#260 Adding error schema in metadata (#266)

netspresso/benchmarker/v2/benchmarker.py

@@ -197,6 +197,7 @@ def benchmark_model(
         except Exception as e:
             logger.error(f"Benchmark failed. Error: {e}")
             benchmarker_metadata.status = Status.ERROR
+            benchmarker_metadata.update_message(exception_detail=e.args[0])
             metadatas[-1] = asdict(benchmarker_metadata)
             MetadataHandler.save_json(
                 data=metadatas,

netspresso/compressor/v2/compressor.py

@@ -1,4 +1,5 @@
 import sys
+from dataclasses import asdict
 from pathlib import Path
 from typing import Dict, List, Optional
 from urllib import request
@@ -626,6 +627,7 @@ def automatic_compression(
         except Exception as e:
             logger.error(f"Automatic compression failed. Error: {e}")
             metadata.update_status(status=Status.ERROR)
+            metadata.update_message(exception_detail=e.args[0])
             MetadataHandler.save_json(data=metadata.asdict(), folder_path=output_dir)
             raise e
 

netspresso/converter/v2/converter.py

@@ -220,6 +220,7 @@ def convert_model(
         except Exception as e:
             logger.error(f"Convert failed. Error: {e}")
             converter_metadata.status = Status.ERROR
+            converter_metadata.update_message(exception_detail=e.args[0])
             MetadataHandler.save_json(
                 data=asdict(converter_metadata), folder_path=output_dir
             )

netspresso/metadata/benchmarker.py

@@ -6,9 +6,9 @@
     DeviceName,
     HardwareType,
     SoftwareVersion,
-    Status,
     TaskType,
 )
+from netspresso.metadata.common import BaseMetadata
 
 
 @dataclass
@@ -44,9 +44,7 @@ class BenchmarkEnvironment:
 
 
 @dataclass
-class BenchmarkerMetadata:
-    status: Status = Status.IN_PROGRESS
-    message: str = ""
+class BenchmarkerMetadata(BaseMetadata):
     task_type: TaskType = TaskType.BENCHMARK
     input_model_path: str = ""
     benchmark_task_info: BenchmarkTaskInfo = field(default_factory=BenchmarkTaskInfo)

netspresso/metadata/common.py

@@ -1,11 +1,10 @@
-from dataclasses import dataclass, field
-from typing import List
+import json
+from dataclasses import asdict, dataclass, field
+from typing import Dict, List, Optional
 
 from netspresso.enums.device import DeviceName, HardwareType, SoftwareVersion
-from netspresso.enums.model import (
-    DataType,
-    Framework,
-)
+from netspresso.enums.metadata import Status
+from netspresso.enums.model import DataType, Framework
 
 
 @dataclass
@@ -43,3 +42,43 @@ class AvailableOption:
     framework: Framework = ""
     display_framework: str = ""
     devices: List[DeviceInfo] = field(default_factory=list)
+
+
+@dataclass
+class LinkInfo:
+    type: str
+    value: str
+
+
+@dataclass
+class AdditionalData:
+    origin: Optional[str] = ""
+    error_log: Optional[str] = ""
+    link: Optional[LinkInfo] = None
+
+
+@dataclass
+class ExceptionDetail:
+    data: Optional[AdditionalData] = field(default_factory=AdditionalData)
+    error_code: Optional[str] = ""
+    name: Optional[str] = ""
+    message: Optional[str] = ""
+
+
+@dataclass
+class BaseMetadata:
+    status: Status = Status.IN_PROGRESS
+    message: ExceptionDetail = field(default_factory=ExceptionDetail)
+
+    def asdict(self) -> Dict:
+        _dict = json.loads(json.dumps(asdict(self)))
+        return _dict
+
+    def update_message(self, exception_detail):
+        if isinstance(exception_detail, str):
+            self.message.message = exception_detail
+        else:
+            self.message = ExceptionDetail(**exception_detail)
+
+    def update_status(self, status: Status):
+        self.status = status

netspresso/metadata/compressor.py

@@ -1,10 +1,9 @@
-import json
-from dataclasses import asdict, dataclass, field
+from dataclasses import dataclass, field
 from typing import Any, Dict, List, Optional
 
-from netspresso.enums.metadata import Status, TaskType
+from netspresso.enums.metadata import TaskType
 from netspresso.enums.model import DataType, Framework
-from netspresso.metadata.common import AvailableOption, InputShape
+from netspresso.metadata.common import AvailableOption, BaseMetadata, InputShape
 from netspresso.metadata.trainer import TrainingInfo
 
 
@@ -44,9 +43,7 @@ class Results:
 
 
 @dataclass
-class CompressorMetadata:
-    status: Status = Status.IN_PROGRESS
-    message: str = ""
+class CompressorMetadata(BaseMetadata):
     task_type: TaskType = TaskType.COMPRESS
     input_model_path: str = ""
     compressed_model_path: str = ""
@@ -58,13 +55,6 @@ class CompressorMetadata:
     results: Results = field(default_factory=Results)
     available_options: List[AvailableOption] = field(default_factory=list)
 
