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| 1 | +/* Copyright 2021 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 | +#include <stdint.h> |
| 17 | + |
| 18 | +#include <algorithm> |
| 19 | + |
| 20 | +#include "tensorflow/lite/c/builtin_op_data.h" |
| 21 | +#include "tensorflow/lite/c/common.h" |
| 22 | +#include "tensorflow/lite/kernels/internal/tensor.h" |
| 23 | +#include "tensorflow/lite/kernels/internal/tensor_ctypes.h" |
| 24 | +#include "tensorflow/lite/kernels/kernel_util.h" |
| 25 | + |
| 26 | +namespace tflite { |
| 27 | +namespace ops { |
| 28 | +namespace builtin { |
| 29 | +namespace bucketize { |
| 30 | +namespace { |
| 31 | + |
| 32 | +constexpr int kInputTensor = 0; |
| 33 | +constexpr int kOutputTensor = 0; |
| 34 | + |
| 35 | +struct OpData { |
| 36 | + // boundaries array is owned by the buffer housing TfLiteBucketizeParams. |
| 37 | + const float* boundaries; |
| 38 | + int num_boundaries; |
| 39 | +}; |
| 40 | + |
| 41 | +void* Init(TfLiteContext* context, const char* buffer, size_t length) { |
| 42 | + auto* op_data = new OpData(); |
| 43 | + const auto* params = reinterpret_cast<const TfLiteBucketizeParams*>(buffer); |
| 44 | + |
| 45 | + op_data->boundaries = params->boundaries; |
| 46 | + op_data->num_boundaries = params->num_boundaries; |
| 47 | + return op_data; |
| 48 | +} |
| 49 | + |
| 50 | +void Free(TfLiteContext* context, void* buffer) { |
| 51 | + delete reinterpret_cast<OpData*>(buffer); |
| 52 | +} |
| 53 | + |
| 54 | +TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) { |
| 55 | + TF_LITE_ENSURE_EQ(context, NumInputs(node), 1); |
| 56 | + TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1); |
| 57 | + OpData* opdata = reinterpret_cast<OpData*>(node->user_data); |
| 58 | + if (!std::is_sorted(opdata->boundaries, |
| 59 | + opdata->boundaries + opdata->num_boundaries)) { |
| 60 | + TF_LITE_KERNEL_LOG(context, "Expected sorted boundaries"); |
| 61 | + return kTfLiteError; |
| 62 | + } |
| 63 | + |
| 64 | + const TfLiteTensor* input; |
| 65 | + TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input)); |
| 66 | + |
| 67 | + if (input->type != kTfLiteInt32 && input->type != kTfLiteFloat32 && |
| 68 | + input->type != kTfLiteInt64 && input->type != kTfLiteFloat64) { |
| 69 | + TF_LITE_KERNEL_LOG(context, "Type '%s' is not supported by bucketize.", |
| 70 | + TfLiteTypeGetName(input->type)); |
| 71 | + return kTfLiteError; |
| 72 | + } |
| 73 | + |
| 74 | + TfLiteTensor* output; |
| 75 | + TF_LITE_ENSURE_OK(context, |
| 76 | + GetOutputSafe(context, node, kOutputTensor, &output)); |
| 77 | + output->type = kTfLiteInt32; |
| 78 | + |
| 79 | + TfLiteIntArray* output_shape = TfLiteIntArrayCopy(input->dims); |
| 80 | + return context->ResizeTensor(context, output, output_shape); |
| 81 | +} |
| 82 | + |
| 83 | +template <typename T> |
| 84 | +inline void Bucketize(const RuntimeShape& input_shape, const T* input_data, |
| 85 | + const float* boundaries, int num_boundaries, |
| 86 | + const RuntimeShape& output_shape, int32_t* output_data) { |
| 87 | + const int flat_size = MatchingFlatSize(input_shape, output_shape); |
| 88 | + |
| 89 | + for (int i = 0; i < flat_size; i++) { |
| 90 | + auto first_bigger_it = std::upper_bound( |
| 91 | + boundaries, boundaries + num_boundaries, input_data[i]); |
| 92 | + output_data[i] = first_bigger_it - boundaries; |
| 93 | + } |
| 94 | +} |
| 95 | + |
| 96 | +template <typename T> |
| 97 | +TfLiteStatus BucketizeImpl(TfLiteContext* context, TfLiteNode* node) { |
| 98 | + const TfLiteTensor* input; |
| 99 | + TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input)); |
| 100 | + OpData* opdata = reinterpret_cast<OpData*>(node->user_data); |
| 101 | + TfLiteTensor* output; |
| 102 | + TF_LITE_ENSURE_OK(context, |
| 103 | + GetOutputSafe(context, node, kOutputTensor, &output)); |
| 104 | + TF_LITE_ENSURE_TYPES_EQ(context, output->type, kTfLiteInt32); |
| 105 | + |
| 106 | + Bucketize<T>(GetTensorShape(input), GetTensorData<T>(input), |
| 107 | + opdata->boundaries, opdata->num_boundaries, |
| 108 | + GetTensorShape(output), GetTensorData<int32_t>(output)); |
| 109 | + |
| 110 | + return kTfLiteOk; |
| 111 | +} |
| 112 | + |
| 113 | +TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) { |
| 114 | + const TfLiteTensor* input; |
| 115 | + TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, kInputTensor, &input)); |
| 116 | + |
| 117 | + switch (input->type) { |
| 118 | + case kTfLiteFloat32: { |
| 119 | + return BucketizeImpl<float>(context, node); |
| 120 | + } |
| 121 | + case kTfLiteFloat64: { |
| 122 | + return BucketizeImpl<double>(context, node); |
| 123 | + } |
| 124 | + case kTfLiteInt32: { |
| 125 | + return BucketizeImpl<int32_t>(context, node); |
| 126 | + } |
| 127 | + case kTfLiteInt64: { |
| 128 | + return BucketizeImpl<int64_t>(context, node); |
| 129 | + } |
| 130 | + default: { |
| 131 | + TF_LITE_KERNEL_LOG(context, "Type '%s' is not supported by bucketize.", |
| 132 | + TfLiteTypeGetName(input->type)); |
| 133 | + return kTfLiteError; |
| 134 | + } |
| 135 | + } |
| 136 | +} |
| 137 | + |
| 138 | +} // namespace |
| 139 | +} // namespace bucketize |
| 140 | + |
| 141 | +TfLiteRegistration* Register_BUCKETIZE() { |
| 142 | + static TfLiteRegistration r = {bucketize::Init, bucketize::Free, |
| 143 | + bucketize::Prepare, bucketize::Eval}; |
| 144 | + return &r; |
| 145 | +} |
| 146 | + |
| 147 | +} // namespace builtin |
| 148 | +} // namespace ops |
| 149 | +} // namespace tflite |
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