Removal of deprecated maps (#30576)
* [test_all] Remove all imports Remove remaining ARCHIVE MAPS Remove remaining PRETRAINED maps * review comments * [test_all] empty commit to trigger tests
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@ -26,7 +26,7 @@ from ...utils import (
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_import_structure = {
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"configuration_albert": ["ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "AlbertConfig", "AlbertOnnxConfig"],
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"configuration_albert": ["AlbertConfig", "AlbertOnnxConfig"],
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}
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try:
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@ -52,7 +52,6 @@ except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_albert"] = [
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"ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
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"AlbertForMaskedLM",
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"AlbertForMultipleChoice",
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"AlbertForPreTraining",
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@ -71,7 +70,6 @@ except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_tf_albert"] = [
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"TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
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"TFAlbertForMaskedLM",
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"TFAlbertForMultipleChoice",
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"TFAlbertForPreTraining",
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@ -101,7 +99,7 @@ else:
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]
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if TYPE_CHECKING:
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from .configuration_albert import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, AlbertConfig, AlbertOnnxConfig
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from .configuration_albert import AlbertConfig, AlbertOnnxConfig
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try:
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if not is_sentencepiece_available():
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@ -126,7 +124,6 @@ if TYPE_CHECKING:
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pass
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else:
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from .modeling_albert import (
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ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
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AlbertForMaskedLM,
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AlbertForMultipleChoice,
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AlbertForPreTraining,
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@ -145,7 +142,6 @@ if TYPE_CHECKING:
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pass
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else:
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from .modeling_tf_albert import (
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TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
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TFAlbertForMaskedLM,
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TFAlbertForMultipleChoice,
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TFAlbertForPreTraining,
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@ -19,7 +19,6 @@ from typing import Mapping
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from ...configuration_utils import PretrainedConfig
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from ...onnx import OnnxConfig
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from ..deprecated._archive_maps import ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
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class AlbertConfig(PretrainedConfig):
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@ -52,9 +52,6 @@ _CHECKPOINT_FOR_DOC = "albert/albert-base-v2"
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_CONFIG_FOR_DOC = "AlbertConfig"
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from ..deprecated._archive_maps import ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
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def load_tf_weights_in_albert(model, config, tf_checkpoint_path):
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"""Load tf checkpoints in a pytorch model."""
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try:
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@ -66,9 +66,6 @@ _CHECKPOINT_FOR_DOC = "albert/albert-base-v2"
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_CONFIG_FOR_DOC = "AlbertConfig"
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from ..deprecated._archive_maps import TF_ALBERT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
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class TFAlbertPreTrainingLoss:
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"""
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Loss function suitable for ALBERT pretraining, that is, the task of pretraining a language model by combining SOP +
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@ -22,7 +22,6 @@ from ...utils import (
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_import_structure = {
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"configuration_align": [
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"ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP",
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"AlignConfig",
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"AlignTextConfig",
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"AlignVisionConfig",
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@ -37,7 +36,6 @@ except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_align"] = [
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"ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST",
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"AlignModel",
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"AlignPreTrainedModel",
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"AlignTextModel",
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@ -46,7 +44,6 @@ else:
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if TYPE_CHECKING:
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from .configuration_align import (
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ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
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AlignConfig,
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AlignTextConfig,
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AlignVisionConfig,
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@ -60,7 +57,6 @@ if TYPE_CHECKING:
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pass
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else:
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from .modeling_align import (
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ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
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AlignModel,
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AlignPreTrainedModel,
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AlignTextModel,
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@ -28,9 +28,6 @@ from ...utils import logging
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logger = logging.get_logger(__name__)
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from ..deprecated._archive_maps import ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
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class AlignTextConfig(PretrainedConfig):
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r"""
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This is the configuration class to store the configuration of a [`AlignTextModel`]. It is used to instantiate a
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@ -47,9 +47,6 @@ _CHECKPOINT_FOR_DOC = "kakaobrain/align-base"
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_CONFIG_FOR_DOC = "AlignConfig"
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from ..deprecated._archive_maps import ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
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ALIGN_START_DOCSTRING = r"""
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This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the
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library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads
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@ -18,7 +18,6 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_
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_import_structure = {
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"configuration_altclip": [
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"ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
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"AltCLIPConfig",
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"AltCLIPTextConfig",
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"AltCLIPVisionConfig",
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@ -33,7 +32,6 @@ except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_altclip"] = [
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"ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
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"AltCLIPPreTrainedModel",
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"AltCLIPModel",
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"AltCLIPTextModel",
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@ -43,7 +41,6 @@ else:
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if TYPE_CHECKING:
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from .configuration_altclip import (
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ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
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AltCLIPConfig,
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AltCLIPTextConfig,
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AltCLIPVisionConfig,
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@ -57,7 +54,6 @@ if TYPE_CHECKING:
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pass
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else:
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from .modeling_altclip import (
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ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
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AltCLIPModel,
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AltCLIPPreTrainedModel,
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AltCLIPTextModel,
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@ -23,9 +23,6 @@ from ...utils import logging
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logger = logging.get_logger(__name__)
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from ..deprecated._archive_maps import ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
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class AltCLIPTextConfig(PretrainedConfig):
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r"""
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This is the configuration class to store the configuration of a [`AltCLIPTextModel`]. It is used to instantiate a
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@ -41,9 +41,6 @@ _CHECKPOINT_FOR_DOC = "BAAI/AltCLIP"
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_CONFIG_FOR_DOC = "AltCLIPConfig"
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from ..deprecated._archive_maps import ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
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ALTCLIP_START_DOCSTRING = r"""
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This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the
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library implements for all its model (such as downloading or saving, resizing the input embeddings, pruning heads
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@ -17,10 +17,7 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_avail
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_import_structure = {
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"configuration_audio_spectrogram_transformer": [
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"AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
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"ASTConfig",
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],
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"configuration_audio_spectrogram_transformer": ["ASTConfig"],
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"feature_extraction_audio_spectrogram_transformer": ["ASTFeatureExtractor"],
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}
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@ -31,7 +28,6 @@ except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_audio_spectrogram_transformer"] = [
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"AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
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"ASTForAudioClassification",
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"ASTModel",
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"ASTPreTrainedModel",
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@ -40,7 +36,6 @@ else:
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if TYPE_CHECKING:
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from .configuration_audio_spectrogram_transformer import (
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AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
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ASTConfig,
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)
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from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor
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@ -52,7 +47,6 @@ if TYPE_CHECKING:
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pass
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else:
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from .modeling_audio_spectrogram_transformer import (
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AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
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ASTForAudioClassification,
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ASTModel,
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ASTPreTrainedModel,
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@ -22,9 +22,6 @@ from ...utils import logging
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logger = logging.get_logger(__name__)
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from ..deprecated._archive_maps import AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
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class ASTConfig(PretrainedConfig):
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r"""
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This is the configuration class to store the configuration of a [`ASTModel`]. It is used to instantiate an AST
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@ -45,9 +45,6 @@ _SEQ_CLASS_EXPECTED_OUTPUT = "'Speech'"
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_SEQ_CLASS_EXPECTED_LOSS = 0.17
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from ..deprecated._archive_maps import AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
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class ASTEmbeddings(nn.Module):
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"""
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Construct the CLS token, position and patch embeddings.
