DepthwiseConv2dNativeBackpropInput

tensorflow C++ API

Computes the gradients of depthwise convolution with respect to the input.

Arguments:

scope: A Scope object
input_sizes: An integer vector representing the shape ofinput, based ondata_format. For example, ifdata_formatis ‘NHWC’ theninputis a 4-D[batch, height, width, channels]tensor.
filter: 4-D with shape[filter_height, filter_width, in_channels, depthwise_multiplier].
out_backprop: 4-D with shape based ondata_format. For example, ifdata_formatis ‘NHWC’ then out_backprop shape is [batch, out_height, out_width, out_channels]. Gradients w.r.t. the output of the convolution.
strides: The stride of the sliding window for each dimension of the input of the convolution.
padding: The type of padding algorithm to use.

Optional attributes (seeAttrs):

data_format: Specify the data format of the input and output data. With the default format “NHWC”, the data is stored in the order of: [batch, height, width, channels]. Alternatively, the format could be “NCHW”, the data storage order of: [batch, channels, height, width].

Returns:

Output: 4-D with shape according todata_format. For example, ifdata_formatis ‘NHWC’, output shape is [batch, in_height, in_width, in_channels]. Gradient w.r.t. the input of the convolution.

Argument:

Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
Input input_sizes: connect Input node.
Input filter: connect Input node.
Input out_backprop: connect Input node.
gtl::ArraySlice< int > strides: Input strides in value ex)1,2,2,1
StringPiece padding: Input padding in value ex)SAME
DepthwiseConv2dNativeBackpropInput::Attrs attrs : Input attrs in value. ex) data_format_ = NHWC;

Return:

Output output : Output object of DepthwiseConv2dNativeBackpropInput class object.

Result:

std::vector(Tensor) result_output : Returned object of executed result by calling session.