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""" |
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Generic utilities |
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""" |
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import warnings |
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from collections import OrderedDict |
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from dataclasses import fields |
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from typing import Any, Tuple |
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import numpy as np |
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from .import_utils import is_torch_available |
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def is_tensor(x): |
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""" |
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Tests if `x` is a `torch.Tensor` or `np.ndarray`. |
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""" |
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if is_torch_available(): |
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import torch |
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if isinstance(x, torch.Tensor): |
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return True |
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return isinstance(x, np.ndarray) |
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class BaseOutput(OrderedDict): |
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""" |
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Base class for all model outputs as dataclass. Has a `__getitem__` that allows indexing by integer or slice (like a |
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tuple) or strings (like a dictionary) that will ignore the `None` attributes. Otherwise behaves like a regular |
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python dictionary. |
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<Tip warning={true}> |
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You can't unpack a `BaseOutput` directly. Use the [`~utils.BaseOutput.to_tuple`] method to convert it to a tuple |
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before. |
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</Tip> |
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""" |
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def __post_init__(self): |
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class_fields = fields(self) |
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if not len(class_fields): |
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raise ValueError(f"{self.__class__.__name__} has no fields.") |
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for field in class_fields: |
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v = getattr(self, field.name) |
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if v is not None: |
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self[field.name] = v |
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def __delitem__(self, *args, **kwargs): |
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raise Exception(f"You cannot use ``__delitem__`` on a {self.__class__.__name__} instance.") |
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def setdefault(self, *args, **kwargs): |
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raise Exception(f"You cannot use ``setdefault`` on a {self.__class__.__name__} instance.") |
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def pop(self, *args, **kwargs): |
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raise Exception(f"You cannot use ``pop`` on a {self.__class__.__name__} instance.") |
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def update(self, *args, **kwargs): |
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raise Exception(f"You cannot use ``update`` on a {self.__class__.__name__} instance.") |
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def __getitem__(self, k): |
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if isinstance(k, str): |
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inner_dict = {k: v for (k, v) in self.items()} |
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if self.__class__.__name__ in ["StableDiffusionPipelineOutput", "ImagePipelineOutput"] and k == "sample": |
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warnings.warn( |
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"The keyword 'samples' is deprecated and will be removed in version 0.4.0. Please use `.images` or" |
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" `'images'` instead.", |
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DeprecationWarning, |
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) |
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return inner_dict["images"] |
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return inner_dict[k] |
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else: |
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return self.to_tuple()[k] |
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def __setattr__(self, name, value): |
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if name in self.keys() and value is not None: |
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super().__setitem__(name, value) |
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super().__setattr__(name, value) |
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def __setitem__(self, key, value): |
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super().__setitem__(key, value) |
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super().__setattr__(key, value) |
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def to_tuple(self) -> Tuple[Any]: |
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""" |
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Convert self to a tuple containing all the attributes/keys that are not `None`. |
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""" |
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return tuple(self[k] for k in self.keys()) |
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