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@ -25,7 +25,7 @@ from ...utils import (
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_import_structure = {
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"auto_factory": ["get_values"],
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"configuration_auto": ["ALL_PRETRAINED_CONFIG_ARCHIVE_MAP", "CONFIG_MAPPING", "MODEL_NAMES_MAPPING", "AutoConfig"],
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"configuration_auto": ["CONFIG_MAPPING", "MODEL_NAMES_MAPPING", "AutoConfig"],
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"feature_extraction_auto": ["FEATURE_EXTRACTOR_MAPPING", "AutoFeatureExtractor"],
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"image_processing_auto": ["IMAGE_PROCESSOR_MAPPING", "AutoImageProcessor"],
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"processing_auto": ["PROCESSOR_MAPPING", "AutoProcessor"],
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@ -213,7 +213,7 @@ else:
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if TYPE_CHECKING:
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from .auto_factory import get_values
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from .configuration_auto import ALL_PRETRAINED_CONFIG_ARCHIVE_MAP, CONFIG_MAPPING, MODEL_NAMES_MAPPING, AutoConfig
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from .configuration_auto import CONFIG_MAPPING, MODEL_NAMES_MAPPING, AutoConfig
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from .feature_extraction_auto import FEATURE_EXTRACTOR_MAPPING, AutoFeatureExtractor
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from .image_processing_auto import IMAGE_PROCESSOR_MAPPING, AutoImageProcessor
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from .processing_auto import PROCESSOR_MAPPING, AutoProcessor
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@ -28,9 +28,6 @@ from ...utils import CONFIG_NAME, logging
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logger = logging.get_logger(__name__)
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from ..deprecated._archive_maps import CONFIG_ARCHIVE_MAP_MAPPING_NAMES # noqa: F401, E402
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CONFIG_MAPPING_NAMES = OrderedDict(
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[
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# Add configs here
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@ -982,6 +979,3 @@ class AutoConfig:
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"match!"
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)
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CONFIG_MAPPING.register(model_type, config, exist_ok=exist_ok)
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ALL_PRETRAINED_CONFIG_ARCHIVE_MAP = _LazyLoadAllMappings(CONFIG_ARCHIVE_MAP_MAPPING_NAMES)
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@ -18,10 +18,7 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_avail
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_import_structure = {
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"configuration_autoformer": [
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"AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
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"AutoformerConfig",
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],
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"configuration_autoformer": ["AutoformerConfig"],
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}
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try:
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@ -31,7 +28,6 @@ except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_autoformer"] = [
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"AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
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"AutoformerForPrediction",
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"AutoformerModel",
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"AutoformerPreTrainedModel",
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@ -40,7 +36,6 @@ else:
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if TYPE_CHECKING:
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from .configuration_autoformer import (
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AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
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AutoformerConfig,
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)
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@ -51,7 +46,6 @@ if TYPE_CHECKING:
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pass
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else:
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from .modeling_autoformer import (
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AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
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AutoformerForPrediction,
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AutoformerModel,
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AutoformerPreTrainedModel,
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@ -23,9 +23,6 @@ from ...utils import logging
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logger = logging.get_logger(__name__)
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from ..deprecated._archive_maps import AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
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class AutoformerConfig(PretrainedConfig):
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r"""
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This is the configuration class to store the configuration of an [`AutoformerModel`]. It is used to instantiate an
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@ -167,9 +167,6 @@ class AutoformerModelOutput(ModelOutput):
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static_features: Optional[torch.FloatTensor] = None
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from ..deprecated._archive_maps import AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
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# Copied from transformers.models.time_series_transformer.modeling_time_series_transformer.TimeSeriesFeatureEmbedder with TimeSeries->Autoformer
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class AutoformerFeatureEmbedder(nn.Module):
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"""
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@ -22,7 +22,6 @@ from ...utils import (
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_import_structure = {
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"configuration_bark": [
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"BARK_PRETRAINED_CONFIG_ARCHIVE_MAP",
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"BarkCoarseConfig",
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"BarkConfig",
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"BarkFineConfig",
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@ -38,7 +37,6 @@ except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_bark"] = [
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"BARK_PRETRAINED_MODEL_ARCHIVE_LIST",
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"BarkFineModel",
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"BarkSemanticModel",
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"BarkCoarseModel",
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@ -49,7 +47,6 @@ else:
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if TYPE_CHECKING:
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from .configuration_bark import (
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BARK_PRETRAINED_CONFIG_ARCHIVE_MAP,
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BarkCoarseConfig,
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BarkConfig,
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BarkFineConfig,
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@ -64,7 +61,6 @@ if TYPE_CHECKING:
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pass
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else:
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from .modeling_bark import (
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BARK_PRETRAINED_MODEL_ARCHIVE_LIST,
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BarkCausalModel,
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BarkCoarseModel,
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BarkFineModel,
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@ -64,9 +64,6 @@ _CHECKPOINT_FOR_DOC = "suno/bark-small"
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_CONFIG_FOR_DOC = "BarkConfig"
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from ..deprecated._archive_maps import BARK_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
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# Copied from transformers.models.llama.modeling_llama._get_unpad_data
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def _get_unpad_data(attention_mask):
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seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)
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@ -24,7 +24,7 @@ from ...utils import (
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_import_structure = {
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"configuration_bart": ["BART_PRETRAINED_CONFIG_ARCHIVE_MAP", "BartConfig", "BartOnnxConfig"],
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"configuration_bart": ["BartConfig", "BartOnnxConfig"],
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"tokenization_bart": ["BartTokenizer"],
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}
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@ -43,7 +43,6 @@ except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_bart"] = [
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"BART_PRETRAINED_MODEL_ARCHIVE_LIST",
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"BartForCausalLM",
