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@ -1,6 +1,8 @@ |
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# Ultralytics YOLO 🚀, AGPL-3.0 license |
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# Ultralytics YOLO 🚀, AGPL-3.0 license |
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import contextlib |
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import contextlib |
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import pickle |
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import types |
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from copy import deepcopy |
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from copy import deepcopy |
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from pathlib import Path |
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from pathlib import Path |
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@ -750,7 +752,35 @@ def temporary_modules(modules=None, attributes=None): |
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del sys.modules[old] |
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del sys.modules[old] |
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def torch_safe_load(weight): |
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class SafeClass: |
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"""A placeholder class to replace unknown classes during unpickling.""" |
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def __init__(self, *args, **kwargs): |
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"""Initialize SafeClass instance, ignoring all arguments.""" |
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pass |
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class SafeUnpickler(pickle.Unpickler): |
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"""Custom Unpickler that replaces unknown classes with SafeClass.""" |
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def find_class(self, module, name): |
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"""Attempt to find a class, returning SafeClass if not among safe modules.""" |
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safe_modules = ( |
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"torch", |
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"collections", |
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"collections.abc", |
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"builtins", |
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"math", |
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"numpy", |
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# Add other modules considered safe |
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) |
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if module in safe_modules: |
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return super().find_class(module, name) |
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else: |
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return SafeClass |
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def torch_safe_load(weight, safe_only=False): |
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""" |
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""" |
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Attempts to load a PyTorch model with the torch.load() function. If a ModuleNotFoundError is raised, it catches the |
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Attempts to load a PyTorch model with the torch.load() function. If a ModuleNotFoundError is raised, it catches the |
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error, logs a warning message, and attempts to install the missing module via the check_requirements() function. |
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error, logs a warning message, and attempts to install the missing module via the check_requirements() function. |
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@ -758,9 +788,18 @@ def torch_safe_load(weight): |
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Args: |
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Args: |
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weight (str): The file path of the PyTorch model. |
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weight (str): The file path of the PyTorch model. |
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safe_only (bool): If True, replace unknown classes with SafeClass during loading. |
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Example: |
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```python |
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from ultralytics.nn.tasks import torch_safe_load |
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ckpt, file = torch_safe_load("path/to/best.pt", safe_only=True) |
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``` |
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Returns: |
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Returns: |
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(dict): The loaded PyTorch model. |
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ckpt (dict): The loaded model checkpoint. |
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file (str): The loaded filename |
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""" |
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""" |
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from ultralytics.utils.downloads import attempt_download_asset |
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from ultralytics.utils.downloads import attempt_download_asset |
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@ -779,7 +818,15 @@ def torch_safe_load(weight): |
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"ultralytics.utils.loss.v10DetectLoss": "ultralytics.utils.loss.E2EDetectLoss", # YOLOv10 |
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"ultralytics.utils.loss.v10DetectLoss": "ultralytics.utils.loss.E2EDetectLoss", # YOLOv10 |
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}, |
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}, |
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): |
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): |
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ckpt = torch.load(file, map_location="cpu") |
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if safe_only: |
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# Load via custom pickle module |
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safe_pickle = types.ModuleType("safe_pickle") |
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safe_pickle.Unpickler = SafeUnpickler |
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safe_pickle.load = lambda file_obj: SafeUnpickler(file_obj).load() |
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with open(file, "rb") as f: |
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ckpt = torch.load(f, pickle_module=safe_pickle) |
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else: |
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ckpt = torch.load(file, map_location="cpu") |
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except ModuleNotFoundError as e: # e.name is missing module name |
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except ModuleNotFoundError as e: # e.name is missing module name |
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if e.name == "models": |
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if e.name == "models": |
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@ -809,7 +856,7 @@ def torch_safe_load(weight): |
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) |
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) |
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ckpt = {"model": ckpt.model} |
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ckpt = {"model": ckpt.model} |
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return ckpt, file # load |
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return ckpt, file |
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def attempt_load_weights(weights, device=None, inplace=True, fuse=False): |
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def attempt_load_weights(weights, device=None, inplace=True, fuse=False): |
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