": null, "executable": null, "expand_argument_vars": true, "removes": null, "stdin": null, "stdin_add_newline": true, "strip_empty_ends": true } }, "msg": "", "rc": 0, "start": "2024-12-18 12:25:32.602981", "stderr": "", "stderr_lines": [], "stdout": "362e03085558 nginx:latest \"/docker-entrypoint.…\" 35 minutes ago Up 35 minutes nginx_container", "stdout_lines": [ "362e03085558 nginx:latest \"/docker-entrypoint.…\" 35 minutes ago Up 35 minutes nginx_container" ] } TASK [Display the status of the Nginx container] ************************************************************************************************************************************* task path: /Users/simon/source/docker-net-test/playbook2.yml:14 ok: [localhost] => { "msg": [ "362e03085558 nginx:latest \"/docker-entrypoint.…\" 35 minutes ago Up 35 minutes nginx_container" ] } TASK [Verify the network exists] ***************************************************************************************************************************************************** task path: /Users/simon/source/docker-net-test/playbook2.yml:18 <127.0.0.1> ESTABLISH LOCAL CONNECTION FOR USER: simon <127.0.0.1> EXEC /bin/sh -c 'echo ~simon && sleep 0' <127.0.0.1> EXEC /bin/sh -c '( umask 77 && mkdir -p "` echo /Users/simon/.ansible/tmp `"&& mkdir "` echo /Users/simon/.ansible/tmp/ansible-tmp-1734524732.802664-80227-229173310682829 `" && echo ansible-tmp-1734524732.802664-80227-229173310682829="` echo /Users/simon/.ansible/tmp/ansible-tmp-1734524732.802664-80227-229173310682829 `" ) && sleep 0' Using module file /opt/homebrew/Cellar/ansible/11.1.0/libexec/lib/python3.13/site-packages/ansible/modules/command.py <127.0.0.1> PUT /Users/simon/.ansible/tmp/ansible-local-80114wwv6suld/tmpbuqg9v6l TO /Users/simon/.ansible/tmp/ansible-tmp-1734524732.802664-80227-229173310682829/AnsiballZ_command.py <127.0.0.1> EXEC /bin/sh -c 'chmod u+x /Users/simon/.ansible/tmp/ansible-tmp-1734524732.802664-80227-229173310682829/ /Users/simon/.ansible/tmp/ansible-tmp-1734524732.802664-80227-229173310682829/AnsiballZ_command.py && sleep 0' <127.0.0.1> EXEC /bin/sh -c 'sudo -H -S -p "[sudo via ansible, key=elfdwluorehhbqjdeeolyqgaymsbbrvg] password:" -u root /bin/sh -c '"'"'echo BECOME-SUCCESS-elfdwluorehhbqjdeeolyqgaymsbbrvg ; /opt/homebrew/Cellar/ansible/11.1.0/libexec/bin/python /Users/simon/.ansible/tmp/ansible-tmp-1734524732.802664-80227-229173310682829/AnsiballZ_command.py'"'"' && sleep 0' <127.0.0.1> EXEC /bin/sh -c 'rm -f -r /Users/simon/.ansible/tmp/ansible-tmp-1734524732.802664-80227-229173310682829/ > /dev/null 2>&1 && sleep 0' changed: [localhost] => { "changed": true, "cmd": "docker network list | grep custom_network", "delta": "0:00:00.065006", "end": "2024-12-18 12:25:33.207390", "failed_when_result": false, "invocation": { "module_args": { "_raw_params": "docker network list | grep custom_network", "_uses_shell": true, "argv": null, "chdir": null, "creates": null, "executable": null, "expand_argument_vars": true, "removes": null, "stdin": null, "stdin_add_newline": true, "strip_empty_ends": true } }, "msg": "non-zero return code", "rc": 1, "start": "2024-12-18 12:25:33.142384", "stderr": "", "stderr_lines": [], "stdout": "", "stdout_lines": [] } TASK [Display the network list] ****************************************************************************************************************************************************** task path: /Users/simon/source/docker-net-test/playbook2.yml:23 ok: [localhost] => { "msg": [] } PLAY RECAP *************************************************************************************************************************************************************************** localhost : ok=6 changed=3 unreachable=0 failed=0 skipped=0 rescued=0 ignored=0 ``` ### Code of Conduct - [X] I agree to follow the Ansible Code of Conduct
1medium
