65 lines
2.7 KiB
C++
65 lines
2.7 KiB
C++
/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License");
|
|
you may not use this file except in compliance with the License.
|
|
You may obtain a copy of the License at
|
|
|
|
http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
Unless required by applicable law or agreed to in writing, software
|
|
distributed under the License is distributed on an "AS IS" BASIS,
|
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
See the License for the specific language governing permissions and
|
|
limitations under the License.
|
|
==============================================================================*/
|
|
#ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_MAXIMUM_MINIMUM_H_
|
|
#define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_MAXIMUM_MINIMUM_H_
|
|
|
|
#include "tensorflow/lite/kernels/internal/common.h"
|
|
#include "tensorflow/lite/kernels/internal/types.h"
|
|
|
|
namespace tflite {
|
|
namespace reference_ops {
|
|
|
|
template <typename T, typename Op, int N = 5>
|
|
void MaximumMinimumBroadcastSlow(const RuntimeShape& unextended_input1_shape,
|
|
const T* input1_data,
|
|
const RuntimeShape& unextended_input2_shape,
|
|
const T* input2_data,
|
|
const RuntimeShape& unextended_output_shape,
|
|
T* output_data, Op op) {
|
|
// Uses element-wise calculation if broadcast is not required.
|
|
if (unextended_input1_shape == unextended_input2_shape) {
|
|
const int flat_size =
|
|
MatchingElementsSize(unextended_input1_shape, unextended_input2_shape,
|
|
unextended_output_shape);
|
|
for (int i = 0; i < flat_size; ++i) {
|
|
output_data[i] = op(input1_data[i], input2_data[i]);
|
|
}
|
|
} else {
|
|
TFLITE_DCHECK_LE(unextended_input1_shape.DimensionsCount(), N);
|
|
TFLITE_DCHECK_LE(unextended_input2_shape.DimensionsCount(), N);
|
|
TFLITE_DCHECK_LE(unextended_output_shape.DimensionsCount(), N);
|
|
|
|
NdArrayDesc<N> desc1;
|
|
NdArrayDesc<N> desc2;
|
|
NdArrayDesc<N> output_desc;
|
|
NdArrayDescsForElementwiseBroadcast(
|
|
unextended_input1_shape, unextended_input2_shape, &desc1, &desc2);
|
|
CopyDimsToDesc(RuntimeShape::ExtendedShape(N, unextended_output_shape),
|
|
&output_desc);
|
|
|
|
auto maxmin_func = [&](int indexes[N]) {
|
|
output_data[SubscriptToIndex(output_desc, indexes)] =
|
|
op(input1_data[SubscriptToIndex(desc1, indexes)],
|
|
input2_data[SubscriptToIndex(desc2, indexes)]);
|
|
};
|
|
NDOpsHelper<N>(output_desc, maxmin_func);
|
|
}
|
|
}
|
|
|
|
} // namespace reference_ops
|
|
} // namespace tflite
|
|
|
|
#endif // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_MAXIMUM_MINIMUM_H_
|