!7010 加入mindspore xts测试用例

Merge pull request !7010 from wangtongyu6/add_ms_xts_real

ai/BUILD.gn

@@ -14,4 +14,7 @@
 group("ai") {
   testonly = true
   deps = [ "neural_network_runtime:neural_network_runtime" ]
+  if (is_standard_system) {
+    deps += [ "mindspore:ActsMindSporeTest" ]
+  }
 }

ai/mindspore/BUILD.gn

+# Copyright (c) 2022 Huawei Device 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.
+
+import("//test/xts/tools/build/suite.gni")
+
+module_output_path = "acts/ActsMindSporeTest"
+
+ohos_moduletest_suite("ActsMindSporeTest") {
+  module_out_path = module_output_path
+  sources = [
+    "src/ohos_c_api_test_mslite.cpp",
+    "src/ohos_common.cpp",
+  ]
+
+  include_dirs = [ "//foundation/ai/mindspore/" ]
+
+  deps = [
+    "//third_party/googletest:gmock",
+    "//third_party/googletest:gtest",
+    "//third_party/mindspore/mindspore/lite:mindspore_lib",
+  ]
+
+  defines = [ "__STDC_FORMAT_MACROS" ]
+  subsystem_name = "ai"
+  part_name = "mindspore"
+}

ai/mindspore/Test.json

+{
+  "description": "Config for MindSpore test cases",
+  "driver": {
+    "module-name": "ActsMindSporeTest",
+    "native-test-timeout": "120000",
+    "native-test-device-path": "/data/local/tmp",
+    "runtime-hint": "1s",
+    "type": "CppTest"
+  },
+  "kits": [
+    {
+        "type": "ShellKit",
+        "run-command": [
+            "remount",
+            "mkdir /data/test"
+        ]
+    },
+    {
+        "type": "PushKit",
+        "push": [
+            "ActsMindSporeTest->/data/local/tmp/ActsMindSporeTest",
+            "resources/ai/mindspore/aiy_vision_classifier_plants_V1_3/aiy_vision_classifier_plants_V1_3.ms -> /data/test",
+            "resources/ai/mindspore/aiy_vision_classifier_plants_V1_3/aiy_vision_classifier_plants_V1_3.input -> /data/test",
+            "resources/ai/mindspore/aiy_vision_classifier_plants_V1_3/aiy_vision_classifier_plants_V1_30.output -> /data/test",
+            "resources/ai/mindspore/ml_face_is_face/ml_face_isface.ms -> /data/test",
+            "resources/ai/mindspore/ml_face_is_face/ml_face_isfacer13.ms -> /data/test",
+            "resources/ai/mindspore/ml_face_is_face/ml_face_isface.input -> /data/test",
+            "resources/ai/mindspore/ml_face_is_face/ml_face_isface_0.input -> /data/test",
+            "resources/ai/mindspore/ml_face_is_face/ml_face_isface0.output -> /data/test",
+            "resources/ai/mindspore/ml_Hand_deploy/ml_Hand_deploy.ms -> /data/test",
+            "resources/ai/mindspore/ml_Hand_deploy/ml_Hand_deploy_0.input -> /data/test",
+            "resources/ai/mindspore/ml_Hand_deploy/ml_Hand_deploy0.output -> /data/test",
+            "resources/ai/mindspore/ml_ocr_cn/ml_ocr_cn_0.input -> /data/test",
+            "resources/ai/mindspore/ml_ocr_cn/ml_ocr_cn.ms -> /data/test",
+            "resources/ai/mindspore/ml_ocr_cn/ml_ocr_cn0.output -> /data/test",
+            "resources/ai/mindspore/ml_headpose_pb2tflite/ml_headpose_pb2tflite.ms -> /data/test",
+            "resources/ai/mindspore/ml_headpose_pb2tflite/ml_headpose_pb2tflite_0.input -> /data/test",
+            "resources/ai/mindspore/ml_headpose_pb2tflite/ml_headpose_pb2tflite_1.input -> /data/test",
+            "resources/ai/mindspore/ml_headpose_pb2tflite/ml_headpose_pb2tflite_2.input -> /data/test",
+            "resources/ai/mindspore/ml_headpose_pb2tflite/ml_headpose_pb2tflite0.output -> /data/test"
+        ]
+    }
+]
+}