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"BartForConditionalGeneration",
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"BartForQuestionAnswering",
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@ -84,7 +83,7 @@ else:
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]
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if TYPE_CHECKING:
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from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
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from .configuration_bart import BartConfig, BartOnnxConfig
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from .tokenization_bart import BartTokenizer
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try:
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@ -102,7 +101,6 @@ if TYPE_CHECKING:
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pass
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else:
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from .modeling_bart import (
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BART_PRETRAINED_MODEL_ARCHIVE_LIST,
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BartForCausalLM,
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BartForConditionalGeneration,
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BartForQuestionAnswering,
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|
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@ -78,9 +78,6 @@ _QA_EXPECTED_LOSS = 0.59
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_QA_EXPECTED_OUTPUT = "' nice puppet'"
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from ..deprecated._archive_maps import BART_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
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# Copied from transformers.models.llama.modeling_llama._get_unpad_data
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def _get_unpad_data(attention_mask):
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seqlens_in_batch = attention_mask.sum(dim=-1, dtype=torch.int32)
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@ -23,7 +23,7 @@ from ...utils import (
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)
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_import_structure = {"configuration_beit": ["BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BeitConfig", "BeitOnnxConfig"]}
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_import_structure = {"configuration_beit": ["BeitConfig", "BeitOnnxConfig"]}
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try:
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if not is_vision_available():
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|
@ -41,7 +41,6 @@ except OptionalDependencyNotAvailable:
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pass
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else:
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_import_structure["modeling_beit"] = [
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"BEIT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BeitForImageClassification",
|
||||
"BeitForMaskedImageModeling",
|
||||
"BeitForSemanticSegmentation",
|
||||
|
@ -65,7 +64,7 @@ else:
|
|||
]
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig
|
||||
from .configuration_beit import BeitConfig, BeitOnnxConfig
|
||||
|
||||
try:
|
||||
if not is_vision_available():
|
||||
|
@ -83,7 +82,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_beit import (
|
||||
BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BeitBackbone,
|
||||
BeitForImageClassification,
|
||||
BeitForMaskedImageModeling,
|
||||
|
|
|
@ -27,9 +27,6 @@ from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feat
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BeitConfig(BackboneConfigMixin, PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`BeitModel`]. It is used to instantiate an BEiT
|
||||
|
|
|
@ -61,9 +61,6 @@ _IMAGE_CLASS_CHECKPOINT = "microsoft/beit-base-patch16-224"
|
|||
_IMAGE_CLASS_EXPECTED_OUTPUT = "tabby, tabby cat"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BEIT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
@dataclass
|
||||
class BeitModelOutputWithPooling(BaseModelOutputWithPooling):
|
||||
"""
|
||||
|
|
|
@ -26,7 +26,7 @@ from ...utils import (
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_bert": ["BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BertConfig", "BertOnnxConfig"],
|
||||
"configuration_bert": ["BertConfig", "BertOnnxConfig"],
|
||||
"tokenization_bert": ["BasicTokenizer", "BertTokenizer", "WordpieceTokenizer"],
|
||||
}
|
||||
|
||||
|
@ -45,7 +45,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_bert"] = [
|
||||
"BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BertForMaskedLM",
|
||||
"BertForMultipleChoice",
|
||||
"BertForNextSentencePrediction",
|
||||
|
@ -67,7 +66,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_tf_bert"] = [
|
||||
"TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"TFBertEmbeddings",
|
||||
"TFBertForMaskedLM",
|
||||
"TFBertForMultipleChoice",
|
||||
|
@ -109,7 +107,7 @@ else:
|
|||
]
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_bert import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, BertConfig, BertOnnxConfig
|
||||
from .configuration_bert import BertConfig, BertOnnxConfig
|
||||
from .tokenization_bert import BasicTokenizer, BertTokenizer, WordpieceTokenizer
|
||||
|
||||
try:
|
||||
|
@ -127,7 +125,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_bert import (
|
||||
BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BertForMaskedLM,
|
||||
BertForMultipleChoice,
|
||||
BertForNextSentencePrediction,
|
||||
|
@ -149,7 +146,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_tf_bert import (
|
||||
TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
TFBertEmbeddings,
|
||||
TFBertForMaskedLM,
|
||||
TFBertForMultipleChoice,
|
||||
|
|
|
@ -25,9 +25,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BertConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`BertModel`] or a [`TFBertModel`]. It is used to
|
||||
|
|
|
@ -82,9 +82,6 @@ _SEQ_CLASS_EXPECTED_OUTPUT = "'LABEL_1'"
|
|||
_SEQ_CLASS_EXPECTED_LOSS = 0.01
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BERT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
def load_tf_weights_in_bert(model, config, tf_checkpoint_path):
|
||||
"""Load tf checkpoints in a pytorch model."""
|
||||
try:
|
||||
|
|
|
@ -90,9 +90,6 @@ _SEQ_CLASS_EXPECTED_OUTPUT = "'LABEL_1'"
|
|||
_SEQ_CLASS_EXPECTED_LOSS = 0.01
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
class TFBertPreTrainingLoss:
|
||||
"""
|
||||
Loss function suitable for BERT-like pretraining, that is, the task of pretraining a language model by combining
|
||||
|
|
|
@ -25,7 +25,7 @@ from ...utils import (
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_big_bird": ["BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP", "BigBirdConfig", "BigBirdOnnxConfig"],
|
||||
"configuration_big_bird": ["BigBirdConfig", "BigBirdOnnxConfig"],
|
||||
}
|
||||
|
||||
try:
|
||||
|
@ -51,7 +51,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_big_bird"] = [
|
||||
"BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BigBirdForCausalLM",
|
||||
"BigBirdForMaskedLM",
|
||||
"BigBirdForMultipleChoice",
|
||||
|
@ -84,7 +83,7 @@ else:
|
|||
]
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_big_bird import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP, BigBirdConfig, BigBirdOnnxConfig
|
||||
from .configuration_big_bird import BigBirdConfig, BigBirdOnnxConfig
|
||||
|
||||
try:
|
||||
if not is_sentencepiece_available():
|
||||
|
@ -109,7 +108,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_big_bird import (
|
||||
BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BigBirdForCausalLM,
|
||||
BigBirdForMaskedLM,
|
||||
BigBirdForMultipleChoice,
|
||||
|
|
|
@ -24,9 +24,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BIG_BIRD_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BigBirdConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`BigBirdModel`]. It is used to instantiate an
|
||||
|
|
|
@ -55,9 +55,6 @@ _CHECKPOINT_FOR_DOC = "google/bigbird-roberta-base"
|
|||
_CONFIG_FOR_DOC = "BigBirdConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BIG_BIRD_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
_TRIVIA_QA_MAPPING = {
|
||||
"big_bird_attention": "attention/self",
|
||||
"output_layer_norm": "output/LayerNorm",
|
||||
|
|
|
@ -18,7 +18,6 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_avail
|
|||
|
||||
_import_structure = {
|
||||
"configuration_bigbird_pegasus": [
|
||||
"BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"BigBirdPegasusConfig",
|
||||
"BigBirdPegasusOnnxConfig",
|
||||
],
|
||||
|
@ -31,7 +30,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_bigbird_pegasus"] = [
|
||||
"BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BigBirdPegasusForCausalLM",
|
||||
"BigBirdPegasusForConditionalGeneration",
|
||||
"BigBirdPegasusForQuestionAnswering",
|
||||
|
@ -43,7 +41,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_bigbird_pegasus import (
|
||||
BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
BigBirdPegasusConfig,
|
||||
BigBirdPegasusOnnxConfig,
|
||||
)
|
||||
|
@ -55,7 +52,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_bigbird_pegasus import (
|
||||
BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BigBirdPegasusForCausalLM,
|
||||
BigBirdPegasusForConditionalGeneration,
|
||||
BigBirdPegasusForQuestionAnswering,
|
||||
|
|
|
@ -27,9 +27,6 @@ from ...utils import TensorType, is_torch_available, logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BigBirdPegasusConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`BigBirdPegasusModel`]. It is used to instantiate
|
||||
|
|
|
@ -54,9 +54,6 @@ _CONFIG_FOR_DOC = "BigBirdPegasusConfig"
|
|||
_EXPECTED_OUTPUT_SHAPE = [1, 7, 1024]
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
def shift_tokens_right(input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int):
|
||||
"""
|
||||
Shift input ids one token to the right.
