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Improve error handling for multigpu threads
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9726eac475
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@ -3,7 +3,7 @@ from __future__ import annotations
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import comfy.model_management
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from .k_diffusion import sampling as k_diffusion_sampling
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from .extra_samplers import uni_pc
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from typing import TYPE_CHECKING, Callable, NamedTuple
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from typing import TYPE_CHECKING, Callable, NamedTuple, Any
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if TYPE_CHECKING:
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from comfy.model_patcher import ModelPatcher
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from comfy.model_base import BaseModel
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@ -428,8 +428,16 @@ def _calc_cond_batch_multigpu(model: BaseModel, conds: list[list[dict]], x_in: t
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if batched_to_run_length >= conds_per_device:
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index_device += 1
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thread_result = collections.namedtuple('thread_result', ['output', 'mult', 'area', 'batch_chunks', 'cond_or_uncond'])
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class thread_result(NamedTuple):
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output: Any
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mult: Any
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area: Any
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batch_chunks: int
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cond_or_uncond: Any
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error: Exception = None
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def _handle_batch(device: torch.device, batch_tuple: tuple[comfy.hooks.HookGroup, tuple], results: list[thread_result]):
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try:
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model_current: BaseModel = model_options["multigpu_clones"][device].model
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# run every hooked_to_run separately
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with torch.no_grad():
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@ -496,6 +504,9 @@ def _calc_cond_batch_multigpu(model: BaseModel, conds: list[list[dict]], x_in: t
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else:
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output = model_current.apply_model(input_x, timestep_, **c).to(output_device).chunk(batch_chunks)
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results.append(thread_result(output, mult, area, batch_chunks, cond_or_uncond))
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except Exception as e:
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results.append(thread_result(None, None, None, None, None, error=e))
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raise
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results: list[thread_result] = []
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@ -508,7 +519,9 @@ def _calc_cond_batch_multigpu(model: BaseModel, conds: list[list[dict]], x_in: t
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for thread in threads:
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thread.join()
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for output, mult, area, batch_chunks, cond_or_uncond in results:
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for output, mult, area, batch_chunks, cond_or_uncond, error in results:
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if error is not None:
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raise error
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for o in range(batch_chunks):
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cond_index = cond_or_uncond[o]
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a = area[o]
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