95 lines
4.7 KiB
C++
95 lines
4.7 KiB
C++
/* Copyright 2020 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TENSORFLOW_LITE_MICRO_KERNELS_CONV_H_
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#define TENSORFLOW_LITE_MICRO_KERNELS_CONV_H_
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#include "tensorflow/lite/c/builtin_op_data.h"
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#include "tensorflow/lite/c/common.h"
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#include "tensorflow/lite/micro/kernels/kernel_runner.h"
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#include "tensorflow/lite/micro/kernels/micro_ops.h"
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#include "tensorflow/lite/micro/test_helpers.h"
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#include "tensorflow/lite/micro/testing/micro_test.h"
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namespace tflite {
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namespace testing {
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TfLiteStatus InvokeConv(TfLiteTensor* tensors, int tensors_size,
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int output_length, TfLiteConvParams* conv_params,
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TfLiteRegistration registration, float* output_data);
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TfLiteStatus InvokeConv(TfLiteTensor* tensors, int tensors_size,
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int output_length, TfLiteConvParams* conv_params,
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TfLiteRegistration registration, int8_t* output_data);
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TfLiteStatus InvokeConv(TfLiteTensor* tensors, int tensors_size,
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int output_length, TfLiteConvParams* conv_params,
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TfLiteRegistration registration, uint8_t* output_data);
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TfLiteStatus ValidateConvGoldens(TfLiteTensor* tensors, int tensors_size,
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const float* expected_output_data,
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int output_length,
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TfLiteConvParams* conv_params,
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TfLiteRegistration registration,
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float* output_data, float tolerance = 1e-5);
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TfLiteStatus ValidateConvGoldens(TfLiteTensor* tensors, int tensors_size,
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const int8_t* expected_output_data,
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int output_length,
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TfLiteConvParams* conv_params,
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TfLiteRegistration registration,
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int8_t* output_data, float tolerance = 1e-5);
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TfLiteStatus ValidateConvGoldens(TfLiteTensor* tensors, int tensors_size,
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const uint8_t* expected_output_data,
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int output_length,
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TfLiteConvParams* conv_params,
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TfLiteRegistration registration,
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uint8_t* output_data, float tolerance = 1e-5);
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TfLiteStatus TestConvFloat(const int* input_dims_data, const float* input_data,
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const int* filter_dims_data,
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const float* filter_data, const int* bias_dims_data,
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const float* bias_data, const int* output_dims_data,
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const float* expected_output_data,
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TfLiteConvParams* conv_params,
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TfLiteRegistration registration, float* output_data);
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TfLiteStatus TestConvQuantizedPerLayer(
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const int* input_dims_data, const float* input_data,
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uint8_t* input_quantized, float input_scale, const int* filter_dims_data,
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const float* filter_data, uint8_t* filter_quantized, float filter_scale,
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const int* bias_dims_data, const float* bias_data, int32_t* bias_quantized,
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const int* output_dims_data, const float* expected_output_data,
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uint8_t* expected_output_quantized, float output_scale,
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TfLiteConvParams* conv_params, TfLiteRegistration registration,
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uint8_t* output_data);
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TfLiteStatus TestConvQuantizedPerChannel(
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const int* input_dims_data, const float* input_data,
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int8_t* input_quantized, float input_scale, int input_zero_point,
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const int* filter_dims_data, const float* filter_data,
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int8_t* filter_data_quantized, const int* bias_dims_data,
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const float* bias_data, int32_t* bias_data_quantized, float* bias_scales,
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int* bias_zero_points, const int* output_dims_data,
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const float* expected_output_data, int8_t* expected_output_data_quantized,
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float output_scale, int output_zero_point, TfLiteConvParams* conv_params,
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TfLiteRegistration registration, int8_t* output_data);
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} // namespace testing
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} // namespace tflite
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#endif // TENSORFLOW_LITE_MICRO_KERNELS_CONV_H_
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