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

* initial commit

* update

* second batch

* style

* fix imports

* fix relative import on pipeline

src/transformers/models/markuplm/configuration_markuplm.py

@@ -14,9 +14,8 @@
 # limitations under the License.
 """ MarkupLM model configuration"""
 
-from transformers.utils import logging
-
 from ...configuration_utils import PretrainedConfig
+from ...utils import logging
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/markuplm/modeling_markuplm.py

@@ -23,13 +23,13 @@ import torch.utils.checkpoint
 from torch import nn
 from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
 
-from transformers.activations import ACT2FN
-from transformers.file_utils import (
+from ...activations import ACT2FN
+from ...file_utils import (
     add_start_docstrings,
     add_start_docstrings_to_model_forward,
     replace_return_docstrings,
 )
-from transformers.modeling_outputs import (
+from ...modeling_outputs import (
     BaseModelOutputWithPastAndCrossAttentions,
     BaseModelOutputWithPoolingAndCrossAttentions,
     MaskedLMOutput,
@@ -37,14 +37,13 @@ from transformers.modeling_outputs import (
     SequenceClassifierOutput,
     TokenClassifierOutput,
 )
-from transformers.modeling_utils import (
+from ...modeling_utils import (
     PreTrainedModel,
     apply_chunking_to_forward,
     find_pruneable_heads_and_indices,
     prune_linear_layer,
 )
-from transformers.utils import logging
-
+from ...utils import logging
 from .configuration_markuplm import MarkupLMConfig
 
 

src/transformers/models/mask2former/image_processing_mask2former.py

@@ -20,8 +20,8 @@ from typing import Any, Dict, Iterable, List, Optional, Set, Tuple, Union
 
 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,
     get_resize_output_image_size,
     normalize,
@@ -31,7 +31,7 @@ from transformers.image_transforms import (
     to_channel_dimension_format,
     to_numpy_array,
 )
-from transformers.image_utils import (
+from ...image_utils import (
     ChannelDimension,
     ImageInput,
     PILImageResampling,
@@ -40,7 +40,7 @@ from transformers.image_utils import (
     is_batched,
     valid_images,
 )
-from transformers.utils import (
+from ...utils import (
     IMAGENET_DEFAULT_MEAN,
     IMAGENET_DEFAULT_STD,
     TensorType,

src/transformers/models/mask2former/modeling_mask2former.py

@@ -24,9 +24,7 @@ import numpy as np
 import torch
 from torch import Tensor, nn
 
-from transformers import AutoBackbone, SwinConfig
-from transformers.utils import logging
-
+from ... import AutoBackbone, SwinConfig
 from ...activations import ACT2FN
 from ...file_utils import (
     ModelOutput,
@@ -38,6 +36,7 @@ from ...file_utils import (
 )
 from ...modeling_outputs import BaseModelOutput, BaseModelOutputWithCrossAttentions
 from ...modeling_utils import PreTrainedModel
+from ...utils import logging
 from .configuration_mask2former import Mask2FormerConfig
 
 

src/transformers/models/maskformer/feature_extraction_maskformer.py

@@ -16,8 +16,7 @@
 
 import warnings
 
-from transformers.utils import logging
-
+from ...utils import logging
 from .image_processing_maskformer import MaskFormerImageProcessor
 
 

src/transformers/models/maskformer/image_processing_maskformer.py

@@ -20,8 +20,8 @@ from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Set, Tupl
 
 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,
     get_resize_output_image_size,
     normalize,
@@ -31,7 +31,7 @@ from transformers.image_transforms import (
     to_channel_dimension_format,
     to_numpy_array,
 )
-from transformers.image_utils import (
+from ...image_utils import (
     ChannelDimension,
     ImageInput,
     PILImageResampling,
@@ -40,7 +40,7 @@ from transformers.image_utils import (
     make_list_of_images,
     valid_images,
 )
-from transformers.utils import (
+from ...utils import (
     IMAGENET_DEFAULT_MEAN,
     IMAGENET_DEFAULT_STD,
     TensorType,

src/transformers/models/maskformer/modeling_maskformer.py

@@ -24,9 +24,7 @@ import numpy as np
 import torch
 from torch import Tensor, nn
 
-from transformers import AutoBackbone
-from transformers.utils import logging
-
+from ... import AutoBackbone
 from ...activations import ACT2FN
 from ...modeling_outputs import BaseModelOutputWithCrossAttentions
 from ...modeling_utils import PreTrainedModel
@@ -35,6 +33,7 @@ from ...utils import (
     add_start_docstrings,
     add_start_docstrings_to_model_forward,
     is_scipy_available,
+    logging,
     replace_return_docstrings,
     requires_backends,
 )

src/transformers/models/mobilenet_v1/image_processing_mobilenet_v1.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/mobilenet_v2/image_processing_mobilenet_v2.py

