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try modify swin

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thanhvc3 2024-04-29 18:28:08 +07:00
parent a8ac4d1b3f
commit 2b6e356e60
1 changed files with 4 additions and 4 deletions
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8
models.py
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@ -532,9 +532,9 @@ class FouriER(torch.nn.Module):
self.patch_embed = PatchEmbed(in_chans=channels, patch_size=self.p.patch_size, self.patch_embed = PatchEmbed(in_chans=channels, patch_size=self.p.patch_size,
embed_dim=self.p.embed_dim, stride=4, padding=2) embed_dim=self.p.embed_dim, stride=4, padding=2)
network = [] network = []
layers = [2, 2, 6, 2] layers = [4, 4, 12, 4]
embed_dims = [self.p.embed_dim, 320, 256, 128] embed_dims = [self.p.embed_dim, 128, 320, 128]
mlp_ratios = [4, 4, 8, 12] mlp_ratios = [4, 4, 4, 4]
num_heads = [2, 4, 8, 16] num_heads = [2, 4, 8, 16]
downsamples = [True, True, True, True] downsamples = [True, True, True, True]
pool_size=3 pool_size=3
@ -949,7 +949,7 @@ class PoolFormerBlock(nn.Module):
self.window_size = window_size self.window_size = window_size
self.shift_size = shift_size self.shift_size = shift_size
self.input_resolution = input_resolution self.input_resolution = input_resolution
self.token_mixer = WindowAttention(dim=dim, window_size=to_2tuple(self.window_size), num_heads=num_heads, attn_drop=0.1, proj_drop=0.2) self.token_mixer = WindowAttention(dim=dim, window_size=to_2tuple(self.window_size), num_heads=num_heads)
self.norm2 = norm_layer(dim) self.norm2 = norm_layer(dim)
mlp_hidden_dim = int(dim * mlp_ratio) mlp_hidden_dim = int(dim * mlp_ratio)
self.mlp = Mlp(in_features=dim, hidden_features=mlp_hidden_dim, self.mlp = Mlp(in_features=dim, hidden_features=mlp_hidden_dim,