1 /* 2 * Copyright (C) 2018 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 #define LOG_TAG "Operations" 18 19 #include "HalInterfaces.h" 20 #include "OperationResolver.h" 21 #include "OperationsUtils.h" 22 #include "Tracing.h" 23 24 namespace android { 25 namespace nn { 26 namespace gather { 27 28 constexpr char kOperationName[] = "GATHER"; 29 30 constexpr uint32_t kNumInputs = 3; 31 constexpr uint32_t kInputTensor = 0; 32 constexpr uint32_t kInputAxis = 1; 33 constexpr uint32_t kInputIndices = 2; 34 35 constexpr uint32_t kNumOutputs = 1; 36 constexpr uint32_t kOutputTensor = 0; 37 38 namespace { 39 40 template <typename T> 41 inline bool eval(const T* inputData, const Shape& inputShape, int32_t axis, 42 const int32_t* indicesData, const Shape& indicesShape, T* outputData) { 43 const auto outerSize = getNumberOfElements(inputShape, 0, axis); 44 const auto axisSize = getSizeOfDimension(inputShape, axis); 45 const auto innerSize = 46 getNumberOfElements(inputShape, axis + 1, getNumberOfDimensions(inputShape)); 47 const auto indicesCount = getNumberOfElements(indicesShape); 48 for (uint32_t outer = 0; outer < outerSize; ++outer) { 49 for (uint32_t outputIndex = 0; outputIndex < indicesCount; ++outputIndex) { 50 const auto inputIndex = static_cast<uint32_t>(indicesData[outputIndex]); 51 NN_RET_CHECK_LE(0u, inputIndex); 52 NN_RET_CHECK_LT(inputIndex, axisSize); 53 std::memcpy(outputData + (outer * indicesCount + outputIndex) * innerSize, 54 inputData + (outer * axisSize + inputIndex) * innerSize, 55 sizeof(T) * innerSize); 56 } 57 } 58 return true; 59 } 60 61 } // namespace 62 63 bool validate(const IOperationValidationContext* context) { 64 NN_RET_CHECK_EQ(context->getNumInputs(), kNumInputs); 65 NN_RET_CHECK_EQ(context->getNumOutputs(), kNumOutputs); 66 OperandType inputType = context->getInputType(kInputTensor); 67 NN_RET_CHECK( 68 inputType == OperandType::TENSOR_FLOAT16 || inputType == OperandType::TENSOR_FLOAT32 || 69 inputType == OperandType::TENSOR_INT32 || inputType == OperandType::TENSOR_QUANT8_ASYMM) 70 << "Unsupported tensor type for operation " << kOperationName; 71 NN_RET_CHECK(validateInputTypes(context, 72 {inputType, OperandType::INT32, OperandType::TENSOR_INT32})); 73 NN_RET_CHECK(validateOutputTypes(context, {inputType})); 74 return validateHalVersion(context, HalVersion::V1_2); 75 } 76 77 bool prepare(IOperationExecutionContext* context) { 78 Shape input = context->getInputShape(kInputTensor); 79 int32_t axis = context->getInputValue<int32_t>(kInputAxis); 80 NN_RET_CHECK(handleNegativeAxis(input, &axis)); 81 Shape indices = context->getInputShape(kInputIndices); 82 Shape output = context->getOutputShape(kOutputTensor); 83 84 output.dimensions.clear(); 85 output.dimensions.reserve(getNumberOfDimensions(input) + getNumberOfDimensions(indices) - 1); 86 output.dimensions.insert(output.dimensions.end(), input.dimensions.begin(), 87 input.dimensions.begin() + axis); 88 output.dimensions.insert(output.dimensions.end(), indices.dimensions.begin(), 89 indices.dimensions.end()); 90 output.dimensions.insert(output.dimensions.end(), input.dimensions.begin() + axis + 1, 91 input.dimensions.end()); 92 93 return context->setOutputShape(kOutputTensor, output); 94 } 95 96 bool execute(IOperationExecutionContext* context) { 97 int32_t axis = context->getInputValue<int32_t>(kInputAxis); 98 NN_RET_CHECK(handleNegativeAxis(context->getInputShape(kInputTensor), &axis)); 99 switch (context->getInputType(kInputTensor)) { 100 case OperandType::TENSOR_FLOAT16: 101 return eval(context->getInputBuffer<_Float16>(kInputTensor), 102 context->getInputShape(kInputTensor), axis, 103 context->getInputBuffer<int32_t>(kInputIndices), 104 context->getInputShape(kInputIndices), 105 context->getOutputBuffer<_Float16>(kOutputTensor)); 106 case OperandType::TENSOR_FLOAT32: 107 return eval(context->getInputBuffer<float>(kInputTensor), 108 context->getInputShape(kInputTensor), axis, 109 context->getInputBuffer<int32_t>(kInputIndices), 110 context->getInputShape(kInputIndices), 111 context->getOutputBuffer<float>(kOutputTensor)); 112 case OperandType::TENSOR_INT32: 113 return eval(context->getInputBuffer<int32_t>(kInputTensor), 114 context->getInputShape(kInputTensor), axis, 115 context->getInputBuffer<int32_t>(kInputIndices), 116 context->getInputShape(kInputIndices), 117 context->getOutputBuffer<int32_t>(kOutputTensor)); 118 case OperandType::TENSOR_QUANT8_ASYMM: 119 return eval(context->getInputBuffer<uint8_t>(kInputTensor), 120 context->getInputShape(kInputTensor), axis, 121 context->getInputBuffer<int32_t>(kInputIndices), 122 context->getInputShape(kInputIndices), 123 context->getOutputBuffer<uint8_t>(kOutputTensor)); 124 default: 125 NN_RET_CHECK_FAIL() << "Unsupported tensor type for operation " << kOperationName; 126 } 127 } 128 129 } // namespace gather 130 131 NN_REGISTER_OPERATION(GATHER, gather::kOperationName, gather::validate, gather::prepare, 132 gather::execute); 133 134 } // namespace nn 135 } // namespace android 136
