tf.raw_ops.MaxPoolGradGradWithArgmax

Computes second-order gradients of the maxpooling function.

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Compat aliases for migration

See Migration guide for more details.

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.