ai/mindspore/src/ohos_common.cpp

+/*
+ * Copyright (c) 2022 Huawei Device 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 "ohos_common.h"
+#include <numeric>
+#include <inttypes.h>
+
+/*
+ * getDimInfo: get dim info from data file(int64_t)
+ * param:
+ * fp: the testing datafile object
+ *
+ * return :
+ * dim_info: array to store the info of the dim in datafile, like
+ * [4,3,3,6,3,162(3*3*6*3)],4 is dim size,3,3,6,3 is the dim shape data_size:
+ * the size of the testing data including the data file
+ * */
+void getDimInfo(FILE *fp, std::vector<int64_t>* dim_info) {
+  const int MAX_HEAD_SIZE = 50;
+  uint32_t *dim_buffer = reinterpret_cast<uint32_t *>(malloc(MAX_HEAD_SIZE * sizeof(uint32_t)));
+  size_t ret = fread(dim_buffer, sizeof(uint32_t), MAX_HEAD_SIZE, fp);
+  if (ret == 0) {
+    free(dim_buffer);
+    return;
+  }
+  dim_info->push_back(*dim_buffer);  // get dim size
+
+  // get data shape to compute the datasize
+  uint64_t data_size = 1;
+  uint32_t i = 1;
+  for (; i <= dim_info->at(0); i++) {
+    dim_info->push_back(*(dim_buffer + i));
+    data_size *= *(dim_buffer + i);
+  }
+  dim_info->push_back(data_size);
+
+  free(dim_buffer);
+}
+
+/*
+ * readTestDataFile: read test date from hisi .t datafile（int64_t）
+ * param:
+ * infile: the path of hisi .t datafile
+ * return:
+ * dim_info: array to store the info of the dim in datafile, like [4,3,3,6,3],4
+ * is dim size,3,3,6,3 is the dim shape
+ * */
+void *readTestDataFile(std::string infile, std::vector<int64_t>* dim_info1) {
+  printf("\n [common.cpp] Loading data from: %s\n", infile.c_str());
+
+  FILE *fp;
+  fp = fopen(infile.c_str(), "r");
+  if (fp == nullptr) {
+    printf("ERROR: cant't open file %s\n", infile.c_str());
+    return nullptr;
+  } else {
+    std::vector<int64_t> dim_info;
+    std::vector<int64_t>* ptr_dim_info = &dim_info;
+    getDimInfo(fp, ptr_dim_info);
+    uint64_t data_size = ptr_dim_info->at(ptr_dim_info->size() - 1);
+    fclose(fp);
+
+    fp = fopen(infile.c_str(), "r");
+    if (fp == nullptr) {
+      printf("ERROR: cant't open file %s\n", infile.c_str());
+      return nullptr;
+    }
+    uint32_t *memory = reinterpret_cast<uint32_t *>(malloc((dim_info[0] + 1) * sizeof(uint32_t)));
+
+    size_t ret = fread(memory, sizeof(uint32_t), (dim_info[0] + 1), fp);
+    if (ret == 0) {
+      free(memory);
+      fclose(fp);
+      return nullptr;
+    }
+    uint32_t *data = reinterpret_cast<uint32_t *>(malloc((data_size) * sizeof(uint32_t)));
+    size_t ret2 = fread(data, sizeof(uint32_t), data_size, fp);
+    if (ret2 == 0) {
+      free(data);
+      fclose(fp);
+      return nullptr;
+    }
+    free(memory);
+    fclose(fp);
+
+    for (int i = 0; i < dim_info[0]; i++) {
+      dim_info1->push_back(dim_info[i + 1]);
+    }
+
+    printf("\n [common.cpp] Read test data file Over, get dimInfo as: (");
+    int count = dim_info1->size();
+    for (int i = 0; i < count; i++) {
+      printf("%" PRId64, dim_info1->at(i));
+    }
+    printf(")\n");
+    return data;
+  }
+}
+
+/*
+ * allclose
+ * param:
+ *  a:compared file a
+ *  b:compared file b
+ *  count: the count size which will compare
+ *  rtol:
+ *  atol:
+ * return:
+ *  true or false
+ * */
+bool allclose(float *a, float *b, uint64_t count, float rtol = 1e-05,
+              float atol = 1e-08, bool isquant = false) {
+  uint32_t i = 0;
+
+  // add fail loop print
+  uint32_t fail_count = 0;
+  float tol = 0;
+  float tol1 = 0;
+  float tol2 = 0;
+  bool nan_occur_in_accuray = false;
+
+  float sum = 0.0f;
+  static float sum_all;
+  static float maximum = 0;
+  static float minimum = 0;
+  static uint64_t c = 0;
+
+  if (a == nullptr || b == nullptr) {
+    return false;
+  }
+
+  for (; i < count; ++i) {
+    sum = sum + fabs(a[i] - b[i]) / (atol + rtol * fabs(b[i]));
+    sum_all = sum_all + fabs(a[i] - b[i]) / (atol + rtol * fabs(b[i]));
+    maximum = max(maximum, fabs(a[i] - b[i]) / (atol + rtol * fabs(b[i])));
+    minimum = min(minimum, fabs(a[i] - b[i]) / (atol + rtol * fabs(b[i])));
+    if (isnan(a[i]) || isinf(a[i])) {
+      fail_count = fail_count + 1;
+      nan_occur_in_accuray = true;
+      if (fail_count < 100) {
