[Refactor] Relative imports wherever we can (#21880)

* initial commit

* update

* second batch

* style

* fix imports

* fix relative import on pipeline

src/transformers/models/deit/image_processing_deit.py

@@ -18,9 +18,6 @@ from typing import Dict, List, Optional, Union
 
 import numpy as np
 
-from transformers.utils import is_vision_available
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
 from ...image_utils import (
@@ -33,7 +30,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, is_vision_available, logging
 
 
 if is_vision_available():

src/transformers/models/detr/image_processing_detr.py

@@ -22,8 +22,8 @@ from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Un
 
 import numpy as np
 
-from transformers.image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
-from transformers.image_transforms import (
+from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
+from ...image_transforms import (
     PaddingMode,
     center_to_corners_format,
     corners_to_center_format,
@@ -35,7 +35,7 @@ from transformers.image_transforms import (
     rgb_to_id,
     to_channel_dimension_format,
 )
-from transformers.image_utils import (
+from ...image_utils import (
     IMAGENET_DEFAULT_MEAN,
     IMAGENET_DEFAULT_STD,
     ChannelDimension,
@@ -49,7 +49,9 @@ from transformers.image_utils import (
     valid_coco_panoptic_annotations,
     valid_images,
 )
-from transformers.utils import (
+from ...utils import (
+    ExplicitEnum,
+    TensorType,
     is_flax_available,
     is_jax_tensor,
     is_scipy_available,
@@ -59,7 +61,6 @@ from transformers.utils import (
     is_torch_tensor,
     is_vision_available,
 )
-from transformers.utils.generic import ExplicitEnum, TensorType
 
 
 if is_torch_available():

src/transformers/models/distilbert/modeling_distilbert.py

@@ -27,9 +27,8 @@ import torch
 from torch import nn
 from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
 
-from transformers.configuration_utils import PretrainedConfig
-
 from ...activations import get_activation
+from ...configuration_utils import PretrainedConfig
 from ...deepspeed import is_deepspeed_zero3_enabled
 from ...modeling_outputs import (
     BaseModelOutput,

src/transformers/models/dpt/image_processing_dpt.py

@@ -19,9 +19,6 @@ from typing import Dict, Iterable, List, Optional, Tuple, Union
 
 import numpy as np
 
-from transformers.utils import is_vision_available
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
 from ...image_utils import (
@@ -37,7 +34,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, is_vision_available, logging
 
 
 if is_torch_available():

src/transformers/models/efficientformer/image_processing_efficientformer.py

@@ -18,8 +18,6 @@ from typing import Dict, List, Optional, Union
 
 import numpy as np
 
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import (
     center_crop,
@@ -39,7 +37,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, logging
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/efficientnet/image_processing_efficientnet.py

@@ -18,9 +18,6 @@ from typing import Dict, List, Optional, Union
 
 import numpy as np
 
-from transformers.utils import is_vision_available
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
 from ...image_utils import (
@@ -33,7 +30,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, is_vision_available, logging
 
 
 if is_vision_available():

src/transformers/models/flava/image_processing_flava.py

@@ -21,9 +21,6 @@ from typing import Any, Dict, Iterable, List, Optional, Tuple, Union
 
 import numpy as np
 
-from transformers.utils import is_vision_available
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
 from ...image_utils import (
@@ -36,7 +33,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, is_vision_available, logging
 
 
 if is_vision_available():

src/transformers/models/flava/modeling_flava.py

@@ -24,13 +24,12 @@ import torch
 import torch.utils.checkpoint
 from torch import nn
 
-from transformers.utils.doc import add_code_sample_docstrings
-
 from ...activations import ACT2FN
 from ...modeling_outputs import BaseModelOutput, BaseModelOutputWithPooling
 from ...modeling_utils import PreTrainedModel, find_pruneable_heads_and_indices, prune_linear_layer
 from ...utils import (
     ModelOutput,
+    add_code_sample_docstrings,
     add_start_docstrings,
     add_start_docstrings_to_model_forward,
     logging,

src/transformers/models/glpn/image_processing_glpn.py

@@ -19,13 +19,17 @@ from typing import List, Optional, Union
 import numpy as np
 import PIL.Image
 
-from transformers.image_utils import PILImageResampling
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature
 from ...image_transforms import rescale, resize, to_channel_dimension_format
-from ...image_utils import ChannelDimension, get_image_size, make_list_of_images, to_numpy_array, valid_images
-from ...utils import logging
+from ...image_utils import (
+    ChannelDimension,
+    PILImageResampling,
+    get_image_size,
+    make_list_of_images,
+    to_numpy_array,
+    valid_images,
+)
+from ...utils import TensorType, logging
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/gpt2/configuration_gpt2.py

@@ -17,8 +17,7 @@
 from collections import OrderedDict
 from typing import Any, List, Mapping, Optional
 
