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37 changes: 37 additions & 0 deletions
37
edgeimpulse/edge-impulse-sdk/tensorflow/lite/kernels/internal/reduce_common.h
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,37 @@ | ||
| /* Copyright 2022 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_REDUCE_COMMON_H_ | ||
| #define TENSORFLOW_LITE_KERNELS_INTERNAL_REDUCE_COMMON_H_ | ||
|
|
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| namespace tflite { | ||
| namespace ops { | ||
| namespace builtin { | ||
| namespace reduce { | ||
|
|
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| enum ReduceType { | ||
| kSum, | ||
| kProd, | ||
| kMax, | ||
| kMin, | ||
| kAny, | ||
| kAll, | ||
| }; | ||
|
|
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| } // namespace reduce | ||
| } // namespace builtin | ||
| } // namespace ops | ||
| } // namespace tflite | ||
|
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| #endif // TENSORFLOW_LITE_KERNELS_INTERNAL_REDUCE_COMMON_H_ |
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77 changes: 77 additions & 0 deletions
77
edgeimpulse/edge-impulse-sdk/tensorflow/lite/kernels/internal/reference/scatter_nd.h
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,77 @@ | ||
| /* Copyright 2018 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_SCATTER_ND_H_ | ||
| #define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_SCATTER_ND_H_ | ||
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| #include "edge-impulse-sdk/tensorflow/lite/kernels/internal/common.h" | ||
| #include "edge-impulse-sdk/tensorflow/lite/kernels/internal/types.h" | ||
| #include "edge-impulse-sdk/tensorflow/lite/kernels/internal/tensor_ctypes.h" | ||
| #include "edge-impulse-sdk/tensorflow/lite/kernels/kernel_util.h" | ||
| #include "edge-impulse-sdk/tensorflow/lite/micro/kernels/kernel_util.h" | ||
|
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| namespace tflite { | ||
|
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| namespace reference_ops { | ||
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| template <typename IndicesT, typename UpdatesT> | ||
| inline TfLiteStatus ScatterNd(const RuntimeShape& indices_shape, | ||
| const IndicesT* indices_data, | ||
| const RuntimeShape& updates_shape, | ||
| const UpdatesT* updates_data, | ||
| const RuntimeShape& output_shape, | ||
| UpdatesT* output_data) { | ||
| int n_slices = 1; | ||
| int slice_size = 1; | ||
| const int outer_dims = indices_shape.DimensionsCount() - 1; | ||
| const int indices_nd = indices_shape.Dims(outer_dims); | ||
| const int updates_dims = updates_shape.DimensionsCount(); | ||
| for (int i = 0; i < outer_dims; ++i) { | ||
| n_slices *= indices_shape.Dims(i); | ||
| } | ||
| for (int i = outer_dims; i < updates_dims; ++i) { | ||
| slice_size *= updates_shape.Dims(i); | ||
| } | ||
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| int output_flat_size = output_shape.FlatSize(); | ||
| int remain_flat_size = output_flat_size; | ||
| std::vector<int> dims_to_count(indices_nd, 0); | ||
| for (int i = 0; i < indices_nd; ++i) { | ||
| dims_to_count[i] = remain_flat_size / output_shape.Dims(i); | ||
| remain_flat_size = dims_to_count[i]; | ||
| } | ||
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| if (n_slices * slice_size > updates_shape.FlatSize()) { | ||
| return kTfLiteError; | ||
| } | ||
| memset(output_data, 0, sizeof(UpdatesT) * output_flat_size); | ||
| for (int i = 0; i < n_slices; ++i) { | ||
| int to_pos = 0; | ||
| for (int j = 0; j < indices_nd; ++j) { | ||
| IndicesT idx = indices_data[i * indices_nd + j]; | ||
| to_pos += idx * dims_to_count[j]; | ||
| } | ||
| if (to_pos < 0 || to_pos + slice_size > output_flat_size) { | ||
| return kTfLiteError; | ||
| } | ||
| for (int j = 0; j < slice_size; j++) { | ||
| output_data[to_pos + j] += updates_data[i * slice_size + j]; | ||
| } | ||
| } | ||
| return kTfLiteOk; | ||
| } | ||
|
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| } // namespace reference_ops | ||
| } // namespace tflite | ||
| #endif // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_SCATTER_ND_H_ |
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