+        printf("     i = %2u:   %+f  |  %+f\n", i, a[i], b[i]);
+      }
+    } else if (fabs(a[i] - b[i]) > (atol + rtol * fabs(b[i]))) {
+      tol = tol + fabs(a[i] - b[i]) / (fabs(b[i]) + 1);
+      tol1 = tol1 + fabs(a[i] - b[i]);
+      tol2 = tol2 + fabs(a[i] - b[i]) / fabs(b[i]);
+      fail_count = fail_count + 1;
+      if (fail_count < 100) {
+        printf("     i = %2u:   %+f  |  %+f\n", i, a[i], b[i]);
+      }
+    }
+
+    if (i == count - 1) {
+      printf("     ……\n");
+      printf("\n *** Total fail_count: %u\n", fail_count);
+      printf("\n     fabs(a[i] - b[i])/(fabs(b[i])+1) : %f\n",
+             tol / fail_count);
+      printf("\n     fabs(a[i] - b[i]) : %f\n", tol1 / fail_count);
+      printf("\n     fabs(a[i] - b[i])/fabs(b[i]) : %f\n", tol2 / fail_count);
+
+      c = c + count;
+      printf("\n     avg : %f\n", sum / count);
+      printf("\n     min : %f\n", minimum);
+      printf("\n     max :  %f\n", maximum);
+      printf("\n     avg_all :  %f\n", sum_all / c);
+      printf("\n");
+      fstream file;
+      file.open("cout.csv", ios::app);
+
+      file << ","
+           << "1,"
+           << "0," << maximum;
+      if (fail_count == 0) {
+        file << "," << sum_all / c;
+      } else {
+        file << "," << tol / fail_count;
+      }
+      file.close();
+    }
+  }
+  if (nan_occur_in_accuray) {
+    printf("\n[common.cpp] eval output include some NAN/INF\n");
+    return false;
+  }
+
+  if (fail_count > 0) {
+    printf("\n *** These data compare failed: atol = %f, rtol = %f\n", atol,
+           rtol);
+    printf("\n");
+    if (isquant) {
+      if (tol / fail_count < 0.04) {
+        return true;
+      }
+    }
+    return false;
+  }
+  return true;
+}
+
+bool allclose_int8(uint8_t *a, uint8_t *b, uint64_t count, float rtol = 1e-05,
+                   float atol = 1e-08, bool isquant = false) {
+  uint32_t i = 0;
+  // add fail loop print
+  uint32_t fail_count = 0;
+  float tol = 0;
+  float tol1 = 0;
+  float tol2 = 0;
+  bool nan_occur_in_accuray = false;
+
+  float sum = 0.0f;
+  static float sum_all;
+  static float maximum = 0;
+  static float minimum = 0;
+  static uint64_t c = 0;
+  // add fail loop print
+
+  if (a == nullptr || b == nullptr) {
+    return false;
+  }
+
+  for (; i < count; ++i) {
+    sum = sum + fabs(a[i] - b[i]) / (atol + rtol * fabs(b[i]));
+    sum_all = sum_all + fabs(a[i] - b[i]) / (atol + rtol * fabs(b[i]));
+    maximum = max(static_cast<double>(maximum),
+                  static_cast<double>(fabs(a[i] - b[i])) / (atol + rtol * fabs(b[i])));
+    minimum = min(static_cast<double>(minimum),
+                  static_cast<double>(fabs(a[i] - b[i])) / (atol + rtol * fabs(b[i])));
+    if (isnan(a[i]) || isinf(a[i])) {
+      fail_count = fail_count + 1;
+      nan_occur_in_accuray = true;
+      if (fail_count < 100) {
+        printf("     i = %2u:   %+f  |  %+f\n", i, static_cast<float>(a[i]), static_cast<float>(b[i]));
+      }
+    } else if (fabs(a[i] - b[i]) > 0) {
+      tol = tol + fabs(a[i] - b[i]) / (fabs(b[i]) + 1);
+      tol1 = tol1 + fabs(a[i] - b[i]);
+      tol2 = tol2 + fabs(a[i] - b[i]) / fabs(b[i]);
+      fail_count = fail_count + 1;
+      printf("%2d", static_cast<int>(fabs(a[i] - b[i])));
+      printf("     i = %2u:   %2d  |  %2d\n", i, a[i], b[i]);
+    }
+    if (i == count - 1) {
+      printf("     ……\n");
+      printf("\n *** Total fail_count: %u\n", fail_count);
+      printf("\n     fabs(a[i] - b[i])/(fabs(b[i])+1) : %f\n",
+             tol / fail_count);
+      printf("\n     fabs(a[i] - b[i]) : %f\n", tol1 / fail_count);
+      printf("\n     fabs(a[i] - b[i])/fabs(b[i]) : %f\n", tol2 / fail_count);
+
+      c = c + count;
+      printf("\n     avg : %f\n", sum / count);
+      printf("\n     min : %f\n", minimum);
+
+      printf("\n     max :  %f\n", maximum);
+      printf("\n     avg_all :  %f\n", sum_all / c);
+      printf("\n");
+      fstream file;
+      file.open("cout.csv", ios::app);
+
+      file << ","
+           << "1,"
+           << "0," << maximum;
+      if (fail_count == 0) {
+        file << "," << sum_all / c;
+      } else {
+        file << "," << tol / fail_count;
