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fiddle with Conv2DTranspose

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you need to set the `stride` argument to actually get it to upscale..... :P
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Starbeamrainbowlabs 2022-10-03 17:51:41 +01:00
parent d544553800
commit 92c380bff5
Signed by: sbrl
GPG key ID: 1BE5172E637709C2
1 changed files with 6 additions and 1 deletions
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7
aimodel/src/lib/ai/components/convnext_inverse.py
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@ -36,7 +36,12 @@ def convnext_inverse(layer_in, depths, dims):
def block_upscale(layer_in, block_number, depth, dim): def block_upscale(layer_in, block_number, depth, dim):
layer_next = layer_in layer_next = layer_in
layer_next = tf.keras.layers.Conv2DTranspose(name=f"cns.stage{block_number}.end.convtp", filters=dim, kernel_size=4, padding="same")(layer_next) layer_next = tf.keras.layers.Conv2DTranspose(
name=f"cns.stage{block_number}.end.convtp",
filters=dim,
kernel_size=4,
stride=2
)(layer_next)
layer_next = tf.keras.layers.LayerNormalization(name=f"cns.stage{block_number}.end.norm", epsilon=1e-6)(layer_next) layer_next = tf.keras.layers.LayerNormalization(name=f"cns.stage{block_number}.end.norm", epsilon=1e-6)(layer_next)
for i in range(depth): for i in range(depth):