update example files of micro

mindspore/lite/micro/example/mnist_stm32f746/mnist_stm32f746/benchmark/benchmark.cc

@@ -24,6 +24,7 @@
 #include "include/errorcode.h"
 
 #include "load_input.h"
+#include "calib_output.h"
 
 using namespace mindspore;
 
@@ -34,8 +35,9 @@ void usage() {
     "args[1]: inputs binary file\n"
     "args[2]: model weight binary file\n"
     "args[3]: loop count for performance test\n"
-    "args[4]: runtime thread num\n"
-    "args[5]: runtime thread bind mode\n\n");
+    "args[4]: calibration file\n"
+    "args[5]: runtime thread num\n"
+    "args[6]: runtime thread bind mode\n\n");
 }
 
 uint64_t GetTimeUs() {
@@ -111,15 +113,15 @@ int main(int argc, const char **argv) {
   }
 
   lite::Context *context = nullptr;
-  if (argc >= 6) {
+  if (argc >= 7) {
     // config benchmark context
     context = new (std::nothrow) lite::Context();
     if (context == nullptr) {
       return lite::RET_ERROR;
     }
-    context->thread_num_ = atoi(argv[4]);
+    context->thread_num_ = atoi(argv[5]);
     context->device_list_.resize(1);
-    context->device_list_[0] = {lite::DT_CPU, {{false, static_cast<lite::CpuBindMode>(atoi(argv[5]))}}};
+    context->device_list_[0] = {lite::DT_CPU, {{false, static_cast<lite::CpuBindMode>(atoi(argv[6]))}}};
     printf("context: ThreadNum: %d, BindMode: %d\n", context->thread_num_,
            context->device_list_[0].device_info_.cpu_device_info_.cpu_bind_mode_);
   }
@@ -167,12 +169,29 @@ int main(int argc, const char **argv) {
     return lite::RET_ERROR;
   }
 
-  Vector<String> outputs_name = session->GetOutputTensorNames();
   printf("\noutputs: \n");
+  Vector<String> outputs_name = session->GetOutputTensorNames();
+  Vector<tensor::MSTensor *> outputs;
   for (const auto &name : outputs_name) {
     auto output = session->GetOutputByTensorName(name);
+    outputs.push_back(output);
     TensorToString(output);
   }
+  if (argc >= 5) {
+    lite::Calibrator *calibrator = new (std::nothrow) lite::Calibrator();
+    if (calibrator == nullptr) {
+      return lite::RET_NULL_PTR;
+    }
+    ret = calibrator->ReadCalibData(argv[4]);
+    if (ret != lite::RET_OK) {
+      return lite::RET_ERROR;
+    }
+    ret = calibrator->CompareOutputs(outputs);
+    if (ret != lite::RET_OK) {
+      return lite::RET_ERROR;
+    }
+    delete calibrator;
+  }
   printf("========run success=======\n");
   delete session;
   session = nullptr;

mindspore/lite/micro/example/mnist_stm32f746/mnist_stm32f746/benchmark/calib_output.cc

