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fixed changed reverse?

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luni
2023-02-21 21:08:05 +00:00
parent 2100d364f9
commit ac27319860
2 changed files with 23 additions and 20 deletions
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convnext/models/convnext_tf.py
+16 -13
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@@ -225,26 +225,28 @@ class ConvNeXtReverse(tf.keras.Model):
drop_path_rate=0., layer_scale_init_value=1e-6, head_init_scale=1., learn_weights=False,
):
super().__init__()
self.upsample_layers = [] # stem and 3 intermediate downsampling conv layers
self.upsample_layers = []
stem = tf.keras.Sequential([
Conv2DTranspose(dims[0], kernel_size=4, strides=4, padding='same'),
# UpSampling2D((4, 4), interpolation='nearest'),
# Conv2D(dims[0], kernel_size=4, strides=1, padding='same'),
# Dense(dims[0]),
LayerNormalization(epsilon=1e-6)]
)
LayerNormalization(epsilon=1e-6),
Conv2DTranspose(dims[0], kernel_size=2, strides=2, padding='same'),
])
self.upsample_layers.append(stem)
for i in range(len(depths) - 1):
for i in range(len(depths) - 2):
downsample_layer = tf.keras.Sequential([
LayerNormalization(epsilon=1e-6),
Conv2DTranspose(dims[i+1], kernel_size=2, strides=2, padding='same')
# UpSampling2D((2,2), interpolation='nearest'),
# Conv2D(dims[i+1], kernel_size=2, strides=1, padding='same'),
# Dense(dims[i+1]),
Conv2DTranspose(dims[i+1], kernel_size=2, strides=2, padding='same'),
])
self.upsample_layers.append(downsample_layer)
self.stages = [] # 4 feature resolution stages, each consisting of multiple residual blocks
downsample_layer = tf.keras.Sequential([
Conv2DTranspose(dims[i+2], kernel_size=2, strides=2, padding='same'),
LayerNormalization(epsilon=1e-6),
])
self.upsample_layers.append(downsample_layer)
self.stages = []
dp_rates = [x for x in np.linspace(0, drop_path_rate, sum(depths))]
cur = 0
for i in range(len(depths)):
@@ -257,6 +259,7 @@ class ConvNeXtReverse(tf.keras.Model):
if not learn_weights:
self.last = Dense(3, activation='tanh')
# self.last = Activation('tanh')
else:
self.last = Activation('softmax')
# self.last = Dense(24, activation='softmax')