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

* initial commit

* update

* second batch

* style

* fix imports

* fix relative import on pipeline

src/transformers/commands/add_new_model_like.py

@@ -23,9 +23,8 @@ from itertools import chain
 from pathlib import Path
 from typing import Any, Callable, Dict, List, Optional, Pattern, Tuple, Union
 
-import transformers.models.auto as auto_module
-from transformers.models.auto.configuration_auto import model_type_to_module_name
-
+from ..models import auto as auto_module
+from ..models.auto.configuration_auto import model_type_to_module_name
 from ..utils import is_flax_available, is_tf_available, is_torch_available, logging
 from . import BaseTransformersCLICommand
 

src/transformers/image_transforms.py

@@ -18,7 +18,7 @@ from typing import Iterable, List, Optional, Tuple, Union
 
 import numpy as np
 
-from transformers.image_utils import (
+from .image_utils import (
     ChannelDimension,
     ImageInput,
     get_channel_dimension_axis,
@@ -26,8 +26,8 @@ from transformers.image_utils import (
     infer_channel_dimension_format,
     to_numpy_array,
 )
-from transformers.utils import ExplicitEnum, TensorType, is_jax_tensor, is_tf_tensor, is_torch_tensor
-from transformers.utils.import_utils import (
+from .utils import ExplicitEnum, TensorType, is_jax_tensor, is_tf_tensor, is_torch_tensor
+from .utils.import_utils import (
     is_flax_available,
     is_tf_available,
     is_torch_available,

src/transformers/modeling_tf_utils.py

@@ -33,8 +33,6 @@ import tensorflow as tf
 from huggingface_hub import Repository, list_repo_files
 from packaging.version import parse
 
-from transformers.utils.hub import convert_file_size_to_int, get_checkpoint_shard_files
-
 from . import DataCollatorWithPadding, DefaultDataCollator
 from .activations_tf import get_tf_activation
 from .configuration_utils import PretrainedConfig
@@ -63,6 +61,7 @@ from .utils import (
     requires_backends,
     working_or_temp_dir,
 )
+from .utils.hub import convert_file_size_to_int, get_checkpoint_shard_files
 
 
 if parse(tf.__version__) >= parse("2.11.0"):

src/transformers/modeling_utils.py

@@ -32,9 +32,6 @@ from packaging import version
 from torch import Tensor, nn
 from torch.nn import CrossEntropyLoss
 
-from transformers.utils.hub import convert_file_size_to_int, get_checkpoint_shard_files
-from transformers.utils.import_utils import ENV_VARS_TRUE_VALUES, is_sagemaker_mp_enabled
-
 from .activations import get_activation
 from .configuration_utils import PretrainedConfig
 from .deepspeed import deepspeed_config, is_deepspeed_zero3_enabled
@@ -73,7 +70,8 @@ from .utils import (
     logging,
     replace_return_docstrings,
 )
-from .utils.import_utils import importlib_metadata
+from .utils.hub import convert_file_size_to_int, get_checkpoint_shard_files
+from .utils.import_utils import ENV_VARS_TRUE_VALUES, importlib_metadata, is_sagemaker_mp_enabled
 from .utils.quantization_config import BitsAndBytesConfig
 from .utils.versions import require_version_core
 

src/transformers/models/albert/convert_albert_original_tf_checkpoint_to_pytorch.py

@@ -19,8 +19,8 @@ import argparse
 
 import torch
 
-from transformers import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
-from transformers.utils import logging
+from ...utils import logging
+from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
 
 
 logging.set_verbosity_info()

src/transformers/models/beit/image_processing_beit.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 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_torch_available, is_torch_tensor, is_vision_available, logging
 
 
 if is_vision_available():

src/transformers/models/bit/image_processing_bit.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,
@@ -40,8 +38,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
-from ...utils.import_utils import is_vision_available
+from ...utils import TensorType, is_vision_available, logging
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/blip/image_processing_blip.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 convert_to_rgb, 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/blip/modeling_blip_text.py

@@ -22,20 +22,19 @@ import torch.utils.checkpoint
 from torch import Tensor, device, nn
 from torch.nn import CrossEntropyLoss
 
-from transformers.activations import ACT2FN
-from transformers.modeling_outputs import (
+from ...activations import ACT2FN
+from ...modeling_outputs import (
     BaseModelOutputWithPastAndCrossAttentions,
     BaseModelOutputWithPoolingAndCrossAttentions,
     CausalLMOutputWithCrossAttentions,
 )
-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_blip import BlipTextConfig
 
