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
)
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 .
|