+      }
+      file.close();
+    }
+  }
+  if (nan_occur_in_accuray) {
+    printf("\n[common.cpp] eval output include some NAN/INF\n");
+    return false;
+  }
+  if (fail_count > 0) {
+    printf("\n *** These data compare failed: atol = %f, rtol = %f\n", atol,
+           rtol);
+    printf("\n");
+    if (isquant) {
+      if (tol / fail_count < 0.04) {
+        return true;
+      }
+    }
+    return false;
+  }
+  return true;
+}
+
+/*
+ * compFp32WithTData: compare the data with the data in hisi .t file
+ * param:
+ *  actualOutputData: the result of ge
+ *  expectedDataFile: the path of hisi .t result file
+ *  rtol:
+ *  atol:
+ * return:
+ *  true of false
+ * */
+bool compFp32WithTData(float *actualOutputData, const std::string& expectedDataFile,
+                       float rtol = 1e-05, float atol = 1e-08,
+                       bool isquant = false) {
+  std::vector<int64_t> dim_info;
+  std::vector<int64_t>* ptr_dim_info = &dim_info;
+  float *expectedOutputData =
+      reinterpret_cast<float *>(readTestDataFile(expectedDataFile, ptr_dim_info));
+  uint32_t i = 0;
+  uint64_t data_size = 1;
+  data_size = accumulate(dim_info.begin(), dim_info.end(), 1, std::multiplies<uint64_t>());
+
+  // print caffe/tf output:
+  printf("[common.cpp] expected output data:");
+  for (; i < data_size && i < 10; i++) {
+    printf("%4f ", expectedOutputData[i]);
+  }
+  printf("\n");
+  if (isquant) {
+    return allclose(actualOutputData, expectedOutputData, data_size, rtol, atol,
+                    true);
+  }
+  return allclose(actualOutputData, expectedOutputData, data_size, rtol, atol);
+}
+
+bool compUint8WithTData(uint8_t *actualOutputData, const std::string& expectedDataFile,
+                        float rtol = 1e-05, float atol = 1e-08,
+                        bool isquant = false) {
+  std::vector<int64_t> dim_info;
+  std::vector<int64_t>* ptr_dim_info = &dim_info;
+  auto dataFile = readTestDataFile(expectedDataFile, ptr_dim_info);
+  if(dataFile == nullptr){
+    return false;
+  }
+  uint8_t *expectedOutputData =
+      reinterpret_cast<uint8_t *>(dataFile);
+  uint32_t i = 0;
+  uint64_t data_size = 1;
+  data_size = accumulate(dim_info.begin(), dim_info.end(), 1, std::multiplies<uint64_t>());
+
+  // print caffe/tf output:
+  printf("\n [common.cpp] expected output data:\n");
+  for (; i < data_size && i < 10; i++) {
+    printf("%4hhu ", static_cast<unsigned char>(expectedOutputData[i]));
+  }
+  printf("\n");
+  if (isquant) {
+    return allclose_int8(actualOutputData, expectedOutputData, data_size, rtol,
+                         atol, true);
+  }
+  return allclose_int8(actualOutputData, expectedOutputData, data_size, rtol,
+                       atol);
+}
+
+/*
+ * ReadFile: read file of model
+ * param:
+ *  file: file location
+ *  size: file size
+ * return:
+ *  buf of file
+ * */
+char *ReadFile(const char *file, size_t* size) {
+  printf("[common.cpp] Loading data from: %s\n", file);
+
+  std::ifstream ifs(file);
+  if (!ifs.good()) {
+    return nullptr;
+  }
+
+  if (!ifs.is_open()) {
+    ifs.close();
+    return nullptr;
+  }
+
+  ifs.seekg(0, std::ios::end);
+  *size = ifs.tellg();
+
+  char *buf = new char[*size];
+  if (buf == nullptr) {
+    ifs.close();
+    return nullptr;
+  }
+
+  ifs.seekg(0, std::ios::beg);
+  ifs.read(buf, *size);
+  ifs.close();
+  printf("[common.cpp]Read Binary Data Over, get tensorSize as: %" PRId64 ".\n", static_cast<int64_t>(*size));
+
+  return buf;
+}
+
+void PackNCHWToNHWCFp32(const char *src, char *dst, int batch, int plane, int channel) {
+    for (int n = 0; n < batch; n++) {
+        for (int c = 0; c < channel; c++) {
+            for (int hw = 0; hw < plane; hw++) {
+                int nhwc_index = n * channel * plane + hw * channel + c;
+                int nchw_index = n * channel * plane + c * plane + hw;
+                dst[nhwc_index * 4] = src[nchw_index * 4];
+                dst[nhwc_index * 4 + 1] = src[nchw_index * 4 + 1];
+                dst[nhwc_index * 4 + 2] = src[nchw_index * 4 + 2];
+                dst[nhwc_index * 4 + 3] = src[nchw_index * 4 + 3];
+            }
+        }
+    }
+    return;
+}

