| /* Copyright 2019 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_COMPARISONS_H_ |
| #define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_COMPARISONS_H_ |
| |
| #include "tensorflow/lite/c/common.h" |
| #include "tensorflow/lite/kernels/internal/common.h" |
| #include "tensorflow/lite/kernels/internal/types.h" |
| #include "tensorflow/lite/string_util.h" |
| |
| namespace tflite { |
| |
| namespace reference_ops { |
| |
| template <typename T> |
| inline bool EqualFn(T lhs, T rhs) { |
| return lhs == rhs; |
| } |
| |
| template <typename T> |
| inline bool NotEqualFn(T lhs, T rhs) { |
| return lhs != rhs; |
| } |
| |
| template <typename T> |
| inline bool GreaterFn(T lhs, T rhs) { |
| return lhs > rhs; |
| } |
| template <typename T> |
| inline bool GreaterEqualFn(T lhs, T rhs) { |
| return lhs >= rhs; |
| } |
| template <typename T> |
| inline bool LessFn(T lhs, T rhs) { |
| return lhs < rhs; |
| } |
| template <typename T> |
| inline bool LessEqualFn(T lhs, T rhs) { |
| return lhs <= rhs; |
| } |
| |
| inline bool StringRefEqualFn(const StringRef& lhs, const StringRef& rhs) { |
| if (lhs.len != rhs.len) return false; |
| for (int i = 0; i < lhs.len; ++i) { |
| if (lhs.str[i] != rhs.str[i]) return false; |
| } |
| return true; |
| } |
| |
| inline bool StringRefNotEqualFn(const StringRef& lhs, const StringRef& rhs) { |
| return !StringRefEqualFn(lhs, rhs); |
| } |
| |
| template <typename T> |
| using ComparisonFn = bool (*)(T, T); |
| |
| template <typename T, ComparisonFn<T> F> |
| inline void ComparisonImpl( |
| const ComparisonParams& op_params, const RuntimeShape& input1_shape, |
| const T* input1_data, const RuntimeShape& input2_shape, |
| const T* input2_data, const RuntimeShape& output_shape, bool* output_data) { |
| const int64_t flatsize = |
| MatchingFlatSize(input1_shape, input2_shape, output_shape); |
| for (int64_t i = 0; i < flatsize; ++i) { |
| output_data[i] = F(input1_data[i], input2_data[i]); |
| } |
| } |
| |
| inline void ComparisonStringImpl(bool (*F)(const StringRef&, const StringRef&), |
| const RuntimeShape& input1_shape, |
| const TfLiteTensor* input1, |
| const RuntimeShape& input2_shape, |
| const TfLiteTensor* input2, |
| const RuntimeShape& output_shape, |
| bool* output_data) { |
| const int64_t flatsize = |
| MatchingFlatSize(input1_shape, input2_shape, output_shape); |
| for (int64_t i = 0; i < flatsize; ++i) { |
| const auto lhs = GetString(input1, i); |
| const auto rhs = GetString(input2, i); |
| output_data[i] = F(lhs, rhs); |
| } |
| } |
| |
| template <ComparisonFn<float> F> |
| inline void Comparison(const ComparisonParams& op_params, |
| const RuntimeShape& input1_shape, |
| const float* input1_data, |
| const RuntimeShape& input2_shape, |
| const float* input2_data, |
| const RuntimeShape& output_shape, bool* output_data) { |
| ComparisonImpl<float, F>(op_params, input1_shape, input1_data, input2_shape, |
| input2_data, output_shape, output_data); |
| } |
| |
| template <typename T, ComparisonFn<int32> F> |
| inline void ComparisonWithScaling( |
| const ComparisonParams& op_params, const RuntimeShape& input1_shape, |
| const T* input1_data, const RuntimeShape& input2_shape, |
| const T* input2_data, const RuntimeShape& output_shape, bool* output_data) { |
| int left_shift = op_params.left_shift; |
| int32 input1_offset = op_params.input1_offset; |
| int32 input1_multiplier = op_params.input1_multiplier; |
| int input1_shift = op_params.input1_shift; |
| int32 input2_offset = op_params.input2_offset; |
| int32 input2_multiplier = op_params.input2_multiplier; |
| int input2_shift = op_params.input2_shift; |
| |
| const int64_t flatsize = |
| MatchingFlatSize(input1_shape, input2_shape, output_shape); |
| for (int64_t i = 0; i < flatsize; ++i) { |
| const int32 input1_val = input1_offset + input1_data[i]; |
| const int32 input2_val = input2_offset + input2_data[i]; |
| const int32 shifted_input1_val = input1_val * (1 << left_shift); |
| const int32 shifted_input2_val = input2_val * (1 << left_shift); |
| const int32 scaled_input1_val = |
| MultiplyByQuantizedMultiplierSmallerThanOneExp( |
| shifted_input1_val, input1_multiplier, input1_shift); |
| const int32 scaled_input2_val = |