Title: dashboard error Body: ## Mycodo Issue Report: - Specific Mycodo Version: 6.08 #### Problem Description Please list: - when i modify the dashboard and add in a graph two value: temp setpoint, temp from ds18b20 ### Errors - List any errors you encountered. - Traceback (most recent call last): File "/home/pi/Mycodo/env/lib/python3.5/site-packages/flask/app.py", line 1982, in wsgi_app response = self.full_dispatch_request() File "/home/pi/Mycodo/env/lib/python3.5/site-packages/flask/app.py", line 1614, in full_dispatch_request rv = self.handle_user_exception(e) File "/home/pi/Mycodo/env/lib/python3.5/site-packages/flask/app.py", line 1517, in handle_user_exception reraise(exc_type, exc_value, tb) File "/home/pi/Mycodo/env/lib/python3.5/site-packages/flask/_compat.py", line 33, in reraise raise value File "/home/pi/Mycodo/env/lib/python3.5/site-packages/flask/app.py", line 1612, in full_dispatch_request rv = self.dispatch_request() File "/home/pi/Mycodo/env/lib/python3.5/site-packages/flask/app.py", line 1598, in dispatch_request return self.view_functions[rule.endpoint](**req.view_args) File "/home/pi/Mycodo/env/lib/python3.5/site-packages/flask_login/utils.py", line 261, in decorated_view return func(*args, **kwargs) File "/home/pi/Mycodo/mycodo/mycodo_flask/routes_page.py", line 400, in page_dashboard y_axes = utils_dashboard.graph_y_axes(dict_measurements) File "/home/pi/Mycodo/mycodo/mycodo_flask/utils/utils_dashboard.py", line 469, in graph_y_axes input_dev) File "/home/pi/Mycodo/mycodo/mycodo_flask/utils/utils_dashboard.py", line 538, in check_func elif each_device.cmd_measurement and each_device.cmd_measurement != '': AttributeError: 'PID' object has no attribute 'cmd_measurement' ### Steps to Reproduce the issue: How can this issue be reproduced? 1. create data for ds18b20 2. create function Pid 3. add to graph : setpoint pid, ds18b20 temp
1medium
Title: show_search not working on gr.Dataframe Body: ### Describe the bug Have gradio 5.14.0, when trying to use show_search='search' paramter for gr.Dataframe(..., getting the error below: TypeError: Dataframe.__init__() got an unexpected keyword argument 'show_search' Other parameters are working. ### Have you searched existing issues? 🔎 - [x] I have searched and found no existing issues ### Reproduction ```python import gradio as gr df_notes = gr.Dataframe(show_search='search', show_fullscreen_button=True, interactive=True, visible=True) ``` ### Screenshot _No response_ ### Logs ```shell ``` ### System Info ```shell 5.14.0 ``` ### Severity I can work around it
1medium
Title: I get OSError: ... is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models' for valid models Body: ### System Info OS: Windows 11 Python: Both 3.11.6 and 3.12.9 Pytorch: Both 2.2.0 and 2.6.0 ### Who can help? _No response_ ### Information - [x] The official example scripts - [ ] My own modified scripts ### Tasks - [x] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...) - [ ] My own task or dataset (give details below) ### Reproduction ``` from transformers import OmDetTurboProcessor, OmDetTurboForObjectDetection processor = OmDetTurboProcessor.from_pretrained("omlab/omdet-turbo-swin-tiny-hf") model = OmDetTurboForObjectDetection.from_pretrained("omlab/omdet-turbo-swin-tiny-hf") ``` I can't reproduce this in colab so i figure it's my system but i can't figure out why. I get this trying to load any model. I also tried rt-detr and got similar errors Full Traceback: ``` Traceback (most recent call last): File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\utils\_http.py", line 406, in hf_raise_for_status response.raise_for_status() File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\requests\models.py", line 1024, in raise_for_status raise HTTPError(http_error_msg, response=self) requests.exceptions.HTTPError: 401 Client Error: Unauthorized for url: https://huggingface.co/omlab/omdet-turbo-swin-tiny-hf/resolve/main/preprocessor_config.json The above exception was the direct cause of the following exception: Traceback (most recent call last): File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\transformers\utils\hub.py", line 403, in cached_file resolved_file = hf_hub_download( ^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\utils\_validators.py", line 114, in _inner_fn return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\file_download.py", line 860, in hf_hub_download return _hf_hub_download_to_cache_dir( ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\file_download.py", line 967, in _hf_hub_download_to_cache_dir _raise_on_head_call_error(head_call_error, force_download, local_files_only) File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\file_download.py", line 1482, in _raise_on_head_call_error raise head_call_error File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\file_download.py", line 1374, in _get_metadata_or_catch_error metadata = get_hf_file_metadata( ^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\utils\_validators.py", line 114, in _inner_fn return