-from transformers import PreTrainedTokenizer, TensorType, is_torch_available
-
+from ... import PreTrainedTokenizer, TensorType, is_torch_available
 from ...configuration_utils import PretrainedConfig
 from ...onnx import OnnxConfigWithPast, PatchingSpec
 from ...utils import logging

src/transformers/models/hubert/modeling_hubert.py

@@ -23,9 +23,8 @@ import torch.utils.checkpoint
 from torch import nn
 from torch.nn import CrossEntropyLoss
 
-from transformers.deepspeed import is_deepspeed_zero3_enabled
-
 from ...activations import ACT2FN
+from ...deepspeed import is_deepspeed_zero3_enabled
 from ...modeling_outputs import BaseModelOutput, CausalLMOutput, SequenceClassifierOutput
 from ...modeling_utils import PreTrainedModel
 from ...pytorch_utils import torch_int_div

src/transformers/models/ibert/configuration_ibert.py

@@ -18,9 +18,8 @@
 from collections import OrderedDict
 from typing import Mapping
 
-from transformers.onnx import OnnxConfig
-
 from ...configuration_utils import PretrainedConfig
+from ...onnx import OnnxConfig
 from ...utils import logging
 
 

src/transformers/models/imagegpt/image_processing_imagegpt.py

@@ -18,9 +18,6 @@ from typing import Dict, List, Optional, Union
 
 import numpy as np
 
-from transformers.utils import is_vision_available
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import rescale, resize, to_channel_dimension_format
 from ...image_utils import (
@@ -31,7 +28,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, is_vision_available, logging
 
 
 if is_vision_available():

src/transformers/models/jukebox/tokenization_jukebox.py

@@ -25,11 +25,10 @@ from typing import Any, Dict, List, Optional, Tuple, Union
 import numpy as np
 import regex
 
-from transformers.utils.generic import _is_jax, _is_numpy
-
 from ...tokenization_utils import AddedToken, PreTrainedTokenizer
 from ...tokenization_utils_base import BatchEncoding
 from ...utils import TensorType, is_flax_available, is_tf_available, is_torch_available, logging
+from ...utils.generic import _is_jax, _is_numpy
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/layoutlm/configuration_layoutlm.py

@@ -16,11 +16,9 @@
 from collections import OrderedDict
 from typing import Any, List, Mapping, Optional
 
-from transformers import PretrainedConfig, PreTrainedTokenizer, TensorType
-
-from ... import is_torch_available
+from ... import PretrainedConfig, PreTrainedTokenizer
 from ...onnx import OnnxConfig, PatchingSpec
-from ...utils import logging
+from ...utils import TensorType, is_torch_available, logging
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/layoutlmv2/image_processing_layoutlmv2.py

@@ -18,9 +18,6 @@ from typing import Dict, Optional, Union
 
 import numpy as np
 
-from transformers.utils import is_vision_available
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import resize, to_channel_dimension_format, to_pil_image
 from ...image_utils import (
@@ -32,7 +29,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import is_pytesseract_available, logging, requires_backends
+from ...utils import TensorType, is_pytesseract_available, is_vision_available, logging, requires_backends
 
 
 if is_vision_available():

src/transformers/models/layoutlmv3/image_processing_layoutlmv3.py

@@ -18,9 +18,6 @@ from typing import Dict, Iterable, Optional, Union
 
 import numpy as np
 
-from transformers.utils import is_vision_available
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
 from ...image_utils import (
@@ -34,7 +31,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import is_pytesseract_available, logging, requires_backends
+from ...utils import TensorType, is_pytesseract_available, is_vision_available, logging, requires_backends
 
 
 if is_vision_available():

src/transformers/models/layoutlmv3/modeling_layoutlmv3.py

@@ -24,18 +24,16 @@ import torch.nn.functional as F
 import torch.utils.checkpoint
 from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
 
-from transformers import apply_chunking_to_forward
-from transformers.modeling_outputs import (
+from ...activations import ACT2FN
+from ...modeling_outputs import (
     BaseModelOutput,
     QuestionAnsweringModelOutput,
     SequenceClassifierOutput,
     TokenClassifierOutput,
 )
-from transformers.modeling_utils import PreTrainedModel
-from transformers.utils import logging
-
-from ...activations import ACT2FN
-from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings
+from ...modeling_utils import PreTrainedModel
+from ...pytorch_utils import apply_chunking_to_forward
+from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
 from .configuration_layoutlmv3 import LayoutLMv3Config
 
 

src/transformers/models/levit/image_processing_levit.py

@@ -18,8 +18,6 @@ from typing import Dict, Iterable, List, Optional, Union
 
 import numpy as np
 
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import (
     center_crop,
@@ -39,7 +37,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, logging
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/lxmert/modeling_tf_lxmert.py

@@ -23,8 +23,6 @@ from typing import Dict, Optional, Tuple, Union
 import numpy as np
 import tensorflow as tf
 
-from transformers.tf_utils import stable_softmax
-
 from ...activations_tf import get_tf_activation
 from ...modeling_tf_utils import (
     TFModelInputType,
@@ -34,6 +32,7 @@ from ...modeling_tf_utils import (
     shape_list,
     unpack_inputs,
 )
+from ...tf_utils import stable_softmax
 from ...utils import (
     ModelOutput,
     add_code_sample_docstrings,