| MultiplyByQuantizedMultiplierSmallerThanOneExp( |
| shifted_input2_val, input2_multiplier, input2_shift); |
| output_data[i] = F(scaled_input1_val, scaled_input2_val); |
| } |
| } |
| |
| struct BroadcastComparison4DSlowCommon { |
| const RuntimeShape output_shape; |
| NdArrayDesc<4> desc1; |
| NdArrayDesc<4> desc2; |
| }; |
| |
| inline BroadcastComparison4DSlowCommon BroadcastComparison4DSlowPreprocess( |
| const RuntimeShape& unextended_input1_shape, |
| const RuntimeShape& unextended_input2_shape, |
| const RuntimeShape& unextended_output_shape) { |
| TFLITE_DCHECK_LE(unextended_input1_shape.DimensionsCount(), 4); |
| TFLITE_DCHECK_LE(unextended_input2_shape.DimensionsCount(), 4); |
| TFLITE_DCHECK_LE(unextended_output_shape.DimensionsCount(), 4); |
| NdArrayDesc<4> desc1; |
| NdArrayDesc<4> desc2; |
| NdArrayDescsForElementwiseBroadcast(unextended_input1_shape, |
| unextended_input2_shape, &desc1, &desc2); |
| return {RuntimeShape::ExtendedShape(4, unextended_output_shape), desc1, |
| desc2}; |
| } |
| |
| template <typename T, ComparisonFn<T> F> |
| inline void BroadcastComparison4DSlowImpl( |
| const ComparisonParams& op_params, |
| const RuntimeShape& unextended_input1_shape, const T* input1_data, |
| const RuntimeShape& unextended_input2_shape, const T* input2_data, |
| const RuntimeShape& unextended_output_shape, bool* output_data) { |
| const BroadcastComparison4DSlowCommon dims = |
| BroadcastComparison4DSlowPreprocess(unextended_input1_shape, |
| unextended_input2_shape, |
| unextended_output_shape); |
| |
| for (int b = 0; b < dims.output_shape.Dims(0); ++b) { |
| for (int y = 0; y < dims.output_shape.Dims(1); ++y) { |
| for (int x = 0; x < dims.output_shape.Dims(2); ++x) { |
| for (int c = 0; c < dims.output_shape.Dims(3); ++c) { |
| output_data[Offset(dims.output_shape, b, y, x, c)] = |
| F(input1_data[SubscriptToIndex(dims.desc1, b, y, x, c)], |
| input2_data[SubscriptToIndex(dims.desc2, b, y, x, c)]); |
| } |
| } |
| } |
| } |
| } |
| |
| inline void BroadcastComparison4DSlowStringImpl( |
| bool (*F)(const StringRef&, const StringRef&), |
| const RuntimeShape& unextended_input1_shape, const TfLiteTensor* input1, |
| const RuntimeShape& unextended_input2_shape, const TfLiteTensor* input2, |
| const RuntimeShape& unextended_output_shape, bool* output_data) { |
| const BroadcastComparison4DSlowCommon dims = |
| BroadcastComparison4DSlowPreprocess(unextended_input1_shape, |
| unextended_input2_shape, |
| unextended_output_shape); |
| |
| for (int b = 0; b < dims.output_shape.Dims(0); ++b) { |
| for (int y = 0; y < dims.output_shape.Dims(1); ++y) { |
| for (int x = 0; x < dims.output_shape.Dims(2); ++x) { |
| for (int c = 0; c < dims.output_shape.Dims(3); ++c) { |
| const auto lhs = |
| GetString(input1, SubscriptToIndex(dims.desc1, b, y, x, c)); |
| const auto rhs = |
| GetString(input2, SubscriptToIndex(dims.desc2, b, y, x, c)); |
| output_data[Offset(dims.output_shape, b, y, x, c)] = F(lhs, rhs); |
| } |
| } |
| } |
| } |
| } |
| |
| template <ComparisonFn<float> F> |
| inline void BroadcastComparison4DSlow(const ComparisonParams& op_params, |
| const RuntimeShape& input1_shape, |
| const float* input1_data, |
| const RuntimeShape& input2_shape, |
| const float* input2_data, |
| const RuntimeShape& output_shape, |
| bool* output_data) { |
| BroadcastComparison4DSlowImpl<float, F>(op_params, input1_shape, input1_data, |
| input2_shape, input2_data, |
| output_shape, output_data); |
| } |
| |
| template <typename T, ComparisonFn<int32> F> |
| inline void BroadcastComparison4DSlowWithScaling( |
| const ComparisonParams& op_params, |
| const RuntimeShape& unextended_input1_shape, const T* input1_data, |
| const RuntimeShape& unextended_input2_shape, const T* input2_data, |
| const RuntimeShape& unextended_output_shape, bool* output_data) { |
| const BroadcastComparison4DSlowCommon dims = |
| BroadcastComparison4DSlowPreprocess(unextended_input1_shape, |
| unextended_input2_shape, |
| unextended_output_shape); |
| |
| int left_shift = op_params.left_shift; |
| int32 input1_offset = op_params.input1_offset; |
| int32 input1_multiplier = op_params.input1_multiplier; |
| int input1_shift = op_params.input1_shift; |
| int32 input2_offset = op_params.input2_offset; |
