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Update init_values const for 24 and 36 layer ResMLP models

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This commit is contained in:
Ross Wightman 2021-06-07 17:15:04 -07:00
parent 8e4ac3549f
commit 2f5ed2dec1
1 changed files with 4 additions and 2 deletions
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6
timm/models/mlp_mixer.py
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@ -422,7 +422,8 @@ def resmlp_24_224(pretrained=False, **kwargs):
Paper: `ResMLP: Feedforward networks for image classification...` - https://arxiv.org/abs/2105.03404
"""
model_args = dict(
patch_size=16, num_blocks=24, hidden_dim=384, mlp_ratio=4, block_layer=ResBlock, norm_layer=Affine, **kwargs)
patch_size=16, num_blocks=24, hidden_dim=384, mlp_ratio=4,
block_layer=partial(ResBlock, init_values=1e-5), norm_layer=Affine, **kwargs)
model = _create_mixer('resmlp_24_224', pretrained=pretrained, **model_args)
return model
@ -433,7 +434,8 @@ def resmlp_36_224(pretrained=False, **kwargs):
Paper: `ResMLP: Feedforward networks for image classification...` - https://arxiv.org/abs/2105.03404
"""
model_args = dict(
patch_size=16, num_blocks=36, hidden_dim=384, mlp_ratio=4, block_layer=ResBlock, norm_layer=Affine, **kwargs)
patch_size=16, num_blocks=36, hidden_dim=384, mlp_ratio=4,
block_layer=partial(ResBlock, init_values=1e-5), norm_layer=Affine, **kwargs)
model = _create_mixer('resmlp_36_224', pretrained=pretrained, **model_args)
return model