@@ -0,0 +1,148 @@
+
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * 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.
+ */
+
+#include "calib_output.h"
+#include <fstream>
+#include <sstream>
+#include <iostream>
+#include <stdio.h>
+#include <cmath>
+
+namespace mindspore {
+namespace lite {
+constexpr float kToleranceVal = 0.0001;
+
+#define MS_ERROR_IF_NULL(ptr)            \
+  do {                                   \
+    if ((ptr) == nullptr) {              \
+      return mindspore::lite::RET_ERROR; \
+    }                                    \
+  } while (0)
+
+int Calibrator::ReadCalibData(const char *calib_data_path) {
+  std::ifstream in_file(calib_data_path);
+  if (!in_file.good()) {
+    printf("file is not exist, %s\n", calib_data_path);
+    return RET_ERROR;
+  }
+  if (!in_file.is_open()) {
+    printf("open file failed, %s\n", calib_data_path);
+    in_file.close();
+    return RET_ERROR;
+  }
+  while (!in_file.eof()) {
+    std::string line;
+    getline(in_file, line);
+    if (line.empty()) {
+      continue;
+    }
+    std::stringstream name_line(line);
+    std::string tensor_name;
+    size_t dim = 0;
+    name_line >> tensor_name >> dim;
+    size_t elements = 1;
+    for (size_t i = 0; i < dim; i++) {
+      size_t tmp_dim;
+      name_line >> tmp_dim;
+      elements *= tmp_dim;
+    }
+    getline(in_file, line);
+    std::stringstream data_line(line);
+    String name(tensor_name.c_str());
+    CalibTensor *output = new (std::nothrow) CalibTensor(name, elements);
+    MS_ERROR_IF_NULL(output);
+    float *data = output->MutableData();
+    MS_ERROR_IF_NULL(data);
+    for (size_t i = 0; i < elements; i++) {
+      data_line >> data[i];
+    }
+    calib_outputs_.push_back(output);
+  }
+  in_file.close();
+  return RET_OK;
+}
+
+template <typename T>
+float CompareData(const T *output, const float *calib, size_t elements_num) {
+  float error = 0.;
+  if (output == nullptr || calib == nullptr) {
+    printf("output or calib is nullptr\n");
+    return error;
+  }
+  for (size_t i = 0; i < elements_num; ++i) {
+    if (std::isnan(output[i]) || std::isinf(output[i]) || std::isnan(calib[i]) || std::isinf(calib[i])) {
+      printf("error, output data is nan or inf\n");
+      return error;
+    }
+    error += std::abs(output[i] - calib[i]);
+  }
+  return error;
+}
+
+int Calibrator::CompareOutputs(const Vector<tensor::MSTensor *> &outputs) const {
+  if (outputs.size() != calib_outputs_.size()) {
+    printf("error, outputs and calibs size is mismatch\n");
+    return RET_ERROR;
+  }
+  float total_error = 0;
+  size_t outputs_num = outputs.size();
+  for (size_t i = 0; i < outputs_num; ++i) {
+    tensor::MSTensor *output = outputs[i];
+    MS_ERROR_IF_NULL(output);
+    CalibTensor *calib = calib_outputs_[i];
+    MS_ERROR_IF_NULL(calib);
+    if (output->tensor_name() != calib->tensor_name()) {
+      printf("error, output tensor name is not equal to calib\n");
+      return RET_ERROR;
+    }
+    if (output->ElementsNum() != calib->ElementsNum()) {
+      printf("error, output elements num is not equal to calib\n");
+      return RET_ERROR;
+    }
+    switch (output->data_type()) {
+      case TypeId::kNumberTypeFloat:
+      case TypeId::kNumberTypeFloat32: {
+        total_error += CompareData(static_cast<float *>(output->data()), calib->MutableData(), output->ElementsNum());
+        break;
+      }
+      case TypeId::kNumberTypeInt8: {
+        total_error += CompareData(static_cast<int8_t *>(output->data()), calib->MutableData(), output->ElementsNum());
+        break;
+      }
+      case TypeId::kNumberTypeUInt8: {
+        total_error += CompareData(static_cast<uint8_t *>(output->data()), calib->MutableData(), output->ElementsNum());
+        break;
+      }
+      case TypeId::kNumberTypeUInt:
+      case TypeId::kNumberTypeUInt32: {
+        total_error += CompareData(static_cast<int32_t *>(output->data()), calib->MutableData(), output->ElementsNum());
+        break;
+      }
+      default: {
+        printf("unsupported tensor data type\n");
+      }
+    }
+  }
+  if (total_error > kToleranceVal) {
+    printf("compare outputs failed, total error: %f\n", total_error);
+    return RET_ERROR;
+  }
+  printf("compare outputs success, total error: %f\n", total_error);
+  return RET_OK;
+}
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/micro/example/mnist_stm32f746/mnist_stm32f746/benchmark/calib_output.h