 

src/transformers/models/blip_2/configuration_blip_2.py

@@ -18,9 +18,8 @@ import copy
 import os
 from typing import Union
 
-from transformers.models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
-
 from ...configuration_utils import PretrainedConfig
+from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
 from ...utils import logging
 from ..auto import CONFIG_MAPPING
 

src/transformers/models/bloom/configuration_bloom.py

@@ -18,15 +18,13 @@ from typing import TYPE_CHECKING, Any, List, Mapping, Optional
 
 from packaging import version
 
-from transformers import is_torch_available
-
 
 if TYPE_CHECKING:
-    from transformers import PreTrainedTokenizer, TensorType
+    from ... import PreTrainedTokenizer, TensorType
 
 from ...configuration_utils import PretrainedConfig
 from ...onnx import OnnxConfigWithPast, PatchingSpec
-from ...utils import logging
+from ...utils import is_torch_available, logging
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/bridgetower/image_processing_bridgetower.py

@@ -19,9 +19,6 @@ 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 PaddingMode, center_crop, normalize, pad, 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/chinese_clip/image_processing_chinese_clip.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,
@@ -40,8 +38,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
-from ...utils.import_utils import is_vision_available
+from ...utils import TensorType, is_vision_available, logging
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/clip/image_processing_clip.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,
@@ -40,8 +38,7 @@ from ...image_utils import (
     to_numpy_array,
     valid_images,
 )
-from ...utils import logging
-from ...utils.import_utils import is_vision_available
+from ...utils import TensorType, is_vision_available, logging
 
 
 logger = logging.get_logger(__name__)

src/transformers/models/conditional_detr/image_processing_conditional_detr.py

@@ -22,9 +22,9 @@ from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Un
 
 import numpy as np
 
-from transformers.feature_extraction_utils import BatchFeature
-from transformers.image_processing_utils import BaseImageProcessor, get_size_dict
-from transformers.image_transforms import (
+from ...feature_extraction_utils import BatchFeature
+from ...image_processing_utils import BaseImageProcessor, get_size_dict
+from ...image_transforms import (
     PaddingMode,
     center_to_corners_format,
     corners_to_center_format,
@@ -36,7 +36,7 @@ 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,
@@ -50,7 +50,9 @@ 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,
@@ -60,7 +62,6 @@ from transformers.utils import (
     is_torch_tensor,
     is_vision_available,
 )
-from transformers.utils.generic import ExplicitEnum, TensorType
 
 
 if is_torch_available():

src/transformers/models/conditional_detr/modeling_conditional_detr.py

@@ -49,7 +49,7 @@ if is_timm_available():
     from timm import create_model
 
 if is_vision_available():
-    from transformers.image_transforms import center_to_corners_format
+    from ...image_transforms import center_to_corners_format
 
 logger = logging.get_logger(__name__)
 

src/transformers/models/convnext/image_processing_convnext.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,
@@ -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/convnext/modeling_tf_convnext.py

@@ -20,8 +20,6 @@ from typing import Dict, Optional, Tuple, Union
 import numpy as np
 import tensorflow as tf
 
-from transformers import shape_list
-
 from ...activations_tf import get_tf_activation
 from ...modeling_tf_outputs import TFBaseModelOutput, TFBaseModelOutputWithPooling, TFSequenceClassifierOutput
 from ...modeling_tf_utils import (
@@ -32,6 +30,7 @@ from ...modeling_tf_utils import (
     keras_serializable,
     unpack_inputs,
 )
+from ...tf_utils import shape_list
 from ...utils import add_start_docstrings, add_start_docstrings_to_model_forward, logging, replace_return_docstrings
 from .configuration_convnext import ConvNextConfig
 

src/transformers/models/data2vec/modeling_tf_data2vec_vision.py

@@ -22,8 +22,6 @@ from typing import Dict, List, Optional, Tuple, Union
 import numpy as np
 import tensorflow as tf
 
-from transformers.tf_utils import shape_list, stable_softmax
-
 from ...activations_tf import get_tf_activation
 from ...modeling_tf_outputs import (
     TFBaseModelOutput,
@@ -39,6 +37,7 @@ from ...modeling_tf_utils import (
     keras_serializable,
     unpack_inputs,
 )
+from ...tf_utils import shape_list, stable_softmax
 from ...utils import (
     add_code_sample_docstrings,
     add_start_docstrings,

src/transformers/models/deformable_detr/image_processing_deformable_detr.py

@@ -22,9 +22,9 @@ from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple, Un
 
 import numpy as np
 
-from transformers.feature_extraction_utils import BatchFeature
-from transformers.image_processing_utils import BaseImageProcessor, get_size_dict
-from transformers.image_transforms import (
+from ...feature_extraction_utils import BatchFeature
+from ...image_processing_utils import BaseImageProcessor, get_size_dict
+from ...image_transforms import (
     PaddingMode,
     center_to_corners_format,
     corners_to_center_format,
@@ -36,7 +36,7 @@ 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,
@@ -50,7 +50,9 @@ 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,
@@ -60,7 +62,6 @@ from transformers.utils import (
     is_torch_tensor,
     is_vision_available,
 )
-from transformers.utils.generic import ExplicitEnum, TensorType
 
 
 if is_torch_available():