MaxPoolGradGrad

tensorflow C++ API

tensorflow::ops::MaxPoolGradGrad

Computes second-order gradients of the maxpooling function.

Summary

Arguments:

• scope: A Scope object
• orig_input: The original input tensor.
• orig_output: The original output tensor.
• grad: 4-D. Gradients of gradients w.r.t. the input ofmax_pool.
• ksize: The size of the window for each dimension of the input tensor.
• strides: The stride of the sliding window for each dimension of the input tensor.
• 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, in_height, in_width, in_channels]. Alternatively, the format could be "NCHW", the data storage order of: [batch, in_channels, in_height, in_width].

Returns:

• Output: Gradients of gradients w.r.t. the input tomax_pool.

MaxPoolGradGrad block

Source link : https://github.com/EXPNUNI/enuSpaceTensorflow/blob/master/enuSpaceTensorflow/tf_nn.cpp

Argument:

• Scope scope : A Scope object (A scope is generated automatically each page. A scope is not connected.)
• Input orig_input: connect Input node.
• Input orig_output: connect Input node.
• Input grad: connect Input node.
• ArraySlice< int> ksize: input ksize in values. ex)1,2,2,2,1
• ArraySlice< int> strides: input ksize in values. ex)1,4,3,2,1
• stringpiece padding: input padding in value. ex)SAME
• MaxPoolGradGrad::Attrs attrs: input attrs in values )data_format_ = NHWC;

Return:

• Output output: Output object of MaxPoolGradGrad class object.

Result:

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

Using Method