tensorflow::
  #include <nn_ops.h>
  Produces the average pool of the input tensor for quantized types.
Summary
Arguments:
- scope: A Scope object
- input: 4-D with shape [batch, height, width, channels].
- min_input: The float value that the lowest quantized input value represents.
- max_input: The float value that the highest quantized input value represents.
- ksize: The size of the window for each dimension of the input tensor. The length must be 4 to match the number of dimensions of the input.
- strides: The stride of the sliding window for each dimension of the input tensor. The length must be 4 to match the number of dimensions of the input.
- padding: The type of padding algorithm to use.
Returns:
- Outputoutput
- Outputmin_output: The float value that the lowest quantized output value represents.
- Outputmax_output: The float value that the highest quantized output value represents.
| Constructors and Destructors | |
|---|---|
| QuantizedAvgPool(const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input min_input, ::tensorflow::Input max_input, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding) | 
| Public attributes | |
|---|---|
| max_output | |
| min_output | |
| operation | |
| output | |
Public attributes
max_output
::tensorflow::Output max_output
min_output
::tensorflow::Output min_output
operation
Operation operation
output
::tensorflow::Output output
Public functions
QuantizedAvgPool
QuantizedAvgPool( const ::tensorflow::Scope & scope, ::tensorflow::Input input, ::tensorflow::Input min_input, ::tensorflow::Input max_input, const gtl::ArraySlice< int > & ksize, const gtl::ArraySlice< int > & strides, StringPiece padding )