|
||||
|
|
|
@ -17,7 +17,7 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
|
||||
"configuration_biogpt": ["BioGptConfig"],
|
||||
"tokenization_biogpt": ["BioGptTokenizer"],
|
||||
}
|
||||
|
||||
|
@ -28,7 +28,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_biogpt"] = [
|
||||
"BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BioGptForCausalLM",
|
||||
"BioGptForTokenClassification",
|
||||
"BioGptForSequenceClassification",
|
||||
|
@ -38,7 +37,7 @@ else:
|
|||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
|
||||
from .configuration_biogpt import BioGptConfig
|
||||
from .tokenization_biogpt import BioGptTokenizer
|
||||
|
||||
try:
|
||||
|
@ -48,7 +47,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_biogpt import (
|
||||
BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BioGptForCausalLM,
|
||||
BioGptForSequenceClassification,
|
||||
BioGptForTokenClassification,
|
||||
|
|
|
@ -21,9 +21,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BioGptConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`BioGptModel`]. It is used to instantiate an
|
||||
|
|
|
@ -47,9 +47,6 @@ _CHECKPOINT_FOR_DOC = "microsoft/biogpt"
|
|||
_CONFIG_FOR_DOC = "BioGptConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Copied from transformers.models.opt.modeling_opt.OPTLearnedPositionalEmbedding with OPT->BioGpt
|
||||
class BioGptLearnedPositionalEmbedding(nn.Embedding):
|
||||
"""
|
||||
|
|
|
@ -16,7 +16,7 @@ from typing import TYPE_CHECKING
|
|||
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
|
||||
|
||||
|
||||
_import_structure = {"configuration_bit": ["BIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BitConfig", "BitOnnxConfig"]}
|
||||
_import_structure = {"configuration_bit": ["BitConfig", "BitOnnxConfig"]}
|
||||
|
||||
try:
|
||||
if not is_torch_available():
|
||||
|
@ -25,7 +25,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_bit"] = [
|
||||
"BIT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BitForImageClassification",
|
||||
"BitModel",
|
||||
"BitPreTrainedModel",
|
||||
|
@ -43,7 +42,7 @@ else:
|
|||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_bit import BIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BitConfig, BitOnnxConfig
|
||||
from .configuration_bit import BitConfig, BitOnnxConfig
|
||||
|
||||
try:
|
||||
if not is_torch_available():
|
||||
|
@ -52,7 +51,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_bit import (
|
||||
BIT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BitBackbone,
|
||||
BitForImageClassification,
|
||||
BitModel,
|
||||
|
|
|
@ -22,9 +22,6 @@ from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feat
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BIT_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BitConfig(BackboneConfigMixin, PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`BitModel`]. It is used to instantiate an BiT
|
||||
|
|
|
@ -57,9 +57,6 @@ _IMAGE_CLASS_CHECKPOINT = "google/bit-50"
|
|||
_IMAGE_CLASS_EXPECTED_OUTPUT = "tiger cat"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BIT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
def get_padding_value(padding=None, kernel_size=7, stride=1, dilation=1) -> Tuple[Tuple, bool]:
|
||||
r"""
|
||||
Utility function to get the tuple padding value given the kernel_size and padding.
|
||||
|
|
|
@ -26,7 +26,6 @@ from ...utils import (
|
|||
|
||||
_import_structure = {
|
||||
"configuration_blenderbot": [
|
||||
"BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"BlenderbotConfig",
|
||||
"BlenderbotOnnxConfig",
|
||||
],
|
||||
|
@ -48,7 +47,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_blenderbot"] = [
|
||||
"BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BlenderbotForCausalLM",
|
||||
"BlenderbotForConditionalGeneration",
|
||||
"BlenderbotModel",
|
||||
|
@ -84,7 +82,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_blenderbot import (
|
||||
BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
BlenderbotConfig,
|
||||
BlenderbotOnnxConfig,
|
||||
)
|
||||
|
@ -105,7 +102,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_blenderbot import (
|
||||
BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BlenderbotForCausalLM,
|
||||
BlenderbotForConditionalGeneration,
|
||||
BlenderbotModel,
|
||||
|
|
|
@ -28,9 +28,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BlenderbotConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`BlenderbotModel`]. It is used to instantiate an
|
||||
|
|
|
@ -53,9 +53,6 @@ _CONFIG_FOR_DOC = "BlenderbotConfig"
|
|||
_CHECKPOINT_FOR_DOC = "facebook/blenderbot-400M-distill"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Copied from transformers.models.bart.modeling_bart.shift_tokens_right
|
||||
def shift_tokens_right(input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int):
|
||||
"""
|
||||
|
|
|
@ -25,7 +25,6 @@ from ...utils import (
|
|||
|
||||
_import_structure = {
|
||||
"configuration_blenderbot_small": [
|
||||
"BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"BlenderbotSmallConfig",
|
||||
"BlenderbotSmallOnnxConfig",
|
||||
],
|
||||
|
@ -47,7 +46,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_blenderbot_small"] = [
|
||||
"BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BlenderbotSmallForCausalLM",
|
||||
"BlenderbotSmallForConditionalGeneration",
|
||||
"BlenderbotSmallModel",
|
||||
|
@ -80,7 +78,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_blenderbot_small import (
|
||||
BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
BlenderbotSmallConfig,
|
||||
BlenderbotSmallOnnxConfig,
|
||||
)
|
||||
|
@ -101,7 +98,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_blenderbot_small import (
|
||||
BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BlenderbotSmallForCausalLM,
|
||||
BlenderbotSmallForConditionalGeneration,
|
||||
BlenderbotSmallModel,
|
||||
|
|
|
@ -27,8 +27,6 @@ from ...utils import logging
|
|||
|
||||
logger = logging.get_logger(__name__)
|
||||
|
||||
from ..deprecated._archive_maps import BLENDERBOT_SMALL_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BlenderbotSmallConfig(PretrainedConfig):
|
||||
r"""
|
||||
|
|
|
@ -49,9 +49,6 @@ logger = logging.get_logger(__name__)
|
|||
_CONFIG_FOR_DOC = "BlenderbotSmallConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Copied from transformers.models.bart.modeling_bart.shift_tokens_right
|
||||
def shift_tokens_right(input_ids: torch.Tensor, pad_token_id: int, decoder_start_token_id: int):
|
||||
"""
|
||||
|
|
|
@ -24,7 +24,6 @@ from ...utils import (
|
|||
|
||||
_import_structure = {
|
||||
"configuration_blip": [
|
||||
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"BlipConfig",
|
||||
"BlipTextConfig",
|
||||
"BlipVisionConfig",
|
||||
|
@ -48,7 +47,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_blip"] = [
|
||||
"BLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BlipModel",
|
||||
"BlipPreTrainedModel",
|
||||
"BlipForConditionalGeneration",
|
||||
|
@ -65,7 +63,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_tf_blip"] = [
|
||||
"TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"TFBlipModel",
|
||||
"TFBlipPreTrainedModel",
|
||||
"TFBlipForConditionalGeneration",
|
||||
|
@ -76,7 +73,7 @@ else:
|
|||
]
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_blip import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP, BlipConfig, BlipTextConfig, BlipVisionConfig
|
||||
from .configuration_blip import BlipConfig, BlipTextConfig, BlipVisionConfig
|
||||
from .processing_blip import BlipProcessor
|
||||
|
||||
try:
|
||||
|
@ -94,7 +91,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_blip import (
|
||||
BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BlipForConditionalGeneration,
|
||||
BlipForImageTextRetrieval,
