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37 lines
1.4 KiB
Python
37 lines
1.4 KiB
Python
# Copyright (c) 2023, NVIDIA CORPORATION. All rights reserved.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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from dataclasses import dataclass
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from typing import Any, Dict, Optional
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@dataclass
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class MLFlowParams:
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"""ML Flow Configuration Dataclass."""
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# name of experiment, if none, defaults to the globally set experiment name
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experiment_name: Optional[str] = None
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run_name: Optional[str] = None
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# if no run_name is set, it's set by version
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# local or remote tracking seerver. If tracking_uri is not set, it defaults to save_dir
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tracking_uri: Optional[str] = None
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tags: Optional[Dict[str, Any]] = None
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save_dir: Optional[str] = "./mlruns"
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prefix: str = ""
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artifact_location: Optional[str] = None
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# provide run_id if resuming a previously started run
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run_id: Optional[str] = None
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# Log checkpoints created by ModelCheckpoint as MLFlow artifacts.
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log_model: bool = False
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