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Update tnt.py

pull/1000/head
cuicheng01 2021-07-01 03:37:42 +00:00
parent 03a3da164b
commit a6420f1cce
1 changed files with 24 additions and 17 deletions
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41
ppcls/arch/backbone/model_zoo/tnt.py
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@ -44,7 +44,7 @@ def drop_path(x, drop_prob=0., training=False):
return x
keep_prob = paddle.to_tensor(1 - drop_prob)
shape = (paddle.shape(x)[0], ) + (1, ) * (x.ndim - 1)
random_tensor = paddle.add(keep_prob, paddle.rand(shape, dtype=x.dtype))
random_tensor = paddle.add(keep_prob, paddle.rand(shape, dtype=x.dtype))
random_tensor = paddle.floor(random_tensor) # binarize
output = x.divide(keep_prob) * random_tensor
return output
@ -114,15 +114,17 @@ class Attention(nn.Layer):
(2, 0, 3, 1, 4))
q, k = qk[0], qk[1]
v = self.v(x).reshape((B, N, self.num_heads, x.shape[-1] // self.num_heads)).transpose(
(0, 2, 1, 3))
v = self.v(x).reshape(
(B, N, self.num_heads, x.shape[-1] // self.num_heads)).transpose(
(0, 2, 1, 3))
attn = paddle.matmul(q, k.transpose((0, 1, 3, 2))) * self.scale
attn = nn.functional.softmax(attn, axis=-1)
attn = self.attn_drop(attn)
x = paddle.matmul(attn, v)
x = x.transpose((0, 2, 1, 3)).reshape((B, N, x.shape[-1] * x.shape[-3]))
x = x.transpose((0, 2, 1, 3)).reshape(
(B, N, x.shape[-1] * x.shape[-3]))
x = self.proj(x)
x = self.proj_drop(x)
return x
@ -183,18 +185,22 @@ class Block(nn.Layer):
def forward(self, pixel_embed, patch_embed):
# inner
pixel_embed = paddle.add(pixel_embed, self.drop_path(
self.attn_in(self.norm_in(pixel_embed))))
pixel_embed = paddle.add(pixel_embed, self.drop_path(
self.mlp_in(self.norm_mlp_in(pixel_embed))))
pixel_embed = paddle.add(
pixel_embed,
self.drop_path(self.attn_in(self.norm_in(pixel_embed))))
pixel_embed = paddle.add(
pixel_embed,
self.drop_path(self.mlp_in(self.norm_mlp_in(pixel_embed))))
# outer
B, N, C = patch_embed.shape
patch_embed[:, 1:] = paddle.add(patch_embed[:, 1:], self.proj(
self.norm1_proj(pixel_embed).reshape((B, N - 1, -1))))
patch_embed = paddle.add(patch_embed, self.drop_path(
self.attn_out(self.norm_out(patch_embed))))
patch_embed = paddle.add(patch_embed, self.drop_path(
self.mlp(self.norm_mlp(patch_embed))))
patch_embed[:, 1:] = paddle.add(
patch_embed[:, 1:],
self.proj(self.norm1_proj(pixel_embed).reshape((B, N - 1, -1))))
patch_embed = paddle.add(
patch_embed,
self.drop_path(self.attn_out(self.norm_out(patch_embed))))
patch_embed = paddle.add(
patch_embed, self.drop_path(self.mlp(self.norm_mlp(patch_embed))))
return pixel_embed, patch_embed
@ -225,8 +231,8 @@ class PixelEmbed(nn.Layer):
x = x.transpose((0, 2, 1)).reshape(
(-1, self.in_dim, self.new_patch_size, self.new_patch_size))
x = x + pixel_pos
x = x.reshape((-1, self.in_dim, self.new_patch_size * self.new_patch_size)).transpose(
(0, 2, 1))
x = x.reshape((-1, self.in_dim, self.new_patch_size *
self.new_patch_size)).transpose((0, 2, 1))
return x
@ -328,7 +334,8 @@ class TNT(nn.Layer):
patch_embed = self.norm2_proj(
self.proj(
self.norm1_proj(
pixel_embed.reshape((-1, self.num_patches, pixel_embed.shape[-1] * pixel_embed.shape[-2])))))
pixel_embed.reshape((-1, self.num_patches, pixel_embed.
shape[-1] * pixel_embed.shape[-2])))))
patch_embed = paddle.concat(
(self.cls_token.expand((B, -1, -1)), patch_embed), axis=1)
patch_embed = patch_embed + self.patch_pos