tf.raw_ops.MaxPoolGradV2

Computes gradients of the maxpooling function.

tf.raw_ops.MaxPoolGradV2(
    orig_input,
    orig_output,
    grad,
    ksize,
    strides,
    padding,
    data_format='NHWC',
    name=None
)

orig_inputA Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64. The original input tensor.
orig_outputA Tensor. Must have the same type as orig_input. The original output tensor.
gradA Tensor. Must have the same type as orig_input. 4-D. Gradients w.r.t. the output of max_pool.
ksizeA Tensor of type int32. The size of the window for each dimension of the input tensor.
stridesA Tensor of type int32. The stride of the sliding window for each dimension of the input tensor.
paddingA string from: "SAME", "VALID". The type of padding algorithm to use.
data_formatAn optional string from: "NHWC", "NCHW". Defaults to "NHWC". 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].
nameA name for the operation (optional).

A Tensor. Has the same type as orig_input.