def concat_channels(inputs,
name='',
data_format='channels_first',
debug_print=debug_print_others):
axis = get_channel_index(inputs[0], data_format)
outputs = tf.concat(inputs, axis=axis, name=name)
if debug_print:
print_shape_parameters(inputs, outputs, name, 'concat')
return outputs
def flatten(inputs, name='', debug_print=debug_print_others):
outputs = tf.layers.flatten(inputs, name)
if debug_print:
print_shape_parameters(inputs, outputs, name, 'flatten')
return outputs
def mult(input0, input1, name='', debug_print=debug_print_others):
outputs = tf.multiply(input0, input1, name=name)
if debug_print:
print_shape_parameters(input0, outputs, name, 'mult')
return outputs
def add(inputs, name='', debug_print=debug_print_others):
outputs = tf.add_n(inputs, name=name)
if debug_print:
print_shape_parameters(inputs[0], outputs, name, 'add')
return outputs
def concat_flattened(inputs, name='', debug_print=debug_print_others):
outputs = tf.concat(inputs, axis=1, name=name)
if debug_print:
print_shape_parameters(inputs[0], outputs, name, 'concat')
return outputs