Spaces:
Running
Running
Fix minor mistakes, tidy up demos.
Browse files- examples/Image processing.lynxkite.json +172 -152
- examples/Model use.lynxkite.json +421 -339
- examples/NetworkX demo.lynxkite.json +0 -0
- examples/Word2vec.lynxkite.json +0 -0
- lynxkite-graph-analytics/src/lynxkite_graph_analytics/ml_ops.py +1 -7
- lynxkite-pillow-example/src/lynxkite_pillow_example/__init__.py +1 -1
examples/Image processing.lynxkite.json
CHANGED
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@@ -1,284 +1,304 @@
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{
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"env": "Pillow",
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"nodes": [
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{
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"id": "Open image 1",
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"type": "basic",
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"data": {
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"
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"
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"filename": "https://media.licdn.com/dms/image/v2/C4E03AQEq4tdJKQiNHQ/profile-displayphoto-shrink_200_200/profile-displayphoto-shrink_200_200/0/1657270040827?e=2147483647&v=beta&t=lDxix0_0-_K7NUFqgPdzxY5-P7f73bWpPS_XRre842c"
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},
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"display": null,
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"error": null,
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"meta": {
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"outputs": {
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"output": {
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"name": "output",
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"type": {
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"type": "None"
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}
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"position": "right"
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}
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},
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"name": "Open image",
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"inputs": {},
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"params": {
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"filename": {
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"name": "filename",
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"type": {
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"type": "<class 'str'>"
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}
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"default": null
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}
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},
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"type": "basic"
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},
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"
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},
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"position": {
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"x": -316.51795927908694,
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"y": 122.80901061526373
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},
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"
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"
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"height": 222.0
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},
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{
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"id": "View image 1",
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"type": "image",
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"data": {
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"title": "View image",
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"params": {},
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"display": "data:image/jpeg;base64,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",
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"error": null,
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"meta": {
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-
"type": "image",
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"outputs": {},
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"inputs": {
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"image": {
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"name": "image",
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"type": {
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"type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
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}
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"position": "left"
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}
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},
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"name": "View image",
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"
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},
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"position": {
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"x": 371.2152385614552,
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"y": -243.68185336918702
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},
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"
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"width": 265.0
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"height": 288.0
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},
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{
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"id": "Flip verically 1",
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"type": "basic",
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"data": {
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"
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"
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"display": null,
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"error": null,
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"meta": {
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"outputs": {
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"output": {
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-
"position": "right",
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"name": "output",
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"type": {
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"type": "None"
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}
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}
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},
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"type": "basic",
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"params": {},
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"
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"inputs": {
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"image": {
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"name": "image",
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"position": "left",
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"type": {
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"type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
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}
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}
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}
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},
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"
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},
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"position": {
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"x": 228.3853393986406,
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"y": 245.68255477059915
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},
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"
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"
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"height": 200.0
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},
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{
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"id": "View image 2",
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"type": "image",
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"data": {
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| 126 |
-
"title": "View image",
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"params": {},
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| 128 |
"display": "data:image/jpeg;base64,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",
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"error": null,
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"meta": {
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"outputs": {},
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"inputs": {
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"image": {
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"position": "left",
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"type": {
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"type": "<module 'PIL.Image' from '/media/nvme/darabos/lynxkite-2024/.venv/lib/python3.11/site-packages/PIL/Image.py'>"
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-
}
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"name": "image"
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}
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},
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"name": "View image",
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"params": {},
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"type": "image"
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}
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},
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"position": {
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{
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"id": "To grayscale 1",
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"data": {
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"name": "output"
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"name": "To grayscale",
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"inputs": {
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"image": {
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"position": "left",
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examples/Model use.lynxkite.json
CHANGED
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| 1496 |
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| 1497 |
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| 1498 |
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| 1499 |
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1.
