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Add todo and comment
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@ -36,6 +36,7 @@ def convnext_inverse(layer_in, depths, dims):
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def block_upscale(layer_in, block_number, depth, dim):
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layer_next = layer_in
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# Ref https://machinelearningmastery.com/upsampling-and-transpose-convolution-layers-for-generative-adversarial-networks/ to understand Conv2DTranspose
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layer_next = tf.keras.layers.Conv2DTranspose(
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name=f"cns.stage{block_number}.end.convtp",
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filters=dim,
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@ -29,6 +29,7 @@ def model_rainfallwater_segmentation(metadata, feature_dim_in, shape_water_out,
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layer_next = do_convnext_inverse(layer_next, arch_name="convnext_i_tiny")
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# TODO: An attention layer here instead of a dense layer, with a skip connection perhaps?
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raise Exception("Error: read and implement attention from https://ieeexplore.ieee.org/document/9076883")
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layer_next = tf.keras.layers.Dense(32)(layer_next)
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layer_next = tf.keras.layers.Conv2D(1, kernel_size=1, activation="softmax", padding="same")(layer_next)
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