xref: /aosp_15_r20/external/tensorflow/tensorflow/lite/kernels/internal/reference/sparse_ops/fully_connected.h (revision b6fb3261f9314811a0f4371741dbb8839866f948)
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 #ifndef TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_SPARSE_OPS_FULLY_CONNECTED_H_
16 #define TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_SPARSE_OPS_FULLY_CONNECTED_H_
17 
18 #include "tensorflow/lite/kernels/internal/reference/fully_connected.h"
19 #include "tensorflow/lite/kernels/internal/utils/sparsity_format_converter.h"
20 
21 namespace tflite {
22 namespace reference_ops {
23 
24 // Convert weights to dense format and run dense fully connected.
FullyConnectedSparseWeight(const TfLiteSparsity & sparsity,const FullyConnectedParams & params,const RuntimeShape & input_shape,const float * input_data,const RuntimeShape & weights_shape,const float * weights_data,const RuntimeShape & bias_shape,const float * bias_data,const RuntimeShape & output_shape,float * output_data)25 inline void FullyConnectedSparseWeight(
26     const TfLiteSparsity& sparsity, const FullyConnectedParams& params,
27     const RuntimeShape& input_shape, const float* input_data,
28     const RuntimeShape& weights_shape, const float* weights_data,
29     const RuntimeShape& bias_shape, const float* bias_data,
30     const RuntimeShape& output_shape, float* output_data) {
31   std::vector<int> weights_shape_vector(weights_shape.DimensionsCount());
32   for (int i = 0; i < weights_shape.DimensionsCount(); i++) {
33     weights_shape_vector[i] = weights_shape.Dims(i);
34   }
35   tflite::internal::sparsity::FormatConverter<float> converter(
36       weights_shape_vector, sparsity);
37   converter.SparseToDense(weights_data);
38   const std::vector<float>& dense_weights_data = converter.GetData();
39   FullyConnected(params, input_shape, input_data, weights_shape,
40                  dense_weights_data.data(), bias_shape, bias_data, output_shape,
41                  output_data);
42 }
43 
44 }  // namespace reference_ops
45 }  // namespace tflite
46 #endif  // TENSORFLOW_LITE_KERNELS_INTERNAL_REFERENCE_SPARSE_OPS_FULLY_CONNECTED_H_
47