@@ -0,0 +1,73 @@
+
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * 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 MINDSPORE_LITE_MICRO_CALIB_OUTPUT_H_
+#define MINDSPORE_LITE_MICRO_CALIB_OUTPUT_H_
+
+#include "include/lite_utils.h"
+#include "include/ms_tensor.h"
+#include "include/errorcode.h"
+
+namespace mindspore {
+namespace lite {
+
+class CalibTensor {
+ public:
+  CalibTensor(String name, size_t elements_num) : tensor_name_(name), elements_num_(elements_num) {}
+  ~CalibTensor() {
+    free(data_);
+    data_ = nullptr;
+  }
+  String tensor_name() const { return tensor_name_; }
+  int ElementsNum() const { return elements_num_; }
+  float *MutableData() {
+    if (data_ == nullptr) {
+      if (elements_num_ == 0 || elements_num_ > INT16_MAX) {
+        return nullptr;
+      }
+      data_ = static_cast<float *>(malloc(elements_num_ * sizeof(float)));
+    }
+    return data_;
+  }
+
+ private:
+  String tensor_name_;
+  int elements_num_{0};
+  float *data_{nullptr};
+};
+
+class Calibrator {
+ public:
+  Calibrator() = default;
+  ~Calibrator() {
+    for (auto &calib : calib_outputs_) {
+      delete calib;
+      calib = nullptr;
+    }
+    calib_outputs_.clear();
+  }
+  int ReadCalibData(const char *calib_data_path);
+  int CompareOutputs(const Vector<tensor::MSTensor *> &outputs) const;
+
+ private:
+  Vector<CalibTensor *> calib_outputs_;
+};
+
+}  // namespace lite
+}  // namespace mindspore
+
+#endif  // MINDSPORE_LITE_MICRO_CALIB_OUTPUT_H_

mindspore/lite/micro/example/mnist_stm32f746/mnist_stm32f746/src/string.cc

@@ -287,6 +287,7 @@ String operator+(const char *lhs, const String &rhs) {
   return str;
 }
 
+bool operator!=(const String &lhs, const String &rhs) { return lhs.compare(rhs) != 0; }
 bool operator==(const String &lhs, const String &rhs) { return lhs.compare(rhs) == 0; }
 bool operator==(const String &lhs, const char *rhs) { return lhs.compare(rhs) == 0; }
 bool operator==(const char *lhs, const String &rhs) { return rhs.compare(lhs) == 0; }

mindspore/lite/micro/example/mnist_x86/benchmark/benchmark.cc

@@ -24,6 +24,7 @@
 #include "include/errorcode.h"
 
 #include "load_input.h"
+#include "calib_output.h"
 
 using namespace mindspore;
 
@@ -34,8 +35,9 @@ void usage() {
     "args[1]: inputs binary file\n"
     "args[2]: model weight binary file\n"
     "args[3]: loop count for performance test\n"
-    "args[4]: runtime thread num\n"
-    "args[5]: runtime thread bind mode\n\n");
+    "args[4]: calibration file\n"
+    "args[5]: runtime thread num\n"
+    "args[6]: runtime thread bind mode\n\n");
 }
 
 uint64_t GetTimeUs() {
@@ -111,15 +113,15 @@ int main(int argc, const char **argv) {
   }
 
   lite::Context *context = nullptr;
-  if (argc >= 6) {
+  if (argc >= 7) {
     // config benchmark context
     context = new (std::nothrow) lite::Context();
     if (context == nullptr) {
       return lite::RET_ERROR;
     }
-    context->thread_num_ = atoi(argv[4]);
+    context->thread_num_ = atoi(argv[5]);
     context->device_list_.resize(1);
-    context->device_list_[0] = {lite::DT_CPU, {{false, static_cast<lite::CpuBindMode>(atoi(argv[5]))}}};
+    context->device_list_[0] = {lite::DT_CPU, {{false, static_cast<lite::CpuBindMode>(atoi(argv[6]))}}};
     printf("context: ThreadNum: %d, BindMode: %d\n", context->thread_num_,
            context->device_list_[0].device_info_.cpu_device_info_.cpu_bind_mode_);
   }
@@ -167,12 +169,29 @@ int main(int argc, const char **argv) {
     return lite::RET_ERROR;
   }
 