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| 1500 |
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| 1501 |
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| 1502 |
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| 1503 |
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| 1504 |
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| 1505 |
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| 1506 |
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| 1507 |
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| 1508 |
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| 1509 |
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| 1510 |
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| 1511 |
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| 1513 |
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|
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|
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|
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|
| 1532 |
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|
| 1533 |
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|
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|
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|
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|
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"model": "ModelConfig(model=Sequential(\n (0) - Identity(): Input__tensor_1_output -> START_Repeat_1_output\n (1) - Linear(4, 4, bias=True): START_Repeat_1_output -> Linear_1_output\n (2) - <function leaky_relu at 0x7a324738f100>: Linear_1_output -> Activation_1_output\n (3) - Identity(): Activation_1_output -> START_Repeat_1_output\n (4) - Linear(4, 4, bias=True): START_Repeat_1_output -> Linear_1_output\n (5) - <function leaky_relu at 0x7a324738f100>: Linear_1_output -> Activation_1_output\n (6) - Identity(): Activation_1_output -> END_Repeat_1_output\n (7) - Identity(): END_Repeat_1_output -> Output_1_x\n (8) - Identity(): Output_1_x -> Output_1_x\n), model_inputs=['Input__tensor_1_output'], model_outputs=['Output_1_x'], loss_inputs=['Input__tensor_3_output', 'Output_1_x'], loss=Sequential(\n (0) - <function constant_vector.<locals>.<lambda> at 0x7a3012b563e0>: nothing -> Constant_vector_1_output\n (1) - <built-in method add of type object at 0x7a324399ef00>: Input__tensor_3_output, Constant_vector_1_output -> Add_1_output\n (2) - <function mse_loss at 0x7a3247398c20>: Output_1_x, Add_1_output -> MSE_loss_2_output\n (3) - Identity(): MSE_loss_2_output -> loss\n), optimizer_parameters={'lr': 0.1, 'type': <OptionsFor_type.SGD: 4>}, optimizer=SGD (\nParameter Group 0\n dampening: 0\n differentiable: False\n foreach: None\n fused: None\n lr: 0.1\n maximize: False\n momentum: 0\n nesterov: False\n weight_decay: 0\n), source_workspace='Model definition.lynxkite.json', trained=True)"
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"canberra",
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},
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"default": "nodes",
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"name": "table_name",
|
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}
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}
|
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},
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"type": "visualization"
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"params": {
|
examples/NetworkX demo.lynxkite.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
examples/Word2vec.lynxkite.json
CHANGED
|
The diff for this file is too large to render.
See raw diff
|
|
|
lynxkite-graph-analytics/src/lynxkite_graph_analytics/ml_ops.py
CHANGED
|
@@ -36,8 +36,7 @@ def define_model(
|
|
| 36 |
):
|
| 37 |
"""Trains the selected model on the selected dataset. Most training parameters are set in the model definition."""
|
| 38 |
assert model_workspace, "Model workspace is unset."
|
| 39 |
-
ws = load_ws(model_workspace)
|
| 40 |
-
# Build the model without inputs, to get its interface.
|
| 41 |
m = pytorch_core.build_model(ws)
|
| 42 |
m.source_workspace = model_workspace
|
| 43 |
bundle = bundle.copy()
|
|
@@ -136,11 +135,6 @@ def view_loss(bundle: core.Bundle):
|
|
| 136 |
return v
|
| 137 |
|
| 138 |
|
| 139 |
-
@op("Reduce dimensions")
|
| 140 |
-
def reduce_dimensions(bundle: core.Bundle):
|
| 141 |
-
return
|
| 142 |
-
|
| 143 |
-
|
| 144 |
VIRIDIS = [
|
| 145 |
"#440154",
|
| 146 |
"#482777",
|
|
|
|
| 36 |
):
|
| 37 |
"""Trains the selected model on the selected dataset. Most training parameters are set in the model definition."""
|
| 38 |
assert model_workspace, "Model workspace is unset."
|
| 39 |
+
ws = load_ws(model_workspace + ".lynxkite.json")
|
|
|
|
| 40 |
m = pytorch_core.build_model(ws)
|
| 41 |
m.source_workspace = model_workspace
|
| 42 |
bundle = bundle.copy()
|
|
|
|
| 135 |
return v
|
| 136 |
|
| 137 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 138 |
VIRIDIS = [
|
| 139 |
"#440154",
|
| 140 |
"#482777",
|
lynxkite-pillow-example/src/lynxkite_pillow_example/__init__.py
CHANGED
|
@@ -35,7 +35,7 @@ def flip_horizontally(image: Image):
|
|
| 35 |
return image.transpose(Image.Transpose.FLIP_LEFT_RIGHT)
|
| 36 |
|
| 37 |
|
| 38 |
-
@op("Flip
|
| 39 |
def flip_vertically(image: Image):
|
| 40 |
return image.transpose(Image.Transpose.FLIP_TOP_BOTTOM)
|
| 41 |
|
|
|
|
| 35 |
return image.transpose(Image.Transpose.FLIP_LEFT_RIGHT)
|
| 36 |
|
| 37 |
|
| 38 |
+
@op("Flip vertically")
|
| 39 |
def flip_vertically(image: Image):
|
| 40 |
return image.transpose(Image.Transpose.FLIP_TOP_BOTTOM)
|
| 41 |
|