tf.raw_ops.MaxPoolGradGradWithArgmax

Computes second-order gradients of the maxpooling function.

Compat aliases for migration

tf.compat.v1.raw_ops.MaxPoolGradGradWithArgmax

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

Args
`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).

Returns
A `Tensor`. Has the same type as `input`.

Args