Open mohit-av opened 1 year ago
I'm creating a model to decompress my image in TF using Conv2DTranspose and GDN layer. My architecture looks like this:
Conv2DTranspose
GDN
import os import tensorflow as tf from tensorflow_compression import layers from tensorflow.keras.layers import Conv2DTranspose from tensorflow.keras.models import Sequential network_channels = 128 compression_channels = 192 in_channels = 3 gdn_layer_1 = layers.GDN(inverse=True, rectify=False, data_format = "channels_first") gdn_layer_2 = layers.GDN(inverse=True, rectify=False, data_format = "channels_first") gdn_layer_3 = layers.GDN(inverse=True, rectify=False, data_format = "channels_first") model = Sequential() model.add(Conv2DTranspose(network_channels, (5, 5), strides = (2, 2), padding= 'same', output_padding = (1,1), data_format = 'channels_first', input_shape=( compression_channels, 1, 1))) model.add(gdn_layer_1) model.add(Conv2DTranspose(network_channels, (5, 5), strides = (2, 2), padding= 'same', output_padding = (1,1), data_format = 'channels_first')) model.add(gdn_layer_2) model.add(Conv2DTranspose(network_channels, (5, 5), strides = (2, 2), padding= 'same', output_padding = (1,1), data_format = 'channels_first')) model.add(gdn_layer_3) model.add(Conv2DTranspose(in_channels, (5, 5), strides = (2, 2), padding= 'same', output_padding = (1,1), data_format = 'channels_first')) model.summary()
When I'm saving my model using the below command.
model.save(os.path.join("./tf_model"))
It's resulting in this issue:
My TF version is 2.11.0. I'm also attaching link to Colab Notebook to replicate the issue.
2.11.0
I'm creating a model to decompress my image in TF using
Conv2DTranspose
andGDN
layer. My architecture looks like this:When I'm saving my model using the below command.
It's resulting in this issue:
My TF version is
2.11.0
. I'm also attaching link to Colab Notebook to replicate the issue.