| int32 input2_multiplier = op_params.input2_multiplier; |
| int input2_shift = op_params.input2_shift; |
| |
| for (int b = 0; b < dims.output_shape.Dims(0); ++b) { |
| for (int y = 0; y < dims.output_shape.Dims(1); ++y) { |
| for (int x = 0; x < dims.output_shape.Dims(2); ++x) { |
| for (int c = 0; c < dims.output_shape.Dims(3); ++c) { |
| const int32 input1_val = |
| input1_offset + |
| input1_data[SubscriptToIndex(dims.desc1, b, y, x, c)]; |
| const int32 input2_val = |
| input2_offset + |
| input2_data[SubscriptToIndex(dims.desc2, b, y, x, c)]; |
| const int32 shifted_input1_val = input1_val * (1 << left_shift); |
| const int32 shifted_input2_val = input2_val * (1 << left_shift); |
| const int32 scaled_input1_val = |
| MultiplyByQuantizedMultiplierSmallerThanOneExp( |
| shifted_input1_val, input1_multiplier, input1_shift); |
| const int32 scaled_input2_val = |
| MultiplyByQuantizedMultiplierSmallerThanOneExp( |
| shifted_input2_val, input2_multiplier, input2_shift); |
| output_data[Offset(dims.output_shape, b, y, x, c)] = |
| F(scaled_input1_val, scaled_input2_val); |
| } |
| } |
| } |
| } |
| } |
| |
| #define TFLITE_COMPARISON_OP(name) \ |
| inline void name(const ComparisonParams& op_params, \ |
| const RuntimeShape& input1_shape, const float* input1_data, \ |
| const RuntimeShape& input2_shape, const float* input2_data, \ |
| const RuntimeShape& output_shape, bool* output_data) { \ |
| Comparison<name##Fn>(op_params, input1_shape, input1_data, input2_shape, \ |
| input2_data, output_shape, output_data); \ |
| } \ |
| template <typename T> \ |
| inline void name##NoScaling( \ |
| const ComparisonParams& op_params, const RuntimeShape& input1_shape, \ |
| const T* input1_data, const RuntimeShape& input2_shape, \ |
| const T* input2_data, const RuntimeShape& output_shape, \ |
| bool* output_data) { \ |
| ComparisonImpl<T, name##Fn>(op_params, input1_shape, input1_data, \ |
| input2_shape, input2_data, output_shape, \ |
| output_data); \ |
| } \ |
| template <typename T> \ |
| inline void name##WithScaling( \ |
| const ComparisonParams& op_params, const RuntimeShape& input1_shape, \ |
| const T* input1_data, const RuntimeShape& input2_shape, \ |
| const T* input2_data, const RuntimeShape& output_shape, \ |
| bool* output_data) { \ |
| ComparisonWithScaling<T, name##Fn>(op_params, input1_shape, input1_data, \ |
| input2_shape, input2_data, \ |
| output_shape, output_data); \ |
| } \ |
| template <typename T> \ |
| inline void Broadcast4DSlow##name##NoScaling( \ |
| const ComparisonParams& op_params, const RuntimeShape& input1_shape, \ |
| const T* input1_data, const RuntimeShape& input2_shape, \ |
| const T* input2_data, const RuntimeShape& output_shape, \ |
| bool* output_data) { \ |
| BroadcastComparison4DSlowImpl<T, name##Fn>( \ |
| op_params, input1_shape, input1_data, input2_shape, input2_data, \ |
| output_shape, output_data); \ |
| } \ |
| inline void Broadcast4DSlow##name( \ |
| const ComparisonParams& op_params, const RuntimeShape& input1_shape, \ |
| const float* input1_data, const RuntimeShape& input2_shape, \ |
| const float* input2_data, const RuntimeShape& output_shape, \ |
| bool* output_data) { \ |
| BroadcastComparison4DSlow<name##Fn>(op_params, input1_shape, input1_data, \ |
| input2_shape, input2_data, \ |
| output_shape, output_data); \ |
| } \ |
| template <typename T> \ |
| inline void Broadcast4DSlow##name##WithScaling( \ |
| const ComparisonParams& op_params, const RuntimeShape& input1_shape, \ |
| const T* input1_data, const RuntimeShape& input2_shape, \ |
| const T* input2_data, const RuntimeShape& output_shape, \ |
| bool* output_data) { \ |
| BroadcastComparison4DSlowWithScaling<T, name##Fn>( \ |
| op_params, input1_shape, input1_data, input2_shape, input2_data, \ |
| output_shape, output_data); \ |
| } |
| TFLITE_COMPARISON_OP(Equal); |
| TFLITE_COMPARISON_OP(NotEqual); |
| TFLITE_COMPARISON_OP(Greater); |
| TFLITE_COMPARISON_OP(GreaterEqual); |
| TFLITE_COMPARISON_OP(Less); |
| TFLITE_COMPARISON_OP(LessEqual); |
| #undef TFLITE_COMPARISON_OP |
| |
| } // namespace reference_ops |
| } // namespace tflite |
| |
| #endif // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_COMPARISONS_H_ |
