[CONFORMANCE] Add comparator accuracy vs conformance

src/tests/test_utils/functional_test_utils/layer_tests_summary/conformance_helper_tools/conformance_vs_accuracy_comparator.py

@@ -0,0 +1,171 @@
+# Copyright (C) 2023 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import csv
+import os
+from argparse import ArgumentParser
+
+def parse_arguments():
+    parser = ArgumentParser()
+
+    accuracy_help = "Path to csv file with accuracy results"
+    conformance_help = "Path to csv file with conformance failed models"
+    model_help = "Path to file with full model list as .lst"
+    device_help = "Target device"
+
+
+    parser.add_argument("-a", "--accuracy", help=accuracy_help, required=True)
+    parser.add_argument("-c", "--conformance", help=conformance_help, required=True)
+    parser.add_argument("-m", "--model", help=model_help, required=True)
+    parser.add_argument("-d", "--device", help=device_help, required=True)
+
+    return parser.parse_args()
+
+class Model:
+    def __init__(self, model_name:str, model_framework:str, model_prc:str):
+        self.__model_name = model_name
+        self.__model_framework = model_framework
+        self.__model_prc = model_prc
+
+    def get_name(self):
+        return self.__model_name
+
+    def get_framework(self):
+        return self.__model_framework
+
+    def get_precision(self):
+        return self.__model_prc
+
+def path_to_model(model_path: os.path, prefix: str):
+    frameworks = {'tf', 'tf2', 'caffe', 'onnx', 'mxnet', 'paddle', 'kaldi'}
+    precisions = {'FP16', 'FP32', 'INT8', 'INT1'}
+    # remove share path + model.xml
+    model, _ = os.path.split(model_path.replace('\n', '').replace(prefix, ''))
+    model, _ = os.path.split(model)
+    model, _ = os.path.split(model)
+    model_name, model_framework, model_prc = (None, None, None)
+    for item in str(model).split(os.path.sep):
+        if model_name == None:
+            model_name = item
+            continue
+        if model_framework is None and item in frameworks:
+            model_framework = item
+            continue
+        if item in precisions:
+            if model_prc == None:
+                model_prc = item
+                continue
+            model_prc += "-"
+            model_prc += item
+    return Model(model_name=model_name, model_framework=model_framework, model_prc=model_prc)
+
+def process_model_list(model_list_file_path: os.path):
+    if not os.path.isfile(model_list_file_path):
+        raise Exception(f"Model filelist: {model_list_file_path} is not file!")
+    models = set()
+    with open(model_list_file_path, "r") as model_list_file:
+        in_models = model_list_file.readlines()
+        prefix = os.path.commonprefix(in_models)
+        for line in in_models:
+            models.add(path_to_model(line, prefix))
+        model_list_file.close()
+    return models
+
+def process_accuracy(accuracy_res_file: os.path, target_device:str):
+    if not os.path.isfile(accuracy_res_file):
+        raise Exception(f"Model filelist: {accuracy_res_file} is not file!")
+    # { model: status }
+    results = dict()
+    conformance_res = list()
+    with open(accuracy_res_file, newline='') as csv_file:
+        csv_reader = csv.reader(csv_file, delimiter=',')
+        model_name_row, model_name_row_idx = ("topology", None)
+        framework_row, framework_row_idx = ("sourceframework", None)
+        precision_row, precision_row_idx = ("precision", None)
+        accuracy_row, accuracy_status_row_idx = ("metricstatus", None)
+        device_row, device_row_idx = ("device", None)
+
+        for row in csv_reader:
+            if model_name_row_idx == None:
+                for i in range(len(row)):
+                    if row[i] == model_name_row:
+                        model_name_row_idx = i
+                    elif row[i] == framework_row:
+                        framework_row_idx = i
+                    elif row[i] == precision_row:
+                        precision_row_idx = i
+                    elif row[i] == accuracy_row:
+                        accuracy_status_row_idx = i
+                    elif row[i] == device_row:
+                        device_row_idx = i
+                continue
+            model = Model(model_name=row[model_name_row_idx], model_framework=row[framework_row_idx], model_prc=row[precision_row_idx])
+            if target_device in row[device_row_idx]:
+                if model in results.keys():
+                    old_status = results[model]
+                    new_status = row[accuracy_status_row_idx]
+                    if old_status != new_status and (new_status == "passed" or old_status == "not_found" or old_status == ""):
+                        results[model] = new_status
+                else:
+                    results.update({model: row[accuracy_status_row_idx]})
+        csv_file.close()
+    return results
+
+
+def process_conformance(failed_models_path:os.path):
+    if not os.path.isfile(failed_models_path):
+        raise Exception(f"Conformance failed model csv: {failed_models_path} is not file!")
+    model_paths = set()
+    models = dict()
+    with open(failed_models_path, newline='') as csv_file:
+        csv_reader = csv.reader(csv_file, delimiter=',')
+        for failed_model in csv_reader:
+            model_paths.add(failed_model[0])
+        csv_file.close()
+    prefix = os.path.commonprefix(list(model_paths))
+    for model in model_paths:
+        models.update({path_to_model(model, prefix): "failed"})
+    return models
+
+def test_results_to_csv(model_set: set, accuracy_res: dict, conformance_res: dict):
+    with open('test_results.csv', 'w', newline='') as csv_file:
+        csv_writer = csv.writer(csv_file, dialect='excel')
+        csv_writer.writerow(
+            ["model_name",
+             "framework",
+             "precision",
+             "accuracy_status",
+             "conformance_status",
+             "test_match"
+             ])
+        for model in model_set:
+            accuracy_status = "not_found"
+            conformance_status = "passed"
+            for acc_model in accuracy_res.keys():
+                if model.get_name() == acc_model.get_name() and \
+                   model.get_framework() == acc_model.get_framework() and \
+                   model.get_precision() == acc_model.get_precision():
+                    accuracy_status = accuracy_res[acc_model]
+                    break
+            for conf_model in conformance_res.keys():
+                if model.get_name() == conf_model.get_name() and \
+                   model.get_framework() == conf_model.get_framework() and \
+                   model.get_precision() == conf_model.get_precision():
+                    conformance_status = conformance_res[conf_model]
+                    break
+            csv_writer.writerow([
+                model.get_name(),
+                model.get_framework(),
+                model.get_precision(),
+                accuracy_status,
+                conformance_status,
+                True if conformance_status == accuracy_status else False
+                ])
+        csv_file.close()
+
+if __name__ == "__main__":
+    args = parse_arguments()
+    models = process_model_list(args.model)
+    models_accuracy = process_accuracy(args.accuracy, args.device)
+    models_conformance = process_conformance(args.conformance)
+    test_results_to_csv(models, models_accuracy, models_conformance)