Fast image processor (#28847)

* Draft fast image processors

* Draft working fast version

* py3.8 compatible cache

* Enable loading fast image processors through auto

* Tidy up; rescale behaviour based on input type

* Enable tests for fast image processors

* Smarter rescaling

* Don't default to Fast

* Safer imports

* Add necessary Pillow requirement

* Woops

* Add AutoImageProcessor test

* Fix up

* Fix test for imagegpt

* Fix test

* Review comments

* Add warning for TF and JAX input types

* Rearrange

* Return transforms

* NumpyToTensor transformation

* Rebase - include changes from upstream in ImageProcessingMixin

* Safe typing

* Fix up

* convert mean/std to tesnor to rescale

* Don't store transforms in state

* Fix up

* Update src/transformers/image_processing_utils_fast.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/auto/image_processing_auto.py

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Warn if fast image processor available

* Update src/transformers/models/vit/image_processing_vit_fast.py

* Transpose incoming numpy images to be in CHW format

* Update mapping names based on packages, auto set fast to None

* Fix up

* Fix

* Add AutoImageProcessor.from_pretrained(checkpoint, use_fast=True) test

* Update src/transformers/models/vit/image_processing_vit_fast.py

Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* Add equivalence and speed tests

* Fix up

---------

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

src/transformers/image_processing_utils_fast.py

@@ -0,0 +1,63 @@
+# coding=utf-8
+# Copyright 2024 The HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import functools
+from dataclasses import dataclass
+
+from .image_processing_utils import BaseImageProcessor
+from .utils.import_utils import is_torchvision_available
+
+
+if is_torchvision_available():
+    from torchvision.transforms import Compose
+
+
+@dataclass(frozen=True)
+class SizeDict:
+    """
+    Hashable dictionary to store image size information.
+    """
+
+    height: int = None
+    width: int = None
+    longest_edge: int = None
+    shortest_edge: int = None
+    max_height: int = None
+    max_width: int = None
+
+    def __getitem__(self, key):
+        if hasattr(self, key):
+            return getattr(self, key)
+        raise KeyError(f"Key {key} not found in SizeDict.")
+
+
+class BaseImageProcessorFast(BaseImageProcessor):
+    _transform_params = None
+
+    def _build_transforms(self, **kwargs) -> "Compose":
+        """
+        Given the input settings e.g. do_resize, build the image transforms.
+        """
+        raise NotImplementedError
+
+    def _validate_params(self, **kwargs) -> None:
+        for k, v in kwargs.items():
+            if k not in self._transform_params:
+                raise ValueError(f"Invalid transform parameter {k}={v}.")
+
+    @functools.lru_cache(maxsize=1)
+    def get_transforms(self, **kwargs) -> "Compose":
+        self._validate_params(**kwargs)
+        return self._build_transforms(**kwargs)