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large refactor

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luni
2022-09-25 08:31:13 +00:00
parent 84ec5a056e
commit 92891f5b26
33 changed files with 1661 additions and 1635 deletions
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convnext/models/convnext_tf.py
+12 -9
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@@ -104,16 +104,18 @@ class ConvNeXt(tf.keras.Model):
super().__init__()
self.include_top = include_top
self.downsample_layers = [] # stem and 3 intermediate downsampling conv layers
stem = tf.keras.Sequential([
Conv2D(dims[0], kernel_size=4, strides=4, padding='same'),
LayerNormalization(epsilon=1e-6)]
)
# stem = tf.keras.Sequential([
# Conv2D(dims[0], kernel_size=4, strides=4, padding='same'),
# LayerNormalization(epsilon=1e-6)]
# )
stem = [Conv2D(dims[0], kernel_size=4, strides=4, padding='same'), LayerNormalization(epsilon=1e-6)]
self.downsample_layers.append(stem)
for i in range(len(depths) - 1):
downsample_layer = tf.keras.Sequential([
LayerNormalization(epsilon=1e-6),
Conv2D(dims[i+1], kernel_size=2, strides=2, padding='same')]
)
# downsample_layer = tf.keras.Sequential([
# LayerNormalization(epsilon=1e-6),
# Conv2D(dims[i+1], kernel_size=2, strides=2, padding='same')]
# )
downsample_layer = [LayerNormalization(epsilon=1e-6), Conv2D(dims[i+1], kernel_size=2, strides=2, padding='same')]
self.downsample_layers.append(downsample_layer)
self.stages = [] # 4 feature resolution stages, each consisting of multiple residual blocks
@@ -138,7 +140,8 @@ class ConvNeXt(tf.keras.Model):
def forward_features(self, x):
for i in range(len(self.downsample_layers)):
x = self.downsample_layers[i](x)
x = self.downsample_layers[i][0](x)
x = self.downsample_layers[i][1](x)
x = self.stages[i](x)
return x