1 /*
2 * Copyright (C) 2017 The Android Open Source Project
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17 // Contains the implementation of the operations.
18
19 #define LOG_TAG "Operations"
20
21 #include "CpuOperationUtils.h"
22 #include "Operations.h"
23
24 #include "tensorflow/lite/kernels/internal/optimized/legacy_optimized_ops.h"
25 #include "tensorflow/lite/kernels/internal/reference/legacy_reference_ops.h"
26
27 #include "Tracing.h"
28
29 namespace android {
30 namespace nn {
31
floorFloat16(const _Float16 * inputData,_Float16 * outputData,const Shape & shape)32 bool floorFloat16(const _Float16* inputData, _Float16* outputData, const Shape& shape) {
33 NNTRACE_TRANS("floorFloat16");
34 std::vector<float> inputDataFloat32(getNumberOfElements(shape));
35 convertFloat16ToFloat32(inputData, &inputDataFloat32);
36
37 std::vector<float> outputDataFloat32(getNumberOfElements(shape));
38 floorFloat32(inputDataFloat32.data(), outputDataFloat32.data(), shape);
39 convertFloat32ToFloat16(outputDataFloat32, outputData);
40 return true;
41 }
42
floorFloat32(const float * inputData,float * outputData,const Shape & shape)43 bool floorFloat32(const float* inputData, float* outputData, const Shape& shape) {
44 NNTRACE_TRANS("floorFloat32");
45 tflite::Dims<4> dim = convertShapeToDims(shape);
46 NNTRACE_COMP_SWITCH("optimized_ops::Floor");
47 tflite::optimized_ops::Floor(inputData, dim, outputData, dim);
48 return true;
49 }
50
meanFloat16(_Float16 * inputData,const Shape & inputShape,const int32_t * axis,const Shape & axisShape,bool keepDims,_Float16 * outputData,const Shape & outputShape)51 bool meanFloat16(_Float16* inputData, const Shape& inputShape, const int32_t* axis,
52 const Shape& axisShape, bool keepDims, _Float16* outputData,
53 const Shape& outputShape) {
54 NNTRACE_TRANS("meanFloat16");
55 std::vector<float> inputDataFloat32(getNumberOfElements(inputShape));
56 convertFloat16ToFloat32(inputData, &inputDataFloat32);
57
58 std::vector<float> outputDataFloat32(getNumberOfElements(outputShape));
59 meanGeneric<float, float>(inputDataFloat32.data(), inputShape, axis, axisShape, keepDims,
60 outputDataFloat32.data(), outputShape);
61 convertFloat32ToFloat16(outputDataFloat32, outputData);
62 return true;
63 }
64
65 template <typename T, typename U>
meanGeneric(T * inputData,const Shape & inputShape,const int32_t * axis,const Shape & axisShape,bool keepDims,T * outputData,const Shape & outputShape)66 bool meanGeneric(T* inputData, const Shape& inputShape, const int32_t* axis, const Shape& axisShape,
67 bool keepDims, T* outputData, const Shape& outputShape) {
68 NNTRACE_TRANS("meanGeneric");
69 // Creates a temp index to iterate through input data.
70 int32_t* scratchBuffer = new int32_t[getNumberOfDimensions(inputShape)];
71
72 // Creates a temp tensor to store resolved axis given input data.
73 int32_t axisSize = static_cast<int32_t>(getSizeOfDimension(axisShape, 0));
74 int32_t* resolvedAxis = new int32_t[axisSize];
75
76 bool result = true;
77 U* tempSumBuffer = new (std::nothrow) U[getNumberOfElements(outputShape)];
78 if (!tempSumBuffer) {
79 LOG(ERROR) << "Failed to allocate tempSumBuffer for MEAN";
80 result = false;
81 } else {
82 NNTRACE_COMP_SWITCH("optimized_ops::Mean");
83 tflite::reference_ops::Mean<T, U>(
84 inputData, reinterpret_cast<const int*>(inputShape.dimensions.data()),
85 getNumberOfDimensions(inputShape), outputData,
86 reinterpret_cast<const int*>(outputShape.dimensions.data()),
87 getNumberOfDimensions(outputShape), axis, axisSize, keepDims, scratchBuffer,
88 resolvedAxis, tempSumBuffer);
89 delete[] tempSumBuffer;
90 }
91 delete[] scratchBuffer;
92 delete[] resolvedAxis;
93 return result;
94 }
95 template bool meanGeneric<float, float>(float* inputData, const Shape& inputShape,
96 const int32_t* axis, const Shape& axisShape, bool keepDims,
97 float* outputData, const Shape& outputShape);
98 template bool meanGeneric<uint8_t, int32_t>(uint8_t* inputData, const Shape& inputShape,
99 const int32_t* axis, const Shape& axisShape,
100 bool keepDims, uint8_t* outputData,
101 const Shape& outputShape);
102
103 } // namespace nn
104 } // namespace android
105