-    def asdict(self) -> Dict:
-        _dict = json.loads(json.dumps(asdict(self)))
-        return _dict
-
-    def update_status(self, status: Status):
-        self.status = status
-
     def update_is_retrainable(self, is_retrainable):
         self.is_retrainable = is_retrainable
 

netspresso/metadata/converter.py

@@ -6,10 +6,9 @@
     DeviceName,
     Framework,
     SoftwareVersion,
-    Status,
     TaskType,
 )
-from netspresso.metadata.common import AvailableOption, ModelInfo
+from netspresso.metadata.common import AvailableOption, BaseMetadata, ModelInfo
 
 
 @dataclass
@@ -29,9 +28,7 @@ class ConvertInfo:
 
 
 @dataclass
-class ConverterMetadata:
-    status: Status = Status.IN_PROGRESS
-    message: str = ""
+class ConverterMetadata(BaseMetadata):
     task_type: TaskType = TaskType.CONVERT
     input_model_path: str = ""
     converted_model_path: str = ""

netspresso/metadata/trainer.py

@@ -1,9 +1,8 @@
-import json
-from dataclasses import asdict, dataclass, field
+from dataclasses import dataclass, field
 from typing import Dict, List
 
-from netspresso.enums.metadata import Status, TaskType
-from netspresso.metadata.common import AvailableOption, InputShape
+from netspresso.enums.metadata import TaskType
+from netspresso.metadata.common import AvailableOption, BaseMetadata, InputShape
 
 
 @dataclass
@@ -23,9 +22,7 @@ class TrainingInfo:
 
 
 @dataclass
-class TrainerMetadata:
-    status: Status = Status.IN_PROGRESS
-    message: str = ""
+class TrainerMetadata(BaseMetadata):
     task_type: TaskType = TaskType.TRAIN
     logging_dir: str = ""
     best_fx_model_path: str = ""
@@ -36,13 +33,6 @@ class TrainerMetadata:
     traning_result: Dict = field(default_factory=dict)
     available_options: List[AvailableOption] = field(default_factory=list)
 
-    def asdict(self) -> Dict:
-        _dict = json.loads(json.dumps(asdict(self)))
-        return _dict
-
-    def update_status(self, status: Status):
-        self.status = status
-
     def update_model_info(self, task, model, dataset, input_shapes):
         self.model_info.task = task
         self.model_info.model = model

netspresso/trainer/trainer.py

@@ -363,7 +363,7 @@ def _change_transforms(self, transforms: Transform):
 
             if field_type == List:
                 transform.size = [self.img_size, self.img_size]
-            elif field_type == int:
+            elif isinstance(field_type, int):
                 transform.size = self.img_size
 
         return transforms
@@ -389,6 +389,14 @@ def _get_available_options(self):
 
         return available_options
 
+    def _check_status(self, training_summary):
+        if training_summary.get("success"):
+            status = Status.COMPLETED
+        else:
+            status = Status.STOPPED if training_summary.get("error_stat", None) is None else Status.ERROR
+
+        return status
+
     def train(self, gpus: str, project_name: str, output_dir: Optional[str] = "./outputs") -> TrainerMetadata:
         """Train the model with the specified configuration.
 
@@ -444,11 +452,7 @@ def train(self, gpus: str, project_name: str, output_dir: Optional[str] = "./out
             logging=configs.logging,
             environment=configs.environment,
         )
-        training_summary_path = logging_dir / "training_summary.json"
-        training_summary = FileHandler.load_json(file_path=training_summary_path)
-        is_success = training_summary["success"]
-        status = Status.COMPLETED if is_success else Status.STOPPED
-
+        training_summary = FileHandler.load_json(file_path=logging_dir / "training_summary.json")
         FileHandler.remove_folder(configs.temp_folder)
         logger.info(f"Removed {configs.temp_folder} folder.")
 
@@ -459,6 +463,8 @@ def train(self, gpus: str, project_name: str, output_dir: Optional[str] = "./out
         best_fx_paths = list(Path(destination_folder).glob("*best_fx.pt"))
         best_onnx_paths = list(Path(destination_folder).glob("*best.onnx"))
         hparams_path = destination_folder / "hparams.yaml"
+        status = self._check_status(training_summary)
+        error_stat = training_summary.get("error_stat", "")
 
         available_options = self._get_available_options()
 
@@ -469,6 +475,7 @@ def train(self, gpus: str, project_name: str, output_dir: Optional[str] = "./out
         metadata.update_training_result(training_summary=training_summary)
         metadata.update_hparams(hparams=hparams_path.resolve().as_posix())
         metadata.update_status(status=status)
+        metadata.update_message(exception_detail=error_stat)
         metadata.update_available_options(available_options)
 
         MetadataHandler.save_json(data=metadata.asdict(), folder_path=destination_folder)