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fix pylint notifs
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parent
52c522d019
commit
42dd7a59e3
@ -19,6 +19,7 @@ from comfy.cmd import folder_paths
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from comfy import node_helpers
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from comfy import node_helpers
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from comfy.cli_args import args
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from comfy.cli_args import args
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from comfy.comfy_types.node_typing import IO
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from comfy.comfy_types.node_typing import IO
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from comfy.execution_context import current_execution_context
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from comfy.weight_adapter import adapters
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from comfy.weight_adapter import adapters
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from . import nodes_custom_sampler
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from . import nodes_custom_sampler
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@ -470,6 +471,8 @@ class TrainLoraNode:
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criterion = torch.nn.HuberLoss()
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criterion = torch.nn.HuberLoss()
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elif loss_function == "SmoothL1":
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elif loss_function == "SmoothL1":
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criterion = torch.nn.SmoothL1Loss()
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criterion = torch.nn.SmoothL1Loss()
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else:
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criterion = None
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# setup models
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# setup models
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for m in find_all_highest_child_module_with_forward(mp.model.diffusion_model):
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for m in find_all_highest_child_module_with_forward(mp.model.diffusion_model):
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@ -493,7 +496,7 @@ class TrainLoraNode:
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# Training loop
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# Training loop
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torch.cuda.empty_cache()
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torch.cuda.empty_cache()
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try:
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try:
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for step in (pbar:=tqdm.trange(steps, desc="Training LoRA", smoothing=0.01, disable=not comfy.utils.PROGRESS_BAR_ENABLED)):
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for step in (pbar:=tqdm.trange(steps, desc="Training LoRA", smoothing=0.01, disable=not current_execution_context().server.receive_all_progress_notifications)):
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# Generate random sigma
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# Generate random sigma
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sigma = mp.model.model_sampling.percent_to_sigma(
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sigma = mp.model.model_sampling.percent_to_sigma(
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torch.rand((1,)).item()
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torch.rand((1,)).item()
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