tf.raw_ops.MaxPoolGradGradWithArgmax

Computes second-order gradients of the maxpooling function.

tf.raw_ops.MaxPoolGradGradWithArgmax(
    input,
    grad,
    argmax,
    ksize,
    strides,
    padding,
    include_batch_in_index=False,
    name=None
)

input A Tensor. Must be one of the following types: float32, float64, int32, uint8, int16, int8, int64, bfloat16, uint16, half, uint32, uint64. The original input.
grad A Tensor. Must have the same type as input. 4-D with shape [batch, height, width, channels]. Gradients w.r.t. the input of max_pool.
argmax A Tensor. Must be one of the following types: int32, int64. The indices of the maximum values chosen for each output of max_pool.
ksize A list of ints that has length >= 4. The size of the window for each dimension of the input tensor.
strides A list of ints that has length >= 4. The stride of the sliding window for each dimension of the input tensor.
padding A string from: "SAME", "VALID". The type of padding algorithm to use.
include_batch_in_index An optional bool. Defaults to False. Whether to include batch dimension in flattened index of argmax.
name A name for the operation (optional).

A Tensor. Has the same type as input.