1 /* Copyright 2020 The TensorFlow Authors. All Rights Reserved. 2 3 Licensed under the Apache License, Version 2.0 (the "License"); 4 you may not use this file except in compliance with the License. 5 You may obtain a copy of the License at 6 7 http://www.apache.org/licenses/LICENSE-2.0 8 9 Unless required by applicable law or agreed to in writing, software 10 distributed under the License is distributed on an "AS IS" BASIS, 11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 See the License for the specific language governing permissions and 13 limitations under the License. 14 ==============================================================================*/ 15 16 #ifndef TENSORFLOW_LITE_DELEGATES_GPU_COMMON_OBJECT_READER_H_ 17 #define TENSORFLOW_LITE_DELEGATES_GPU_COMMON_OBJECT_READER_H_ 18 19 #include <cstdint> 20 #include <vector> 21 22 #include "fp16.h" // from @FP16 23 #include "absl/container/flat_hash_map.h" 24 #include "tensorflow/lite/c/common.h" 25 #include "tensorflow/lite/delegates/gpu/common/model.h" 26 #include "tensorflow/lite/delegates/gpu/common/model_builder_helper.h" 27 #include "tensorflow/lite/delegates/gpu/common/status.h" 28 #include "tensorflow/lite/kernels/internal/utils/sparsity_format_converter.h" 29 #include "tensorflow/lite/kernels/kernel_util.h" 30 31 namespace tflite { 32 namespace gpu { 33 34 // If quantized tensors exist in the graph & quant_conversion_map is non-null, 35 // the mapping between the original tensors (fixed-point) & GPU values (fp) is 36 // stored in quant_conversion_map. 37 class ObjectReader { 38 public: 39 static absl::Status ReadNonConstantTensor( 40 TfLiteContext* context, absl::flat_hash_map<int, Value*>* tensor_to_value, 41 absl::flat_hash_map<int, int>* quant_conversion_map, GraphFloat32* graph, 42 uint32_t tensor_idx, Value** value = nullptr); 43 44 ObjectReader(GraphFloat32* graph, TfLiteContext* context, 45 const TfLiteNode* node, 46 absl::flat_hash_map<int, Value*>* tensor_to_value, 47 absl::flat_hash_map<int, int>* quant_conversion_map = nullptr) graph_(graph)48 : graph_(graph), 49 context_(context), 50 node_(node), 51 tensor_to_value_(tensor_to_value), 52 quant_conversion_map_(quant_conversion_map) {} 53 54 absl::Status ReadValue(uint32_t idx, Value** value); 55 56 absl::Status ReadValueByTensorIdx(uint32_t tensor_idx, Value** value); 57 58 int GetNumberOfRuntimeInputs() const; 59 60 absl::Status GetTensorId(uint32_t input_id, int* tensor_id) const; 61 62 absl::Status GetTensorDims(uint32_t idx, TfLiteIntArray* dimensions) const; 63 64 template <typename TensorT> ReadTensor(uint32_t index,TensorT * tensor)65 absl::Status ReadTensor(uint32_t index, TensorT* tensor) const { 66 if (index < 0 || index >= node_->inputs->size) { 67 // If larger, this can be an older model with fewer input tensors than the 68 // current implementation. 69 return absl::OutOfRangeError("Invalid data index found."); 70 } 71 const int32_t tensor_id = node_->inputs->data[index]; 72 if (tensor_id < 0) { 73 return absl::InvalidArgumentError( 74 "Invalid data index found. Possibly an unset optional tensor is " 75 "being read."); 76 } 77 const TfLiteTensor* tflite_tensor = context_->tensors + tensor_id; 78 tensor->data.resize(NumElements(tflite_tensor)); 79 if (tflite_tensor->sparsity) { 80 std::vector<int> dims; 81 dims.reserve(tflite_tensor->dims->size); 82 for (int i = 0; i < tflite_tensor->dims->size; ++i) { 83 dims.push_back(tflite_tensor->dims->data[i]); 84 } 85 switch (tflite_tensor->type) { 86 case kTfLiteFloat32: { 87 internal::sparsity::FormatConverter<float> converter( 88 dims, *tflite_tensor->sparsity); 89 converter.SparseToDense( 90 static_cast<const float*>(tflite_tensor->data.data)); 91 const std::vector<float> out = converter.GetData(); 92 std::memcpy(&tensor->data[0], out.data(), out.size() * sizeof(float)); 93 break; 94 } 95 case kTfLiteFloat16: { 96 internal::sparsity::FormatConverter<Eigen::half> converter( 97 dims, *tflite_tensor->sparsity); 98 converter.SparseToDense( 99 static_cast<const Eigen::half*>(tflite_tensor->data.data)); 100 const std::vector<Eigen::half> out = converter.GetData(); 101 std::transform(out.begin(), out.end(), tensor->data.begin(), 102 [](const Eigen::half& x) { 103 return fp16_ieee_to_fp32_value( 104 Eigen::numext::bit_cast<uint16_t>(x)); 105 }); 106 break; 107 } 108 default: { 109 return absl::InvalidArgumentError( 110 "Unexpected data type in sparse tensor"); 111 } 112 } 113 } else { 114 RETURN_IF_ERROR(CreateVectorCopyData(*tflite_tensor, &tensor->data[0])); 115 } 116 117 // Axis and data layout depend on operation this tensor is used in. So, 118 // postpone resolutions until operations are parsed. 119 tensor->id = tensor_id; 120 return SetAllDimensions(tflite_tensor->dims, &tensor->shape); 121 } 122 123 absl::Status AddOutput(const Node* node, int id); 124 125 absl::Status AddOutputs(const Node* node); 126 127 absl::Status AddInput(const Node* node, uint32_t idx); 128 129 absl::Status AddUpdate(const Node* node, uint32_t idx); 130 131 TfLiteTensor* GetInputTensor(int index) const; 132 133 TfLiteTensor* GetOutputTensor(int index) const; 134 135 absl::Status VerifyInputsConstsOutputs(const TfLiteNode* node, 136 int runtime_inputs, int const_inputs, 137 int outputs); 138 139 private: 140 GraphFloat32* graph_; 141 TfLiteContext* context_; 142 const TfLiteNode* node_; 143 absl::flat_hash_map<int, Value*>* tensor_to_value_; 144 absl::flat_hash_map<int, int>* quant_conversion_map_; 145 }; 146 147 } // namespace gpu 148 } // namespace tflite 149 150 #endif // TENSORFLOW_LITE_DELEGATES_GPU_COMMON_OBJECT_READER_H_ 151