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Merge branch 'master' into worksplit-multigpu
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@@ -18,6 +18,7 @@ import comfy.sampler_helpers
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import comfy.model_patcher
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import comfy.patcher_extension
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import comfy.hooks
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import comfy.context_windows
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import scipy.stats
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import numpy
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import threading
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@@ -203,14 +204,20 @@ def finalize_default_conds(model: 'BaseModel', hooked_to_run: dict[comfy.hooks.H
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hooked_to_run.setdefault(p.hooks, list())
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hooked_to_run[p.hooks] += [(p, i)]
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def calc_cond_batch(model: 'BaseModel', conds: list[list[dict]], x_in: torch.Tensor, timestep, model_options):
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def calc_cond_batch(model: BaseModel, conds: list[list[dict]], x_in: torch.Tensor, timestep, model_options: dict[str]):
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handler: comfy.context_windows.ContextHandlerABC = model_options.get("context_handler", None)
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if handler is None or not handler.should_use_context(model, conds, x_in, timestep, model_options):
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return _calc_cond_batch_outer(model, conds, x_in, timestep, model_options)
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return handler.execute(_calc_cond_batch_outer, model, conds, x_in, timestep, model_options)
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def _calc_cond_batch_outer(model: BaseModel, conds: list[list[dict]], x_in: torch.Tensor, timestep, model_options):
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executor = comfy.patcher_extension.WrapperExecutor.new_executor(
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_calc_cond_batch,
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comfy.patcher_extension.get_all_wrappers(comfy.patcher_extension.WrappersMP.CALC_COND_BATCH, model_options, is_model_options=True)
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)
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return executor.execute(model, conds, x_in, timestep, model_options)
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def _calc_cond_batch(model: 'BaseModel', conds: list[list[dict]], x_in: torch.Tensor, timestep: torch.Tensor, model_options: dict[str]):
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def _calc_cond_batch(model: BaseModel, conds: list[list[dict]], x_in: torch.Tensor, timestep: torch.Tensor, model_options: dict[str]):
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if 'multigpu_clones' in model_options:
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return _calc_cond_batch_multigpu(model, conds, x_in, timestep, model_options)
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out_conds = []
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