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Use consistent --gpu-id option name
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b84fd70cc3
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@ -25,7 +25,7 @@ def debug_model_cli(
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P1: bool = Opt(False, "--print-step1", "-P1", help="Print model after initialization"),
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P2: bool = Opt(False, "--print-step2", "-P2", help="Print model after training"),
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P3: bool = Opt(True, "--print-step3", "-P3", help="Print final predictions"),
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use_gpu: int = Opt(-1, "--use-gpu", "-g", help="GPU ID or -1 for CPU")
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use_gpu: int = Opt(-1, "--gpu-id", "-g", help="GPU ID or -1 for CPU")
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# fmt: on
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):
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"""
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@ -36,7 +36,7 @@ def pretrain_cli(
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code_path: Optional[Path] = Opt(None, "--code-path", "-c", help="Path to Python file with additional code (registered functions) to be imported"),
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resume_path: Optional[Path] = Opt(None, "--resume-path", "-r", help="Path to pretrained weights from which to resume pretraining"),
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epoch_resume: Optional[int] = Opt(None, "--epoch-resume", "-er", help="The epoch to resume counting from when using '--resume_path'. Prevents unintended overwriting of existing weight files."),
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use_gpu: int = Opt(-1, "--use-gpu", "-g", help="GPU ID or -1 for CPU"),
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use_gpu: int = Opt(-1, "--gpu-id", "-g", help="GPU ID or -1 for CPU"),
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# fmt: on
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):
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"""
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@ -36,7 +36,7 @@ def train_cli(
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output_path: Optional[Path] = Opt(None, "--output", "--output-path", "-o", help="Output directory to store model in"),
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code_path: Optional[Path] = Opt(None, "--code-path", "-c", help="Path to Python file with additional code (registered functions) to be imported"),
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verbose: bool = Opt(False, "--verbose", "-V", "-VV", help="Display more information for debugging purposes"),
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use_gpu: int = Opt(-1, "--use-gpu", "-g", help="GPU ID or -1 for CPU"),
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use_gpu: int = Opt(-1, "--gpu-id", "-g", help="GPU ID or -1 for CPU"),
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resume: bool = Opt(False, "--resume", "-R", help="Resume training"),
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# fmt: on
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):
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