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Merge branch 'master' into dr-support-pip-cm
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@@ -150,6 +150,7 @@ class PerformanceFeature(enum.Enum):
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parser.add_argument("--fast", nargs="*", type=PerformanceFeature, help="Enable some untested and potentially quality deteriorating optimizations. --fast with no arguments enables everything. You can pass a list specific optimizations if you only want to enable specific ones. Current valid optimizations: fp16_accumulation fp8_matrix_mult cublas_ops")
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parser.add_argument("--mmap-torch-files", action="store_true", help="Use mmap when loading ckpt/pt files.")
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parser.add_argument("--disable-mmap", action="store_true", help="Don't use mmap when loading safetensors.")
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parser.add_argument("--dont-print-server", action="store_true", help="Don't print server output.")
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parser.add_argument("--quick-test-for-ci", action="store_true", help="Quick test for CI.")
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@@ -973,7 +973,7 @@ class VideoVAE(nn.Module):
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norm_layer=config.get("norm_layer", "group_norm"),
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causal=config.get("causal_decoder", False),
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timestep_conditioning=self.timestep_conditioning,
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spatial_padding_mode=config.get("spatial_padding_mode", "zeros"),
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spatial_padding_mode=config.get("spatial_padding_mode", "reflect"),
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)
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self.per_channel_statistics = processor()
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@@ -18,7 +18,7 @@
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"single_word": false
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},
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"errors": "replace",
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"model_max_length": 77,
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"model_max_length": 8192,
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"name_or_path": "openai/clip-vit-large-patch14",
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"pad_token": "<|endoftext|>",
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"special_tokens_map_file": "./special_tokens_map.json",
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@@ -31,6 +31,7 @@ from einops import rearrange
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from comfy.cli_args import args
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MMAP_TORCH_FILES = args.mmap_torch_files
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DISABLE_MMAP = args.disable_mmap
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ALWAYS_SAFE_LOAD = False
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if hasattr(torch.serialization, "add_safe_globals"): # TODO: this was added in pytorch 2.4, the unsafe path should be removed once earlier versions are deprecated
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@@ -58,7 +59,10 @@ def load_torch_file(ckpt, safe_load=False, device=None, return_metadata=False):
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with safetensors.safe_open(ckpt, framework="pt", device=device.type) as f:
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sd = {}
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for k in f.keys():
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sd[k] = f.get_tensor(k)
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tensor = f.get_tensor(k)
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if DISABLE_MMAP: # TODO: Not sure if this is the best way to bypass the mmap issues
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tensor = tensor.to(device=device, copy=True)
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sd[k] = tensor
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if return_metadata:
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metadata = f.metadata()
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except Exception as e:
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