Computes second-order gradients of the maxpooling function.
tf.raw_ops.MaxPoolGradGradV2(
orig_input, orig_output, grad, ksize, strides, padding,
data_format='NHWC', name=None
)
Args |
orig_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 tensor.
|
orig_output
|
A Tensor . Must have the same type as orig_input .
The original output tensor.
|
grad
|
A Tensor . Must have the same type as orig_input .
4-D. Gradients of gradients w.r.t. the input of max_pool .
|
ksize
|
A Tensor of type int32 .
The size of the window for each dimension of the input tensor.
|
strides
|
A Tensor of type int32 .
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.
|
data_format
|
An 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].
|
name
|
A name for the operation (optional).
|
Returns |
A Tensor . Has the same type as orig_input .
|