|
||||
BlipForQuestionAnswering,
|
||||
|
@ -111,7 +107,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_tf_blip import (
|
||||
TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
TFBlipForConditionalGeneration,
|
||||
TFBlipForImageTextRetrieval,
|
||||
TFBlipForQuestionAnswering,
|
||||
|
|
|
@ -24,9 +24,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BlipTextConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`BlipTextModel`]. It is used to instantiate a BLIP
|
||||
|
|
|
@ -42,9 +42,6 @@ logger = logging.get_logger(__name__)
|
|||
_CHECKPOINT_FOR_DOC = "Salesforce/blip-vqa-base"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BLIP_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Copied from transformers.models.clip.modeling_clip.contrastive_loss
|
||||
def contrastive_loss(logits: torch.Tensor) -> torch.Tensor:
|
||||
return nn.functional.cross_entropy(logits, torch.arange(len(logits), device=logits.device))
|
||||
|
|
|
@ -49,9 +49,6 @@ logger = logging.get_logger(__name__)
|
|||
_CHECKPOINT_FOR_DOC = "Salesforce/blip-vqa-base"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import TF_BLIP_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Copied from transformers.models.clip.modeling_tf_clip.contrastive_loss
|
||||
def contrastive_loss(logits: tf.Tensor) -> tf.Tensor:
|
||||
return tf.math.reduce_mean(
|
||||
|
|
|
@ -18,7 +18,6 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_avail
|
|||
|
||||
_import_structure = {
|
||||
"configuration_blip_2": [
|
||||
"BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"Blip2Config",
|
||||
"Blip2QFormerConfig",
|
||||
"Blip2VisionConfig",
|
||||
|
@ -33,7 +32,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_blip_2"] = [
|
||||
"BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"Blip2Model",
|
||||
"Blip2QFormerModel",
|
||||
"Blip2PreTrainedModel",
|
||||
|
@ -43,7 +41,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_blip_2 import (
|
||||
BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
Blip2Config,
|
||||
Blip2QFormerConfig,
|
||||
Blip2VisionConfig,
|
||||
|
@ -57,7 +54,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_blip_2 import (
|
||||
BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
Blip2ForConditionalGeneration,
|
||||
Blip2Model,
|
||||
Blip2PreTrainedModel,
|
||||
|
|
|
@ -26,9 +26,6 @@ from ..auto import CONFIG_MAPPING
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class Blip2VisionConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`Blip2VisionModel`]. It is used to instantiate a
|
||||
|
|
|
@ -48,9 +48,6 @@ logger = logging.get_logger(__name__)
|
|||
_CHECKPOINT_FOR_DOC = "Salesforce/blip2-opt-2.7b"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
@dataclass
|
||||
class Blip2ForConditionalGenerationModelOutput(ModelOutput):
|
||||
"""
|
||||
|
|
|
@ -24,7 +24,7 @@ from ...utils import (
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
|
||||
"configuration_bloom": ["BloomConfig", "BloomOnnxConfig"],
|
||||
}
|
||||
try:
|
||||
if not is_tokenizers_available():
|
||||
|
@ -41,7 +41,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_bloom"] = [
|
||||
"BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BloomForCausalLM",
|
||||
"BloomModel",
|
||||
"BloomPreTrainedModel",
|
||||
|
@ -64,7 +63,7 @@ else:
|
|||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig
|
||||
from .configuration_bloom import BloomConfig, BloomOnnxConfig
|
||||
|
||||
try:
|
||||
if not is_tokenizers_available():
|
||||
|
@ -81,7 +80,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_bloom import (
|
||||
BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BloomForCausalLM,
|
||||
BloomForQuestionAnswering,
|
||||
BloomForSequenceClassification,
|
||||
|
|
|
@ -30,9 +30,6 @@ from ...utils import is_torch_available, logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BloomConfig(PretrainedConfig):
|
||||
"""
|
||||
This is the configuration class to store the configuration of a [`BloomModel`]. It is used to instantiate a Bloom
|
||||
|
|
|
@ -44,9 +44,6 @@ _CHECKPOINT_FOR_DOC = "bigscience/bloom-560m"
|
|||
_CONFIG_FOR_DOC = "BloomConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
def build_alibi_tensor(attention_mask: torch.Tensor, num_heads: int, dtype: torch.dtype) -> torch.Tensor:
|
||||
"""
|
||||
Link to paper: https://arxiv.org/abs/2108.12409 Alibi tensor is not causal as the original paper mentions, it
|
||||
|
|
|
@ -18,7 +18,6 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_avail
|
|||
|
||||
_import_structure = {
|
||||
"configuration_bridgetower": [
|
||||
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"BridgeTowerConfig",
|
||||
"BridgeTowerTextConfig",
|
||||
"BridgeTowerVisionConfig",
|
||||
|
@ -41,7 +40,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_bridgetower"] = [
|
||||
"BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BridgeTowerForContrastiveLearning",
|
||||
"BridgeTowerForImageAndTextRetrieval",
|
||||
"BridgeTowerForMaskedLM",
|
||||
|
@ -52,7 +50,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_bridgetower import (
|
||||
BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
BridgeTowerConfig,
|
||||
BridgeTowerTextConfig,
|
||||
BridgeTowerVisionConfig,
|
||||
|
@ -74,7 +71,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_bridgetower import (
|
||||
BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BridgeTowerForContrastiveLearning,
|
||||
BridgeTowerForImageAndTextRetrieval,
|
||||
BridgeTowerForMaskedLM,
|
||||
|
|
|
@ -24,9 +24,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BridgeTowerVisionConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the vision configuration of a [`BridgeTowerModel`]. Instantiating a
|
||||
|
|
|
@ -45,9 +45,6 @@ _CHECKPOINT_FOR_DOC = "BridgeTower/bridgetower-base"
|
|||
_TOKENIZER_FOR_DOC = "RobertaTokenizer"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BRIDGETOWER_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
BRIDGETOWER_START_DOCSTRING = r"""
|
||||
This model is a PyTorch `torch.nn.Module <https://pytorch.org/docs/stable/nn.html#torch.nn.Module>`_ subclass. Use
|
||||
it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage and
|
||||
|
|
|
@ -17,7 +17,7 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_bros": ["BROS_PRETRAINED_CONFIG_ARCHIVE_MAP", "BrosConfig"],
|
||||
"configuration_bros": ["BrosConfig"],
|
||||
}
|
||||
|
||||
try:
|
||||
|
@ -35,7 +35,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_bros"] = [
|
||||
"BROS_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"BrosPreTrainedModel",
|
||||
"BrosModel",
|
||||
"BrosForTokenClassification",
|
||||
|
@ -45,7 +44,7 @@ else:
|
|||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_bros import BROS_PRETRAINED_CONFIG_ARCHIVE_MAP, BrosConfig
|
||||
from .configuration_bros import BrosConfig
|
||||
|
||||
try:
|
||||
if not is_tokenizers_available():
|
||||
|
@ -62,7 +61,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_bros import (
|
||||
BROS_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
BrosForTokenClassification,
|
||||
BrosModel,
|
||||
BrosPreTrainedModel,
|
||||
|
|
|
@ -21,9 +21,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BROS_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class BrosConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`BrosModel`] or a [`TFBrosModel`]. It is used to
|
||||
|
|
|
@ -48,9 +48,6 @@ _CHECKPOINT_FOR_DOC = "jinho8345/bros-base-uncased"
|
|||
_CONFIG_FOR_DOC = "BrosConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import BROS_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
BROS_START_DOCSTRING = r"""
|
||||
This model is also a PyTorch [torch.nn.Module](https://pytorch.org/docs/stable/nn.html#torch.nn.Module) subclass.
