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Number of output and input in layer of networks #7

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@TyrandeWhisperwind

hello, wanted to ask u if possible, why did u choose this number of input and output in the layers?
layer_1 = self.layer_manager.create_conv_layer(self.tf_inputs_norm, 32, 8, strides=4, activation_fn='relu',
padding='valid', scope='tf_layer_1')
layer_2 = self.layer_manager.create_conv_layer(layer_1, 64, 4, strides=2, activation_fn='relu', padding='valid',
scope='tf_layer_2')
layer_3 = self.layer_manager.create_conv_layer(layer_2, 64, 3, strides=1, activation_fn='relu', padding='valid',
scope='tf_layer_3')
layer_4 = self.layer_manager.create_fully_connected_layer(layer_3, 512, activation_fn='relu',
scope='tf_layer_4')
as i know the number of outputs in the output layer should be the number of possible actions in the environment, and the input is the state

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