@@ -18,9 +18,6 @@ from typing import Dict, List, Optional, Tuple, Union
 
 import numpy as np
 
-from transformers.utils import is_torch_available, is_torch_tensor
-from transformers.utils.generic import TensorType
-
 from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
 from ...image_transforms import (
     center_crop,
@@ -40,7 +37,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, is_torch_available, is_torch_tensor, logging
 
 
 if is_torch_available():

src/transformers/models/mobilevit/image_processing_mobilevit.py

@@ -18,9 +18,6 @@ from typing import Dict, List, Optional, Tuple, Union
 
 import numpy as np
 
-from transformers.utils import is_torch_available, is_torch_tensor, 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, get_resize_output_image_size, rescale, resize, to_channel_dimension_format
 from ...image_utils import (
@@ -32,7 +29,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, is_torch_available, is_torch_tensor, is_vision_available, logging
 
 
 if is_vision_available():

src/transformers/models/nezha/configuration_nezha.py

-from transformers import PretrainedConfig
+from ... import PretrainedConfig
 
 
 NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP = {

src/transformers/models/oneformer/image_processing_oneformer.py

@@ -21,8 +21,8 @@ from typing import Any, Dict, Iterable, List, Optional, Set, Tuple, Union
 import numpy as np
 from huggingface_hub import hf_hub_download
 
-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,
     get_resize_output_image_size,
     normalize,
@@ -32,7 +32,7 @@ from transformers.image_transforms import (
     to_channel_dimension_format,
     to_numpy_array,
 )
-from transformers.image_utils import (
+from ...image_utils import (
     ChannelDimension,
     ImageInput,
     PILImageResampling,
@@ -41,7 +41,7 @@ from transformers.image_utils import (
     make_list_of_images,
     valid_images,
 )
-from transformers.utils import (
+from ...utils import (
     IMAGENET_DEFAULT_MEAN,
     IMAGENET_DEFAULT_STD,
     TensorType,

src/transformers/models/oneformer/modeling_oneformer.py

@@ -24,9 +24,7 @@ import torch
 from torch import Tensor, nn
 from torch.cuda.amp import autocast
 
-from transformers import AutoBackbone
-from transformers.utils import logging
-
+from ... import AutoBackbone
 from ...activations import ACT2FN
 from ...modeling_outputs import BaseModelOutput
 from ...modeling_utils import PreTrainedModel
@@ -35,6 +33,7 @@ from ...utils import (
     add_start_docstrings,
     add_start_docstrings_to_model_forward,
     is_scipy_available,
+    logging,
     replace_return_docstrings,
     requires_backends,
 )

src/transformers/models/oneformer/processing_oneformer.py

@@ -18,9 +18,8 @@ Image/Text processor class for OneFormer
 
 from typing import List
 
-from transformers.utils import is_torch_available
-
 from ...processing_utils import ProcessorMixin
+from ...utils import is_torch_available
 
 
 if is_torch_available():

src/transformers/models/owlvit/image_processing_owlvit.py

@@ -19,8 +19,8 @@ from typing import Dict, List, Optional, Tuple, Union
 
 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 (
     center_crop,
     center_to_corners_format,
     normalize,
@@ -29,7 +29,7 @@ from transformers.image_transforms import (
     to_channel_dimension_format,
     to_numpy_array,
 )
-from transformers.image_utils import (
+from ...image_utils import (
     OPENAI_CLIP_MEAN,
     OPENAI_CLIP_STD,
     ChannelDimension,
@@ -38,7 +38,7 @@ from transformers.image_utils import (
     make_list_of_images,
     valid_images,
 )
-from transformers.utils import TensorType, is_torch_available, logging
+from ...utils import TensorType, is_torch_available, logging
 
 
 if is_torch_available():

src/transformers/models/owlvit/processing_owlvit.py

@@ -21,10 +21,9 @@ from typing import List
 
 import numpy as np
 
-from transformers import is_flax_available, is_tf_available, is_torch_available
-
 from ...processing_utils import ProcessorMixin
 from ...tokenization_utils_base import BatchEncoding
+from ...utils import is_flax_available, is_tf_available, is_torch_available
 
 
 class OwlViTProcessor(ProcessorMixin):

src/transformers/models/perceiver/image_processing_perceiver.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 (
@@ -34,7 +31,7 @@ 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/poolformer/image_processing_poolformer.py

@@ -18,9 +18,6 @@ from typing import Dict, List, Optional, Union
 
 import numpy as np
 
-from transformers 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,
@@ -40,7 +37,7 @@ 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/realm/retrieval_realm.py

@@ -20,8 +20,7 @@ from typing import Optional, Union
 import numpy as np
 from huggingface_hub import hf_hub_download
 
-from transformers import AutoTokenizer
-
+from ... import AutoTokenizer
 from ...utils import logging
 
 

src/transformers/models/segformer/image_processing_segformer.py

@@ -19,9 +19,6 @@ from typing import Any, Dict, List, Optional, Tuple, Union
 
 import numpy as np
 
-from transformers.utils import is_torch_available, is_torch_tensor, 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 (
@@ -34,7 +31,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
+from ...utils import TensorType, is_torch_available, is_torch_tensor, is_vision_available, logging
 
 
 if is_vision_available():