listen2you003 commited on
Commit
e74c01b
Β·
1 Parent(s): e9ed143

return to old version

Browse files
README.md CHANGED
@@ -3,7 +3,7 @@ title: Test
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  emoji: πŸš€
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  colorFrom: indigo
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  colorTo: pink
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- sdk: docker
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  app_file: app.py
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  pinned: false
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  license: mit
 
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  emoji: πŸš€
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  colorFrom: indigo
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  colorTo: pink
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+ sdk: gradio
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  app_file: app.py
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  pinned: false
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  license: mit
modules/__pycache__/__init__.cpython-310.pyc CHANGED
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modules/__pycache__/attention.cpython-310.pyc CHANGED
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modules/__pycache__/autoencoder.cpython-310.pyc CHANGED
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modules/__pycache__/conditioner.cpython-310.pyc CHANGED
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modules/__pycache__/connector_edit.cpython-310.pyc CHANGED
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modules/__pycache__/layers.cpython-310.pyc CHANGED
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modules/__pycache__/model_edit.cpython-310.pyc CHANGED
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modules/attention.py CHANGED
@@ -43,7 +43,7 @@ def attention(
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  q,
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  k,
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  v,
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- mode="flash",
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  drop_rate=0,
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  attn_mask=None,
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  causal=False,
 
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  q,
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  k,
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  v,
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+ mode="torch",
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  drop_rate=0,
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  attn_mask=None,
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  causal=False,
modules/conditioner.py CHANGED
@@ -73,7 +73,7 @@ class Qwen25VL_7b_Embedder(torch.nn.Module):
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  self.model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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  model_path,
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  torch_dtype=dtype,
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- attn_implementation="flash_attention_2",
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  ).to(torch.cuda.current_device())
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  self.model.requires_grad_(False)
 
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  self.model = Qwen2_5_VLForConditionalGeneration.from_pretrained(
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  model_path,
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  torch_dtype=dtype,
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+ attn_implementation="eager",
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  ).to(torch.cuda.current_device())
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  self.model.requires_grad_(False)
modules/layers.py CHANGED
@@ -24,7 +24,7 @@ from functools import partial
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  import torch
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  import torch.nn.functional as F
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  from einops import rearrange
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- from liger_kernel.ops.rms_norm import LigerRMSNormFunction
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  from torch import Tensor, nn
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@@ -60,7 +60,7 @@ def attention(
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  q,
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  k,
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  v,
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- mode="flash",
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  drop_rate=0,
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  attn_mask=None,
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  causal=False,
@@ -436,16 +436,16 @@ class RMSNorm(torch.nn.Module):
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  super().__init__()
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  self.scale = nn.Parameter(torch.ones(dim))
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- @staticmethod
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- def rms_norm_fast(x, weight, eps):
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- return LigerRMSNormFunction.apply(
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- x,
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- weight,
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- eps,
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- 0.0,
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- "gemma",
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- True,
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- )
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450
  @staticmethod
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  def rms_norm(x, weight, eps):
@@ -455,7 +455,8 @@ class RMSNorm(torch.nn.Module):
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  return (x * rrms).to(dtype=x_dtype) * weight
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  def forward(self, x: Tensor):
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- return self.rms_norm_fast(x, self.scale, 1e-6)
 
459
 
460
 
461
  class QKNorm(torch.nn.Module):
 
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  import torch
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  import torch.nn.functional as F
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  from einops import rearrange
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+ # from liger_kernel.ops.rms_norm import LigerRMSNormFunction
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  from torch import Tensor, nn
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60
  q,
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  k,
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  v,
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+ mode="torch",
64
  drop_rate=0,
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  attn_mask=None,
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  causal=False,
 
436
  super().__init__()
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  self.scale = nn.Parameter(torch.ones(dim))
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+ # @staticmethod
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+ # def rms_norm_fast(x, weight, eps):
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+ # return LigerRMSNormFunction.apply(
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+ # x,
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+ # weight,
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+ # eps,
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+ # 0.0,
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+ # "gemma",
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+ # True,
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+ # )
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450
  @staticmethod
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  def rms_norm(x, weight, eps):
 
455
  return (x * rrms).to(dtype=x_dtype) * weight
456
 
457
  def forward(self, x: Tensor):
458
+ # return self.rms_norm_fast(x, self.scale, 1e-6)
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+ return self.rms_norm(x, self.scale, 1e-6)
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461
 
462
  class QKNorm(torch.nn.Module):
requirements.txt CHANGED
@@ -1,8 +1,12 @@
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- torch==2.3.1
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- liger_kernel==0.5.4
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- einops==0.8.1
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  transformers==4.49.0
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  qwen_vl_utils==0.0.10
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  safetensors==0.4.5
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  pillow==11.1.0
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- huggingface_hub
 
 
 
 
 
 
 
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+ einops
 
 
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  transformers==4.49.0
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  qwen_vl_utils==0.0.10
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  safetensors==0.4.5
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  pillow==11.1.0
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+ huggingface_hub
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+ transformers
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+ diffusers
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+ peft
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+ opencv-python
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+ sentencepiece
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+ boto3