fn(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\file_download.py", line 1294, in get_hf_file_metadata r = _request_wrapper( ^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\file_download.py", line 278, in _request_wrapper response = _request_wrapper( ^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\file_download.py", line 302, in _request_wrapper hf_raise_for_status(response) File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\huggingface_hub\utils\_http.py", line 454, in hf_raise_for_status raise _format(RepositoryNotFoundError, message, response) from e huggingface_hub.errors.RepositoryNotFoundError: 401 Client Error. (Request ID: Root=1-67a9034f-3221be180265fb393ff1b352;afb39851-99d5-491d-8d27-f58783b491da) Repository Not Found for url: https://huggingface.co/omlab/omdet-turbo-swin-tiny-hf/resolve/main/preprocessor_config.json. Please make sure you specified the correct `repo_id` and `repo_type`. If you are trying to access a private or gated repo, make sure you are authenticated. Invalid credentials in Authorization header The above exception was the direct cause of the following exception: Traceback (most recent call last): File "C:\Users\obkal\Desktop\cbtest\omdet\detect.py", line 5, in <module> processor = OmDetTurboProcessor.from_pretrained("omlab/omdet-turbo-swin-tiny-hf") ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\transformers\processing_utils.py", line 974, in from_pretrained args = cls._get_arguments_from_pretrained(pretrained_model_name_or_path, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\transformers\processing_utils.py", line 1020, in _get_arguments_from_pretrained args.append(attribute_class.from_pretrained(pretrained_model_name_or_path, **kwargs)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\transformers\image_processing_base.py", line 209, in from_pretrained image_processor_dict, kwargs = cls.get_image_processor_dict(pretrained_model_name_or_path, **kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\transformers\image_processing_base.py", line 341, in get_image_processor_dict resolved_image_processor_file = cached_file( ^^^^^^^^^^^^ File "C:\Users\obkal\Desktop\cbtest\omdet\.venv\Lib\site-packages\transformers\utils\hub.py", line 426, in cached_file raise EnvironmentError( OSError: omlab/omdet-turbo-swin-tiny-hf is not a local folder and is not a valid model identifier listed on 'https://huggingface.co/models' If this is a private repository, make sure to pass a token having permission to this repo either by logging in with `huggingface-cli login` or by passing `token=<your_token>` ```
1medium
Title: Tensorflow Variable Aggregation testing in Keras 3.7.0 Body: Forking this from: https://github.com/keras-team/keras/issues/20568 Specifically tagging @james77777778. tl; dr: It's `SUM`. ------ The recommendation was: > Since there is no reproducible script for debugging, this is a random guess: > Before https://github.com/keras-team/keras/commit/28d39c0cc766767f4db54edc8b8ce68d3a05d4b4, the aggregation behavior might have been broken due to incorrect propagation of the aggregation attr to the variables. Essentially, the training would be an aggregation=None setting (the default value for tf.Variable), which is likely incorrect. > >@das-apratim could you first try training the model without using tf.distribute.MirroredStrategy() to check if any NaNs occur? > >If the training runs without issues, try adding back tf.distribute.MirroredStrategy() and modifying _map_aggregation in keras/src/backend/tensorflow/core.py as follows: mapping = { "none": tf.VariableAggregation.NONE, "sum": tf.VariableAggregation.NONE, "mean": tf.VariableAggregation.NONE, "only_first_replica": tf.VariableAggregation.NONE, } >This adjustment reflects the behavior in Keras 3.6. See if the training runs well with this change. > >If it does, incrementally restore the original mapping to identify which key is causing the issue. Here's a general guideline: > > "sum" is associated with metrics. "mean" is associated with model/optimizer weights. "only_first_replica" is associated with counters. I can make the following report for you: ``` NONE, NONE, NONE, NONE -- okay NONE, SUM, NONE, NONE -- fail, metrics nan first. Regression metrics go inf, "counting" metrics go nan; 123/341 NONE, NONE, MEAN, NONE -- okay NONE, NONE, NONE, FIRST -- okay NONE, NONE, MEAN, FIRST -- okay ``` If it matters at all, this was using a Logical split of an RTX A6000 Ada for testing.
