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https://github.com/brycedrennan/imaginAIry
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build: remove fairscale dependency (#441)
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@ -12,7 +12,6 @@ from functools import partial
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import torch
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import torch.nn as nn
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from fairscale.nn.checkpoint.checkpoint_activations import checkpoint_wrapper
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from timm.models.helpers import adapt_input_conv
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from timm.models.layers import DropPath, trunc_normal_
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from timm.models.vision_transformer import PatchEmbed
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@ -144,8 +143,7 @@ class Block(nn.Module):
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)
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if use_grad_checkpointing:
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self.attn = checkpoint_wrapper(self.attn)
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self.mlp = checkpoint_wrapper(self.mlp)
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raise RuntimeError("not supported")
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def forward(self, x, register_hook=False):
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x = x + self.drop_path(self.attn(self.norm1(x), register_hook=register_hook))
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@ -45,8 +45,6 @@ exceptiongroup==1.2.0
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# pytest
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facexlib==0.3.0
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# via imaginAIry (setup.py)
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fairscale==0.4.13
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# via imaginAIry (setup.py)
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fastapi==0.108.0
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# via imaginAIry (setup.py)
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filelock==3.13.1
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@ -125,7 +123,6 @@ numpy==1.24.4
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# contourpy
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# diffusers
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# facexlib
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# fairscale
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# filterpy
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# imageio
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# imaginAIry (setup.py)
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@ -255,7 +252,6 @@ tomli==2.0.1
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torch==2.1.2
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# via
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# facexlib
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# fairscale
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# imaginAIry (setup.py)
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# kornia
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# open-clip-torch
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