-  Vector<String> outputs_name = session->GetOutputTensorNames();
   printf("\noutputs: \n");
+  Vector<String> outputs_name = session->GetOutputTensorNames();
+  Vector<tensor::MSTensor *> outputs;
   for (const auto &name : outputs_name) {
     auto output = session->GetOutputByTensorName(name);
+    outputs.push_back(output);
     TensorToString(output);
   }
+  if (argc >= 5) {
+    lite::Calibrator *calibrator = new (std::nothrow) lite::Calibrator();
+    if (calibrator == nullptr) {
+      return lite::RET_NULL_PTR;
+    }
+    ret = calibrator->ReadCalibData(argv[4]);
+    if (ret != lite::RET_OK) {
+      return lite::RET_ERROR;
+    }
+    ret = calibrator->CompareOutputs(outputs);
+    if (ret != lite::RET_OK) {
+      return lite::RET_ERROR;
+    }
+    delete calibrator;
+  }
   printf("========run success=======\n");
   delete session;
   session = nullptr;

mindspore/lite/micro/example/mnist_x86/benchmark/calib_output.cc

@@ -0,0 +1,148 @@
+
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * 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.
+ */
+
+#include "calib_output.h"
+#include <fstream>
+#include <sstream>
+#include <iostream>
+#include <stdio.h>
+#include <cmath>
+
+namespace mindspore {
+namespace lite {
+constexpr float kToleranceVal = 0.0001;
+
+#define MS_ERROR_IF_NULL(ptr)            \
+  do {                                   \
+    if ((ptr) == nullptr) {              \
+      return mindspore::lite::RET_ERROR; \
+    }                                    \
+  } while (0)
+
+int Calibrator::ReadCalibData(const char *calib_data_path) {
+  std::ifstream in_file(calib_data_path);
+  if (!in_file.good()) {
+    printf("file is not exist, %s\n", calib_data_path);
+    return RET_ERROR;
+  }
+  if (!in_file.is_open()) {
+    printf("open file failed, %s\n", calib_data_path);
+    in_file.close();
+    return RET_ERROR;
+  }
+  while (!in_file.eof()) {
+    std::string line;
+    getline(in_file, line);
+    if (line.empty()) {
+      continue;
+    }
+    std::stringstream name_line(line);
+    std::string tensor_name;
+    size_t dim = 0;
+    name_line >> tensor_name >> dim;
+    size_t elements = 1;
+    for (size_t i = 0; i < dim; i++) {
+      size_t tmp_dim;
+      name_line >> tmp_dim;
+      elements *= tmp_dim;
+    }
+    getline(in_file, line);
+    std::stringstream data_line(line);
+    String name(tensor_name.c_str());
+    CalibTensor *output = new (std::nothrow) CalibTensor(name, elements);
+    MS_ERROR_IF_NULL(output);
+    float *data = output->MutableData();
+    MS_ERROR_IF_NULL(data);
+    for (size_t i = 0; i < elements; i++) {
+      data_line >> data[i];
+    }
+    calib_outputs_.push_back(output);
+  }
+  in_file.close();
+  return RET_OK;
+}
+
+template <typename T>
+float CompareData(const T *output, const float *calib, size_t elements_num) {
+  float error = 0.;
+  if (output == nullptr || calib == nullptr) {
+    printf("output or calib is nullptr\n");
+    return error;
+  }
+  for (size_t i = 0; i < elements_num; ++i) {
+    if (std::isnan(output[i]) || std::isinf(output[i]) || std::isnan(calib[i]) || std::isinf(calib[i])) {
+      printf("error, output data is nan or inf\n");
+      return error;
+    }
+    error += std::abs(output[i] - calib[i]);
+  }
+  return error;
+}
+
+int Calibrator::CompareOutputs(const Vector<tensor::MSTensor *> &outputs) const {
+  if (outputs.size() != calib_outputs_.size()) {
+    printf("error, outputs and calibs size is mismatch\n");
+    return RET_ERROR;
+  }
+  float total_error = 0;
+  size_t outputs_num = outputs.size();
+  for (size_t i = 0; i < outputs_num; ++i) {
+    tensor::MSTensor *output = outputs[i];
+    MS_ERROR_IF_NULL(output);
+    CalibTensor *calib = calib_outputs_[i];
+    MS_ERROR_IF_NULL(calib);
+    if (output->tensor_name() != calib->tensor_name()) {
+      printf("error, output tensor name is not equal to calib\n");
+      return RET_ERROR;
+    }
+    if (output->ElementsNum() != calib->ElementsNum()) {
+      printf("error, output elements num is not equal to calib\n");
+      return RET_ERROR;
+    }
+    switch (output->data_type()) {
+      case TypeId::kNumberTypeFloat:
+      case TypeId::kNumberTypeFloat32: {
+        total_error += CompareData(static_cast<float *>(output->data()), calib->MutableData(), output->ElementsNum());
+        break;
+      }
+      case TypeId::kNumberTypeInt8: {
+        total_error += CompareData(static_cast<int8_t *>(output->data()), calib->MutableData(), output->ElementsNum());
+        break;
+      }
+      case TypeId::kNumberTypeUInt8: {
+        total_error += CompareData(static_cast<uint8_t *>(output->data()), calib->MutableData(), output->ElementsNum());
+        break;
+      }
+      case TypeId::kNumberTypeUInt:
+      case TypeId::kNumberTypeUInt32: {
+        total_error += CompareData(static_cast<int32_t *>(output->data()), calib->MutableData(), output->ElementsNum());
+        break;
+      }
+      default: {
+        printf("unsupported tensor data type\n");
+      }
+    }
+  }
+  if (total_error > kToleranceVal) {
+    printf("compare outputs failed, total error: %f\n", total_error);
+    return RET_ERROR;
+  }
+  printf("compare outputs success, total error: %f\n", total_error);
+  return RET_OK;
+}
+}  // namespace lite
+}  // namespace mindspore

