def __call__(self, x):
"""Applies the depthwise convolution layer.
Args:
x (chainer.Variable or :class:`numpy.ndarray` or cupy.ndarray):
Input image.
Returns:
~chainer.Variable: Output of the depthwise convolution.
"""
if self.W.data is None:
self._initialize_params(x.shape[1])
return depthwise_convolution_2d.depthwise_convolution_2d(
x, self.W, self.b, self.stride, self.pad)
def forward(self, x):
"""Applies the depthwise convolution layer.
Args:
x (chainer.Variable or :class:`numpy.ndarray` or cupy.ndarray):
Input image.
Returns:
~chainer.Variable: Output of the depthwise convolution.
"""
if self.W.array is None:
self._initialize_params(x.shape[1])
return depthwise_convolution_2d.depthwise_convolution_2d(
x, self.W, self.b, self.stride, self.pad)
def __call__(self, x):
"""Applies the depthwise convolution layer.
Args:
x (chainer.Variable or :class:`numpy.ndarray` or cupy.ndarray):
Input image.
Returns:
~chainer.Variable: Output of the depthwise convolution.
"""
if self.has_uninitialized_params:
with cuda.get_device_from_id(self._device_id):
self._initialize_params(x.shape[1])
return depthwise_convolution_2d.depthwise_convolution_2d(
x, self.W, self.b, self.stride, self.pad)
def __call__(self, x):
"""Applies the depthwise convolution layer.
Args:
x (chainer.Variable or :class:`numpy.ndarray` or cupy.ndarray):
Input image.
Returns:
~chainer.Variable: Output of the depthwise convolution.
"""
if self.has_uninitialized_params:
with cuda.get_device(self._device_id):
self._initialize_params(x.shape[1])
return depthwise_convolution_2d.depthwise_convolution_2d(
x, self.W, self.b, self.stride, self.pad)
def __call__(self, x):
if self.W.data is None:
self._initialize_params(x.shape[1])
return depthwise_convolution_2d.depthwise_convolution_2d(
x, self.W_bar, self.b, self.stride, self.pad)