ai/mindspore/src/ohos_common.h

+/*
+ * Copyright (c) 2022 Huawei Device 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 GE_COMMON_H
+#define GE_COMMON_H
+
+#include <cstdio>
+#include <cstdlib>
+#include <fstream>
+#include <iostream>
+#include <string>
+#include <vector>
+#include <map>
+#include <math.h>
+
+using std::string;
+using std::cout;
+using std::endl;
+using std::map;
+using std::ios;
+using std::fstream;
+using std::to_string;
+using std::ifstream;
+using std::stringstream;
+using std::max;
+using std::min;
+using std::vector;
+// using namespace mindspore::tensor;
+
+bool compFp32WithTData(float *actualOutputData,
+                       const std::string &expectedDataFile, float rtol,
+                       float atol, bool isquant);
+bool allclose_int8(int8_t *a, int8_t *b, uint64_t count, float rtol, float atol,
+                   bool isquant);
+bool compUint8WithTData(uint8_t *actualOutputData,
+                        const std::string &expectedDataFile, float rtol,
+                        float atol, bool isquant);
+//// add for mslite test of int64:
+void getDimInfo(FILE *fp, std::vector<int64_t>* dim_info);
+char *ReadFile(const char *file, size_t* size);
+void PackNCHWToNHWCFp32(const char *src, char *dst, int batch, int plane, int channel);
+
+#endif  // GE_COMMON_H
\ No newline at end of file