mindspore/lite/micro/example/mnist_x86/benchmark/calib_output.h

@@ -0,0 +1,73 @@
+
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * 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 MINDSPORE_LITE_MICRO_CALIB_OUTPUT_H_
+#define MINDSPORE_LITE_MICRO_CALIB_OUTPUT_H_
+
+#include "include/lite_utils.h"
+#include "include/ms_tensor.h"
+#include "include/errorcode.h"
+
+namespace mindspore {
+namespace lite {
+
+class CalibTensor {
+ public:
+  CalibTensor(String name, size_t elements_num) : tensor_name_(name), elements_num_(elements_num) {}
+  ~CalibTensor() {
+    free(data_);
+    data_ = nullptr;
+  }
+  String tensor_name() const { return tensor_name_; }
+  int ElementsNum() const { return elements_num_; }
+  float *MutableData() {
+    if (data_ == nullptr) {
+      if (elements_num_ == 0 || elements_num_ > INT16_MAX) {
+        return nullptr;
+      }
+      data_ = static_cast<float *>(malloc(elements_num_ * sizeof(float)));
+    }
+    return data_;
+  }
+
+ private:
+  String tensor_name_;
+  int elements_num_{0};
+  float *data_{nullptr};
+};
+
+class Calibrator {
+ public:
+  Calibrator() = default;
+  ~Calibrator() {
+    for (auto &calib : calib_outputs_) {
+      delete calib;
+      calib = nullptr;
+    }
+    calib_outputs_.clear();
+  }
+  int ReadCalibData(const char *calib_data_path);
+  int CompareOutputs(const Vector<tensor::MSTensor *> &outputs) const;
+
+ private:
+  Vector<CalibTensor *> calib_outputs_;
+};
+
+}  // namespace lite
+}  // namespace mindspore
+
+#endif  // MINDSPORE_LITE_MICRO_CALIB_OUTPUT_H_

mindspore/lite/micro/example/mnist_x86/src/string.cc

@@ -287,6 +287,7 @@ String operator+(const char *lhs, const String &rhs) {
   return str;
 }
 
+bool operator!=(const String &lhs, const String &rhs) { return lhs.compare(rhs) != 0; }
 bool operator==(const String &lhs, const String &rhs) { return lhs.compare(rhs) == 0; }
 bool operator==(const String &lhs, const char *rhs) { return lhs.compare(rhs) == 0; }
 bool operator==(const char *lhs, const String &rhs) { return rhs.compare(lhs) == 0; }