|
||||
Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage
|
||||
|
|
|
@ -25,7 +25,7 @@ from ...utils import (
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_camembert": ["CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "CamembertConfig", "CamembertOnnxConfig"],
|
||||
"configuration_camembert": ["CamembertConfig", "CamembertOnnxConfig"],
|
||||
}
|
||||
|
||||
try:
|
||||
|
@ -51,7 +51,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_camembert"] = [
|
||||
"CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"CamembertForCausalLM",
|
||||
"CamembertForMaskedLM",
|
||||
"CamembertForMultipleChoice",
|
||||
|
@ -69,7 +68,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_tf_camembert"] = [
|
||||
"TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"TFCamembertForCausalLM",
|
||||
"TFCamembertForMaskedLM",
|
||||
"TFCamembertForMultipleChoice",
|
||||
|
@ -82,7 +80,7 @@ else:
|
|||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_camembert import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, CamembertConfig, CamembertOnnxConfig
|
||||
from .configuration_camembert import CamembertConfig, CamembertOnnxConfig
|
||||
|
||||
try:
|
||||
if not is_sentencepiece_available():
|
||||
|
@ -107,7 +105,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_camembert import (
|
||||
CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
CamembertForCausalLM,
|
||||
CamembertForMaskedLM,
|
||||
CamembertForMultipleChoice,
|
||||
|
@ -125,7 +122,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_tf_camembert import (
|
||||
TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
TFCamembertForCausalLM,
|
||||
TFCamembertForMaskedLM,
|
||||
TFCamembertForMultipleChoice,
|
||||
|
|
|
@ -26,9 +26,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class CamembertConfig(PretrainedConfig):
|
||||
"""
|
||||
This is the configuration class to store the configuration of a [`CamembertModel`] or a [`TFCamembertModel`]. It is
|
||||
|
|
|
@ -52,9 +52,6 @@ _CHECKPOINT_FOR_DOC = "almanach/camembert-base"
|
|||
_CONFIG_FOR_DOC = "CamembertConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
CAMEMBERT_START_DOCSTRING = r"""
|
||||
|
||||
This model inherits from [`PreTrainedModel`]. Check the superclass documentation for the generic methods the
|
||||
|
|
|
@ -66,9 +66,6 @@ _CHECKPOINT_FOR_DOC = "almanach/camembert-base"
|
|||
_CONFIG_FOR_DOC = "CamembertConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import TF_CAMEMBERT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
CAMEMBERT_START_DOCSTRING = r"""
|
||||
|
||||
This model inherits from [`TFPreTrainedModel`]. Check the superclass documentation for the generic methods the
|
||||
|
|
|
@ -17,7 +17,7 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"],
|
||||
"configuration_canine": ["CanineConfig"],
|
||||
"tokenization_canine": ["CanineTokenizer"],
|
||||
}
|
||||
|
||||
|
@ -28,7 +28,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_canine"] = [
|
||||
"CANINE_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"CanineForMultipleChoice",
|
||||
"CanineForQuestionAnswering",
|
||||
"CanineForSequenceClassification",
|
||||
|
@ -41,7 +40,7 @@ else:
|
|||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
|
||||
from .configuration_canine import CanineConfig
|
||||
from .tokenization_canine import CanineTokenizer
|
||||
|
||||
try:
|
||||
|
@ -51,7 +50,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_canine import (
|
||||
CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
CanineForMultipleChoice,
|
||||
CanineForQuestionAnswering,
|
||||
CanineForSequenceClassification,
|
||||
|
|
|
@ -21,9 +21,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class CanineConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`CanineModel`]. It is used to instantiate an
|
||||
|
|
|
@ -53,9 +53,6 @@ _CHECKPOINT_FOR_DOC = "google/canine-s"
|
|||
_CONFIG_FOR_DOC = "CanineConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CANINE_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Support up to 16 hash functions.
