When the U-net model is created, we should support custom up/downsampling layers and allow Conv2DTranspose etc to use the correct number of filters:
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# set up the up/downsampling |
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# TODO(arl): these may already be instantiated with custom params |
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# TODO(arl): if using a transpose convolution, we need to set the number of filters |
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self._downsampling = downsampling() |
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self._upsampling = upsampling() |
When the U-net model is created, we should support custom up/downsampling layers and allow
Conv2DTransposeetc to use the correct number of filters:cellx/cellx/networks/unet.py
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