def depth_to_space(input, scale, data_format=None):
''' Uses phase shift algorithm to convert channels/depth for spatial resolution '''
if data_format is None:
data_format = image_data_format()
data_format = data_format.lower()
input = _preprocess_conv2d_input(input, data_format)
out = tf.depth_to_space(input, scale)
out = _postprocess_conv2d_output(out, data_format)
return out
def call(self, inputs, training=None):
inputs = _preprocess_conv2d_input(inputs, self.data_format)
outputs = tf.nn.depthwise_conv2d(inputs,
self.depthwise_kernel,
strides=self._strides,
padding=self._padding,
rate=self.dilation_rate,
data_format=self._data_format)
outputs = _postprocess_conv2d_output(outputs, self.data_format)
if self.bias:
outputs = K.bias_add(outputs,
self.bias,
data_format=self.data_format)
if self.activation is not None:
return self.activation(outputs)
return outputs