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thanhvc3 2024-04-27 10:32:08 +07:00
parent 63ccb4ec75
commit 22d44d1a99
1 changed files with 2 additions and 1 deletions
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models.py
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@ -786,6 +786,7 @@ class WindowAttention(nn.Module):
x: input features with shape of (num_windows*B, N, C) x: input features with shape of (num_windows*B, N, C)
mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh*Ww) or None mask: (0/-inf) mask with shape of (num_windows, Wh*Ww, Wh*Ww) or None
""" """
print(x.shape)
B_, N, C = x.shape B_, N, C = x.shape
qkv_bias = None qkv_bias = None
if self.q_bias is not None: if self.q_bias is not None:
@ -862,7 +863,7 @@ class PoolFormerBlock(nn.Module):
self.norm1 = norm_layer(dim) self.norm1 = norm_layer(dim)
#self.token_mixer = Pooling(pool_size=pool_size) #self.token_mixer = Pooling(pool_size=pool_size)
# self.token_mixer = FNetBlock() # self.token_mixer = FNetBlock()
self.token_mixer = WindowAttention(dim=dim, window_size=to_2tuple(7), num_heads=1, pretrained_window_size=[5,5]) self.token_mixer = WindowAttention(dim=dim, window_size=to_2tuple(7), num_heads=10, pretrained_window_size=[5,5])
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,