From 285b3bcaa907fea27dca169896057d9b6ef52a2a Mon Sep 17 00:00:00 2001 From: Phil Wang Date: Wed, 5 May 2021 09:44:15 -0700 Subject: [PATCH] add dropout and diagram --- README.md | 2 ++ mlp-mixer.png | Bin 0 -> 104525 bytes mlp_mixer_pytorch/mlp_mixer_pytorch.py | 12 +++++++----- setup.py | 2 +- 4 files changed, 10 insertions(+), 6 deletions(-) create mode 100644 mlp-mixer.png diff --git a/README.md b/README.md index c2229b9..cd637f8 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,5 @@ + + ## MLP Mixer - Pytorch An All-MLP solution for Vision, from Google AI, in Pytorch. diff --git a/mlp-mixer.png b/mlp-mixer.png new file mode 100644 index 0000000000000000000000000000000000000000..39542568250c19ea990ea1a40ed894f7c8ccfbcd GIT binary patch literal 104525 zcma&OcRZKv|2O`&QV5kwMl>#oGBP3~yArZDWt6>VQZ_AA(jYs^CL=^C6Spj zGrFJW_4#~%zx%%by06FexUS~;exJvA9Iw}Nz0OT@GG08G-mi8rJLM2?XCF7cdO-1{CuCgqQ1M9(-n6wGuO)`D@P}X%g5a;TrXdC zbhCDHpQEUhCXqNv=M-eMy`N3TdC4$!FEvya#0|!Bs@^-u$)k8%?wECql7&jXLiiu^ 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U>G~l90RR9107*qoM6N<$f^c;V8UO$Q literal 0 HcmV?d00001 diff --git a/mlp_mixer_pytorch/mlp_mixer_pytorch.py b/mlp_mixer_pytorch/mlp_mixer_pytorch.py index 417ce23..5014e48 100644 --- a/mlp_mixer_pytorch/mlp_mixer_pytorch.py +++ b/mlp_mixer_pytorch/mlp_mixer_pytorch.py @@ -10,14 +10,16 @@ def __init__(self, dim, fn): def forward(self, x): return self.fn(self.norm(x)) + x -def FeedForward(dim, expansion_factor = 4): +def FeedForward(dim, expansion_factor = 4, dropout = 0.): return nn.Sequential( nn.Linear(dim, dim * expansion_factor), nn.GELU(), - nn.Linear(dim * expansion_factor, dim) + nn.Dropout(dropout), + nn.Linear(dim * expansion_factor, dim), + nn.Dropout(dropout) ) -def MLPMixer(*, image_size, patch_size, dim, depth, num_classes, expansion_factor = 4): +def MLPMixer(*, image_size, patch_size, dim, depth, num_classes, expansion_factor = 4, dropout = 0.): assert (image_size % patch_size) == 0, 'image must be divisible by patch size' num_patches = (image_size // patch_size) ** 2 @@ -27,10 +29,10 @@ def MLPMixer(*, image_size, patch_size, dim, depth, num_classes, expansion_facto *[nn.Sequential( PreNormResidual(dim, nn.Sequential( Rearrange('b n c -> b c n'), - FeedForward(num_patches, expansion_factor), + FeedForward(num_patches, expansion_factor, dropout), Rearrange('b c n -> b n c'), )), - PreNormResidual(dim, FeedForward(dim, expansion_factor)) + PreNormResidual(dim, FeedForward(dim, expansion_factor, dropout)) ) for _ in range(depth)], nn.LayerNorm(dim), Rearrange('b n c -> b c n'), diff --git a/setup.py b/setup.py index fb4acb2..9346cf5 100644 --- a/setup.py +++ b/setup.py @@ -3,7 +3,7 @@ setup( name = 'mlp-mixer-pytorch', packages = find_packages(exclude=[]), - version = '0.0.2', + version = '0.0.3', license='MIT', description = 'MLP Mixer - Pytorch', author = 'Phil Wang',