2hard
Title: Noise, wheezing in the output audio Body: Hi! Almost all the output audio that I received had a low voice frequency, and noise could occur in the middle of the voice. On many synthesized audio, the voice had a "hoarseness". As the source audio, I tried many different voices, many of them with a high-pitched voice. What could be the problem? Is this an inaccuracy of the model or my mistake? Thank you in advance for your help!
1medium
Title: [Bug] Deepseek chatChatCompletion has an additional bos in end of the assistant Body: ### Checklist - [x] 1. I have searched related issues but cannot get the expected help. - [x] 2. The bug has not been fixed in the latest version. - [x] 3. Please note that if the bug-related issue you submitted lacks corresponding environment info and a minimal reproducible demo, it will be challenging for us to reproduce and resolve the issue, reducing the likelihood of receiving feedback. - [x] 4. If the issue you raised is not a bug but a question, please raise a discussion at https://github.com/sgl-project/sglang/discussions/new/choose Otherwise, it will be closed. - [x] 5. Please use English, otherwise it will be closed. ### Describe the bug When sglang processes a chat request, if the last role is assistant, it will separate it and do tokenizer.encode separately, and then splice the tokenid. But when I tested deepseek R1, I found that tokenizer.encode adds bos at the beginning of the tokenids by default, which will result in an extra bos after assistant in the final tokenid.like `<|begin▁of▁sentence|><|User|>Tell me a common saying<|Assistant|><|begin▁of▁sentence|>"An apple a day, keeps` Not sure about the tokenizer behavior of other models. Should we remove the first token of tokenizer.encode? ### Reproduction openai_compatible_messages = [ { "role": "user", "content": "Tell me a common saying" }, { "role": "assistant", "content": "\"An apple a day, keeps" } ] ### Environment python3
1medium
Title: mode.val(save_json=True),COCO API AssertionError: Results do not correspond to current coco set. Body: ### Search before asking - [x] I have searched the Ultralytics YOLO [issues](https://github.com/ultralytics/ultralytics/issues) and [discussions](https://github.com/orgs/ultralytics/discussions) and found no similar questions. ### Question trian.py ``` if __name__ == '__main__': from ultralytics import YOLO model = YOLO("yolo11n.pt") # load a pretrained model (recommended for training) model.train(data="coco8.yaml",device=0,batch=-1) ``` yolo2json.py ``` import os import json from PIL import Image # 设置数据集路径 output_dir = "D:\YOLOv11\datasets\coco8" #修改为YOLO格式的数据集路径; dataset_path = "D:\YOLOv11\datasets\coco8" # 修改你想输出的coco格式数据集路径 images_path = os.path.join(dataset_path,"images") labels_path = os.path.join(dataset_path,"labels") # 类别映射 categories = [ {"id": 0, "name": "person"}, {"id": 1, "name": "bicycle"}, {"id": 2, "name": "car"}, {"id": 3, "name": "motorcycle"}, {"id": 4, "name": "airplane"}, {"id": 5, "name": "bus"}, {"id": 6, "name": "train"}, {"id": 7, "name": "truck"}, {"id": 8, "name": "boat"}, {"id": 9, "name": "traffic light"}, {"id": 10, "name": "fire hydrant"}, {"id": 11, "name": "stop sign"}, {"id": 12, "name": "parking meter"}, {"id": 13, "name": "bench"}, {"id": 14, "name": "bird"}, {"id": 15, "name": "cat"}, # 修改这里 {"id": 16, "name": "dog"}, {"id": 17, "name": "horse"}, {"id": 18, "name": "sheep"}, {"id": 19, "name": "cow"}, {"id": 20, "name": "elephant"}, {"id": 21, "name": "bear"}, {"id": 22, "name": "zebra"}, {"id": 23, "name": "giraffe"}, {"id": 24, "name": "backpack"}, {"id": 25, "name": "umbrella"}, {"id": 26, "name": "handbag"}, {"id": 27, "name": "tie"}, {"id": 28, "name": "suitcase"}, {"id": 29, "name": "frisbee"}, {"id": 30, "name": "skis"}, {"id": 31, "name": "snowboard"}, {"id": 32, "name": "sports ball"}, {"id": 33, "name": "kite"}, {"id": 34, "name": "baseball bat"}, {"id": 