|
||||
_PRIMES = [31, 43, 59, 61, 73, 97, 103, 113, 137, 149, 157, 173, 181, 193, 211, 223]
|
||||
|
||||
|
|
|
@ -18,7 +18,6 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_avail
|
|||
|
||||
_import_structure = {
|
||||
"configuration_chinese_clip": [
|
||||
"CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"ChineseCLIPConfig",
|
||||
"ChineseCLIPOnnxConfig",
|
||||
"ChineseCLIPTextConfig",
|
||||
|
@ -43,7 +42,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_chinese_clip"] = [
|
||||
"CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"ChineseCLIPModel",
|
||||
"ChineseCLIPPreTrainedModel",
|
||||
"ChineseCLIPTextModel",
|
||||
|
@ -52,7 +50,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_chinese_clip import (
|
||||
CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
ChineseCLIPConfig,
|
||||
ChineseCLIPOnnxConfig,
|
||||
ChineseCLIPTextConfig,
|
||||
|
@ -75,7 +72,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_chinese_clip import (
|
||||
CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
ChineseCLIPModel,
|
||||
ChineseCLIPPreTrainedModel,
|
||||
ChineseCLIPTextModel,
|
||||
|
|
|
@ -31,9 +31,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class ChineseCLIPTextConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`ChineseCLIPModel`]. It is used to instantiate a
|
||||
|
|
|
@ -49,9 +49,6 @@ _CHECKPOINT_FOR_DOC = "OFA-Sys/chinese-clip-vit-base-patch16"
|
|||
_CONFIG_FOR_DOC = "ChineseCLIPConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CHINESE_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# https://sachinruk.github.io/blog/pytorch/pytorch%20lightning/loss%20function/gpu/2021/03/07/CLIP.html
|
||||
# Copied from transformers.models.clip.modeling_clip.contrastive_loss
|
||||
def contrastive_loss(logits: torch.Tensor) -> torch.Tensor:
|
||||
|
|
|
@ -18,7 +18,6 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_avail
|
|||
|
||||
_import_structure = {
|
||||
"configuration_clap": [
|
||||
"CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"ClapAudioConfig",
|
||||
"ClapConfig",
|
||||
"ClapTextConfig",
|
||||
|
@ -33,7 +32,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_clap"] = [
|
||||
"CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"ClapModel",
|
||||
"ClapPreTrainedModel",
|
||||
"ClapTextModel",
|
||||
|
@ -45,7 +43,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_clap import (
|
||||
CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
ClapAudioConfig,
|
||||
ClapConfig,
|
||||
ClapTextConfig,
|
||||
|
@ -60,7 +57,6 @@ if TYPE_CHECKING:
|
|||
else:
|
||||
from .feature_extraction_clap import ClapFeatureExtractor
|
||||
from .modeling_clap import (
|
||||
CLAP_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
ClapAudioModel,
|
||||
ClapAudioModelWithProjection,
|
||||
ClapModel,
|
||||
|
|
|
@ -45,9 +45,6 @@ logger = logging.get_logger(__name__)
|
|||
_CHECKPOINT_FOR_DOC = "laion/clap-htsat-fused"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CLAP_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Adapted from: https://github.com/LAION-AI/CLAP/blob/6ad05a971ba0622f6acee8c41993e0d02bbed639/src/open_clip/utils.py#L191
|
||||
def interpolate(hidden_states, ratio):
|
||||
"""
|
||||
|
|
|
@ -26,7 +26,6 @@ from ...utils import (
|
|||
|
||||
_import_structure = {
|
||||
"configuration_clip": [
|
||||
"CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"CLIPConfig",
|
||||
"CLIPOnnxConfig",
|
||||
"CLIPTextConfig",
|
||||
|
@ -60,7 +59,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_clip"] = [
|
||||
"CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"CLIPModel",
|
||||
"CLIPPreTrainedModel",
|
||||
"CLIPTextModel",
|
||||
|
@ -77,7 +75,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_tf_clip"] = [
|
||||
"TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"TFCLIPModel",
|
||||
"TFCLIPPreTrainedModel",
|
||||
"TFCLIPTextModel",
|
||||
|
@ -103,7 +100,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_clip import (
|
||||
CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
CLIPConfig,
|
||||
CLIPOnnxConfig,
|
||||
CLIPTextConfig,
|
||||
|
@ -136,7 +132,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_clip import (
|
||||
CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
CLIPForImageClassification,
|
||||
CLIPModel,
|
||||
CLIPPreTrainedModel,
|
||||
|
@ -153,7 +148,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_tf_clip import (
|
||||
TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
TFCLIPModel,
|
||||
TFCLIPPreTrainedModel,
|
||||
TFCLIPTextModel,
|
||||
|
|
|
@ -31,9 +31,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class CLIPTextConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`CLIPTextModel`]. It is used to instantiate a CLIP
|
||||
|
|
|
@ -49,9 +49,6 @@ _IMAGE_CLASS_CHECKPOINT = "openai/clip-vit-base-patch32"
|
|||
_IMAGE_CLASS_EXPECTED_OUTPUT = "LABEL_0"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CLIP_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# contrastive loss function, adapted from
|
||||
# https://sachinruk.github.io/blog/2021-03-07-clip.html
|
||||
def contrastive_loss(logits: torch.Tensor) -> torch.Tensor:
|
||||
|
|
|
@ -52,9 +52,6 @@ logger = logging.get_logger(__name__)
|
|||
_CHECKPOINT_FOR_DOC = "openai/clip-vit-base-patch32"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import TF_CLIP_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
LARGE_NEGATIVE = -1e8
|
||||
|
||||
|
||||
|
|
|
@ -18,7 +18,6 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_avail
|
|||
|
||||
_import_structure = {
|
||||
"configuration_clipseg": [
|
||||
"CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"CLIPSegConfig",
|
||||
"CLIPSegTextConfig",
|
||||
"CLIPSegVisionConfig",
|
||||
|
@ -33,7 +32,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_clipseg"] = [
|
||||
"CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"CLIPSegModel",
|
||||
"CLIPSegPreTrainedModel",
|
||||
"CLIPSegTextModel",
|
||||
|
@ -43,7 +41,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_clipseg import (
|
||||
CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
CLIPSegConfig,
|
||||
CLIPSegTextConfig,
|
||||
CLIPSegVisionConfig,
|
||||
|
@ -57,7 +54,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_clipseg import (
|
||||
CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
CLIPSegForImageSegmentation,
|
||||
CLIPSegModel,
|
||||
CLIPSegPreTrainedModel,
|
||||
|
|
|
@ -24,9 +24,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class CLIPSegTextConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`CLIPSegModel`]. It is used to instantiate an
|
||||
|
|
|
@ -43,9 +43,6 @@ logger = logging.get_logger(__name__)
|
|||
_CHECKPOINT_FOR_DOC = "CIDAS/clipseg-rd64-refined"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# contrastive loss function, adapted from
|
||||
# https://sachinruk.github.io/blog/pytorch/pytorch%20lightning/loss%20function/gpu/2021/03/07/CLIP.html
|
||||
def contrastive_loss(logits: torch.Tensor) -> torch.Tensor:
|
||||
|
|
|
@ -22,7 +22,6 @@ from ...utils import (
|
|||
|
||||
_import_structure = {
|
||||
"configuration_clvp": [
|
||||
"CLVP_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"ClvpConfig",
|
||||
"ClvpDecoderConfig",
|
||||
"ClvpEncoderConfig",
|
||||
|
@ -40,7 +39,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_clvp"] = [
|
||||
"CLVP_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"ClvpModelForConditionalGeneration",
|
||||
"ClvpForCausalLM",
|
||||
"ClvpModel",
|
||||
|
@ -52,7 +50,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_clvp import (
|
||||
CLVP_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
ClvpConfig,
|
||||
ClvpDecoderConfig,
|
||||
ClvpEncoderConfig,
|
||||
|
@ -68,7 +65,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_clvp import (
|
||||
CLVP_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
