Get the value of some weights in a model trained by TensorFlow

Question

I have trained a ConvNet model with TensorFlow, and I want to get a particular weight in layer. For example in torch7 I would simply access model.modules[2].weights

Answer 1

2.0 Compatible Answer: If we build a Model using Keras Sequential API, we can get the Weights of the Model using the code mentioned below:

!pip install tensorflow==2.1

from tf.keras import Sequential

model = Sequential()

model.add(Conv2D(filters=conv1_fmaps, kernel_size=conv1_ksize,
                         strides=conv1_stride, padding=conv1_pad,
                         activation=tf.nn.relu, input_shape=(height, width, channels),
                    data_format='channels_last'))

model.add(MaxPool2D(pool_size = (2,2), strides= (2,2), padding="VALID"))

model.add(Dropout(0.25))

model.add(Flatten())

model.add(Dense(units = 32, activation = 'relu'))

model.add(Dense(units = 10, activation = 'softmax'))

model.summary()

print(model.trainable_variables) 

The Last Statement, print(model.trainable_variables), will return the Weights of the Model as shown below:

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