35, "name": "baseball glove"}, {"id": 36, "name": "skateboard"}, {"id": 37, "name": "surfboard"}, {"id": 38, "name": "tennis racket"}, {"id": 39, "name": "bottle"}, {"id": 40, "name": "wine glass"}, {"id": 41, "name": "cup"}, {"id": 42, "name": "fork"}, {"id": 43, "name": "knife"}, {"id": 44, "name": "spoon"}, {"id": 45, "name": "bowl"}, {"id": 46, "name": "banana"}, {"id": 47, "name": "apple"}, {"id": 48, "name": "sandwich"}, {"id": 49, "name": "orange"}, {"id": 50, "name": "broccoli"}, {"id": 51, "name": "carrot"}, {"id": 52, "name": "hot dog"}, {"id": 53, "name": "pizza"}, {"id": 54, "name": "donut"}, {"id": 55, "name": "cake"}, {"id": 56, "name": "chair"}, {"id": 57, "name": "couch"}, {"id": 58, "name": "potted plant"}, {"id": 59, "name": "bed"}, {"id": 60, "name": "dining table"}, {"id": 61, "name": "toilet"}, {"id": 62, "name": "tv"}, {"id": 63, "name": "laptop"}, {"id": 64, "name": "mouse"}, {"id": 65, "name": "remote"}, {"id": 66, "name": "keyboard"}, {"id": 67, "name": "cell phone"}, {"id": 68, "name": "microwave"}, {"id": 69, "name": "oven"}, {"id": 70, "name": "toaster"}, {"id": 71, "name": "sink"}, {"id": 72, "name": "refrigerator"}, {"id": 73, "name": "book"}, {"id": 74, "name": "clock"}, {"id": 75, "name": "vase"}, {"id": 76, "name": "scissors"}, {"id": 77, "name": "teddy bear"}, {"id": 78, "name": "hair drier"}, {"id": 79, "name": "toothbrush"} ] # YOLO格式转COCO格式的函数 def convert_yolo_to_coco(x_center, y_center, width, height, img_width, img_height): x_min = (x_center - width / 2) * img_width y_min = (y_center - height / 2) * img_height width = width * img_width height = height * img_height return [x_min, y_min, width, height] # 初始化COCO数据结构 def init_coco_format(): return { "images": [], "annotations": [], "categories": categories } # 处理每个数据集分区 for split in ['train', 'val']: #'test' coco_format = init_coco_format() annotation_id = 1 for img_name in os.listdir(os.path.join(images_path, split)): if img_name.lower().endswith(('.png', '.jpg', '.jpeg')): img_path = os.path.join(images_path, split, img_name) label_path = os.path.join(labels_path, split, img_name.replace("jpg", "txt")) img = Image.open(img_path) img_width, img_height = img.size image_info = { "file_name": img_name, "id": len(coco_format["images"]) + 1, "width": img_width, "height": img_height } coco_format["images"].append(image_info) if os.path.exists(label_path): with open(label_path, "r") as file: for line in file: category_id, x_center, y_center, width, height = map(float, line.split()) bbox = convert_yolo_to_coco(x_center, y_center, width, height, img_width, img_height) annotation = { "id": annotation_id, "image_id": image_info["id"], "category_id": int(category_id) + 1, "bbox": bbox, "area": bbox[2] * bbox[3], "iscrowd": 0 } coco_format["annotations"].append(annotation) annotation_id += 1 # 为每个分区保存JSON文件 with open(os.path.join(output_dir, f"{split}_coco_format.json"), "w") as json_file: json.dump(coco_format, json_file, indent=4) ``` vail.py ``` if __name__ == '__main__': from ultralytics import YOLO from pycocotools.coco import COCO from pycocotools.cocoeval import COCOeval model = YOLO("runs/detect/train11/weights/best.pt") # load a pretrained model (recommended for training) results=model.val(data="coco8.yaml",save_json=True,device=0,batch=1) anno = COCO("D:/YOLOv11/datasets/coco8/val_coco_format.json") # Load your JSON annotations pred = anno.loadRes(f"{results.save_dir}/predictions.json") # Load predictions.json val = COCOeval(anno, pred, "bbox") val.evaluate() val.accumulate() val.summarize() ``` vail.py 报错 ``` (yolov11) D:\YOLOv11>python vail.py Ultralytics 8.3.18 🚀 Python-3.11.7 torch-2.6.0+cu126 CUDA:0 (NVIDIA GeForce RTX 4060 Ti, 16380MiB) YOLO11n summary (fused): 238 layers, 2,616,248 parameters, 0 gradients, 6.5 GFLOPs val: Scanning D:\YOLOv11\datasets\coco8\labels\val.cache... 