from tensorflow.keras.layers import Dense, Conv2D, MaxPool2D, Flatten

		# Block 1
		conv1a   =  Conv2D(padding="same", filters=RNN_SIZE//8, kernel_size=[8, 8],   strides=4, data_format='channels_last', kernel_initializer=w_init,activation=tf.nn.relu)(self.inputs)
		conv1b   =  Conv2D(padding="same", filters=RNN_SIZE//8, kernel_size=[3, 3],   strides=1, data_format='channels_last', kernel_initializer=w_init,activation=tf.nn.relu)(conv1a)
		conv1c   =  Conv2D(padding="same", filters=RNN_SIZE//8, kernel_size=[3, 3],   strides=1, data_format='channels_last', kernel_initializer=w_init,activation=tf.nn.relu)(conv1b)
