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[DPO Training] pass tracker name as argument (#6542)
pass tracker name as argumentw
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@@ -414,6 +414,12 @@ def parse_args(input_args=None):
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default=4,
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help=("The dimension of the LoRA update matrices."),
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)
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parser.add_argument(
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"--tracker_name",
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type=str,
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default="diffusion-dpo-lora",
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help=("The name of the tracker to report results to."),
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)
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if input_args is not None:
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args = parser.parse_args(input_args)
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@@ -726,7 +732,7 @@ def main(args):
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# We need to initialize the trackers we use, and also store our configuration.
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# The trackers initializes automatically on the main process.
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if accelerator.is_main_process:
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accelerator.init_trackers("diffusion-dpo-lora", config=vars(args))
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accelerator.init_trackers(args.tracker_name, config=vars(args))
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# Train!
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total_batch_size = args.train_batch_size * accelerator.num_processes * args.gradient_accumulation_steps
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@@ -429,6 +429,12 @@ def parse_args(input_args=None):
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default=4,
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help=("The dimension of the LoRA update matrices."),
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)
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parser.add_argument(
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"--tracker_name",
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type=str,
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default="diffusion-dpo-lora-sdxl",
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help=("The name of the tracker to report results to."),
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)
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if input_args is not None:
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args = parser.parse_args(input_args)
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@@ -821,7 +827,7 @@ def main(args):
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# We need to initialize the trackers we use, and also store our configuration.
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# The trackers initializes automatically on the main process.
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if accelerator.is_main_process:
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accelerator.init_trackers("diffusion-dpo-lora-sdxl", config=vars(args))
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accelerator.init_trackers(args.tracker_name, config=vars(args))
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# Train!
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total_batch_size = args.train_batch_size * accelerator.num_processes * args.gradient_accumulation_steps
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