4 images, 0 backgrounds, 0 corrupt: 100%|██████████| 4/4 [00:00<?, ?it/s] Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 4/4 [00:01<00:00, 2.88it/s] all 4 17 0.802 0.66 0.864 0.593 person 3 10 0.82 0.461 0.695 0.347 dog 1 1 0.707 1 0.995 0.697 horse 1 2 0.835 1 0.995 0.473 elephant 1 2 0.779 0.5 0.508 0.153 umbrella 1 1 0.669 1 0.995 0.995 potted plant 1 1 1 0 0.995 0.895 Speed: 2.2ms preprocess, 26.6ms inference, 0.0ms loss, 14.8ms postprocess per image Saving runs\detect\val18\predictions.json... Results saved to runs\detect\val18 loading annotations into memory... Done (t=0.00s) creating index... index created! Loading and preparing results... Traceback (most recent call last): File "D:\YOLOv11\vail.py", line 56, in <module> pred = anno.loadRes(f"{results.save_dir}/predictions.json") # Load predictions.json ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\ProgramData\anaconda3\Lib\site-packages\pycocotools\coco.py", line 327, in loadRes assert set(annsImgIds) == (set(annsImgIds) & set(self.getImgIds())), \ ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ AssertionError: Results do not correspond to current coco set ``` ### Additional I don't know why there's an error
1medium
Title: Numpy 1.22.0 and 1.24.3 Problem with TTS 0.22.0 and Librosa 0.10.0 and 0.10.1 Body: Hello everyone, I'm working as a scientistic assistance on Linux and we had a compatibility problem with TTS 0.22.0, Librosa 0.10.0 and Numpy 1.22.0 after an TTS Update from 0.11.0 to 0.22.0. With these updates we got the following traceback: ``` Traceback (most recent call last): File "/project/translate_lecture.py", line 195, in <module> main( File "/project/translate_lecture.py", line 96, in main speaker.speak(use_gpu=use_cuda) File "/project/src/speaker.py", line 49, in speak self._add_text(segment=segment, use_gpu=use_gpu) File "/project/src/speaker.py", line 110, in _add_text file_handler.adjust_audio_length( File "/project/utils/file_handler.py", line 122, in adjust_audio_length short_y = librosa.effects.time_stretch(y=y, rate=factor) File "/opt/conda/lib/python3.10/site-packages/librosa/effects.py", line 245, in time_stretch stft_stretch = core.phase_vocoder( File "/opt/conda/lib/python3.10/site-packages/librosa/core/spectrum.py", line 1457, in phase_vocoder d_stretch[..., t] = util.phasor(phase_acc, mag=mag) File "/opt/conda/lib/python3.10/site-packages/librosa/util/utils.py", line 2602, in phasor z = _phasor_angles(angles) File "/opt/conda/lib/python3.10/site-packages/numba/np/ufunc/dufunc.py", line 190, in __call__ return super().__call__(*args, **kws) numpy.core._exceptions._UFuncNoLoopError: ufunc '_phasor_angles' did not contain a loop with signature matching types <class 'numpy.dtype[float32]'> -> None ``` After this I was looking inside of the requirements of TTS 0.22.0 to search for the numpy compatibility: ``` # core deps numpy==1.22.0;python_version<="3.10" numpy>=1.24.3;python_version>"3.10" librosa>=0.10.0 ... ``` and Librosa 0.10.1: ``` install_requires = audioread >= 2.1.9 numpy >= 1.20.3, != 1.22.0, != 1.22.1, != 1.22.2 ... ``` With this knowledge I updated from python 3.10 (uninstalled) to python 3.11 and defined ``numpy==1.24.3`` in our requirements, because I thought it needs the next higher compatible version, as read in the TTS requirements. But, while building, the compiler said: ``` #17 12.18 The conflict is caused by: #17 12.18 The user requested numpy==1.24.3 #17 12.18 tts 0.22.0 depends on numpy==1.22.0; python_version <= "3.10" #17 12.18 ``` I already tried to install numpy, librosa and tts without an version tag, but I got again the 1.22.0 numpy version with librosa 0.10.0 and tts 0.22.0 with the error at the beginning. Why does the compiler stops at the first requirement validation and doesn't run through to the next one? Does anyone has an idea to fix it? install python 3.10 and 3.11? _Originally posted by @OrbitPeppermint in https://github.com/coqui-ai/TTS/discussions/3537_
2hard