dynamic_vram: Training fixes (#12442)
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@@ -1561,6 +1561,8 @@ class ModelPatcherDynamic(ModelPatcher):
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allocated_size += weight_size
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vbar.set_watermark_limit(allocated_size)
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move_weight_functions(m, device_to)
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logging.info(f"Model {self.model.__class__.__name__} prepared for dynamic VRAM loading. {allocated_size // (1024 ** 2)}MB Staged. {num_patches} patches attached.")
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self.model.device = device_to
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@@ -1601,6 +1603,8 @@ class ModelPatcherDynamic(ModelPatcher):
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if unpatch_weights:
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self.partially_unload_ram(1e32)
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self.partially_unload(None, 1e32)
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for m in self.model.modules():
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move_weight_functions(m, device_to)
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def partially_load(self, device_to, extra_memory=0, force_patch_weights=False):
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assert not force_patch_weights #See above
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