ClvpDecoder,
|
||||
ClvpEncoder,
|
||||
ClvpForCausalLM,
|
||||
|
|
|
@ -29,9 +29,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CLVP_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class ClvpEncoderConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`ClvpEncoder`]. It is used to instantiate a CLVP
|
||||
|
|
|
@ -56,9 +56,6 @@ logger = logging.get_logger(__name__)
|
|||
_CHECKPOINT_FOR_DOC = "susnato/clvp_dev"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CLVP_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Copied from transformers.models.clip.modeling_clip.contrastive_loss
|
||||
def contrastive_loss(logits: torch.Tensor) -> torch.Tensor:
|
||||
return nn.functional.cross_entropy(logits, torch.arange(len(logits), device=logits.device))
|
||||
|
|
|
@ -17,7 +17,7 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_codegen": ["CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP", "CodeGenConfig", "CodeGenOnnxConfig"],
|
||||
"configuration_codegen": ["CodeGenConfig", "CodeGenOnnxConfig"],
|
||||
"tokenization_codegen": ["CodeGenTokenizer"],
|
||||
}
|
||||
|
||||
|
@ -36,14 +36,13 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_codegen"] = [
|
||||
"CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"CodeGenForCausalLM",
|
||||
"CodeGenModel",
|
||||
"CodeGenPreTrainedModel",
|
||||
]
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_codegen import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP, CodeGenConfig, CodeGenOnnxConfig
|
||||
from .configuration_codegen import CodeGenConfig, CodeGenOnnxConfig
|
||||
from .tokenization_codegen import CodeGenTokenizer
|
||||
|
||||
try:
|
||||
|
@ -61,7 +60,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_codegen import (
|
||||
CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
CodeGenForCausalLM,
|
||||
CodeGenModel,
|
||||
CodeGenPreTrainedModel,
|
||||
|
|
|
@ -25,9 +25,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CODEGEN_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class CodeGenConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`CodeGenModel`]. It is used to instantiate a
|
||||
|
|
|
@ -34,9 +34,6 @@ _CHECKPOINT_FOR_DOC = "Salesforce/codegen-2B-mono"
|
|||
_CONFIG_FOR_DOC = "CodeGenConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CODEGEN_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Copied from transformers.models.gptj.modeling_gptj.create_sinusoidal_positions
|
||||
def create_sinusoidal_positions(num_pos: int, dim: int) -> torch.Tensor:
|
||||
inv_freq = 1.0 / (10000 ** (torch.arange(0, dim, 2, dtype=torch.int64) / dim))
|
||||
|
|
|
@ -23,7 +23,7 @@ from ...utils import (
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_cohere": ["COHERE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CohereConfig"],
|
||||
"configuration_cohere": ["CohereConfig"],
|
||||
}
|
||||
|
||||
|
||||
|
@ -49,7 +49,7 @@ else:
|
|||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_cohere import COHERE_PRETRAINED_CONFIG_ARCHIVE_MAP, CohereConfig
|
||||
from .configuration_cohere import CohereConfig
|
||||
|
||||
try:
|
||||
if not is_tokenizers_available():
|
||||
|
|
|
@ -25,8 +25,6 @@ from ...utils import logging
|
|||
|
||||
logger = logging.get_logger(__name__)
|
||||
|
||||
COHERE_PRETRAINED_CONFIG_ARCHIVE_MAP = {}
|
||||
|
||||
|
||||
class CohereConfig(PretrainedConfig):
|
||||
r"""
|
||||
|
|
|
@ -19,7 +19,6 @@ from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_avail
|
|||
|
||||
_import_structure = {
|
||||
"configuration_conditional_detr": [
|
||||
"CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP",
|
||||
"ConditionalDetrConfig",
|
||||
"ConditionalDetrOnnxConfig",
|
||||
]
|
||||
|
@ -41,7 +40,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_conditional_detr"] = [
|
||||
"CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"ConditionalDetrForObjectDetection",
|
||||
"ConditionalDetrForSegmentation",
|
||||
"ConditionalDetrModel",
|
||||
|
@ -51,7 +49,6 @@ else:
|
|||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_conditional_detr import (
|
||||
CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP,
|
||||
ConditionalDetrConfig,
|
||||
ConditionalDetrOnnxConfig,
|
||||
)
|
||||
|
@ -72,7 +69,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_conditional_detr import (
|
||||
CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
ConditionalDetrForObjectDetection,
|
||||
ConditionalDetrForSegmentation,
|
||||
ConditionalDetrModel,
|
||||
|
|
|
@ -27,9 +27,6 @@ from ..auto import CONFIG_MAPPING
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class ConditionalDetrConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`ConditionalDetrModel`]. It is used to instantiate
|
||||
|
|
|
@ -61,9 +61,6 @@ _CONFIG_FOR_DOC = "ConditionalDetrConfig"
|
|||
_CHECKPOINT_FOR_DOC = "microsoft/conditional-detr-resnet-50"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CONDITIONAL_DETR_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
@dataclass
|
||||
class ConditionalDetrDecoderOutput(BaseModelOutputWithCrossAttentions):
|
||||
"""
|
||||
|
|
|
@ -23,7 +23,7 @@ from ...utils import (
|
|||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_convbert": ["CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvBertConfig", "ConvBertOnnxConfig"],
|
||||
"configuration_convbert": ["ConvBertConfig", "ConvBertOnnxConfig"],
|
||||
"tokenization_convbert": ["ConvBertTokenizer"],
|
||||
}
|
||||
|
||||
|
@ -42,7 +42,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_convbert"] = [
|
||||
"CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"ConvBertForMaskedLM",
|
||||
"ConvBertForMultipleChoice",
|
||||
"ConvBertForQuestionAnswering",
|
||||
|
@ -62,7 +61,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_tf_convbert"] = [
|
||||
"TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"TFConvBertForMaskedLM",
|
||||
"TFConvBertForMultipleChoice",
|
||||
"TFConvBertForQuestionAnswering",
|
||||
|
@ -75,7 +73,7 @@ else:
|
|||
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_convbert import CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvBertConfig, ConvBertOnnxConfig
|
||||
from .configuration_convbert import ConvBertConfig, ConvBertOnnxConfig
|
||||
from .tokenization_convbert import ConvBertTokenizer
|
||||
|
||||
try:
|
||||
|
@ -93,7 +91,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_convbert import (
|
||||
CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
ConvBertForMaskedLM,
|
||||
ConvBertForMultipleChoice,
|
||||
ConvBertForQuestionAnswering,
|
||||
|
@ -112,7 +109,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_tf_convbert import (
|
||||
TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
TFConvBertForMaskedLM,
|
||||
TFConvBertForMultipleChoice,
|
||||
TFConvBertForQuestionAnswering,
|
||||
|
|
|
@ -25,9 +25,6 @@ from ...utils import logging
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class ConvBertConfig(PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`ConvBertModel`]. It is used to instantiate an
|
||||
|
|
|
@ -46,9 +46,6 @@ _CHECKPOINT_FOR_DOC = "YituTech/conv-bert-base"
|
|||
_CONFIG_FOR_DOC = "ConvBertConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
def load_tf_weights_in_convbert(model, config, tf_checkpoint_path):
|
||||
"""Load tf checkpoints in a pytorch model."""
|
||||
try:
|
||||
|
|
|
@ -61,9 +61,6 @@ _CHECKPOINT_FOR_DOC = "YituTech/conv-bert-base"
|
|||
_CONFIG_FOR_DOC = "ConvBertConfig"
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import TF_CONVBERT_PRETRAINED_MODEL_ARCHIVE_LIST # noqa: F401, E402
|
||||
|
||||
|
||||
# Copied from transformers.models.albert.modeling_tf_albert.TFAlbertEmbeddings with Albert->ConvBert
|
||||
class TFConvBertEmbeddings(keras.layers.Layer):
|
||||
"""Construct the embeddings from word, position and token_type embeddings."""
|
||||
|
|
|
@ -22,9 +22,7 @@ from ...utils import (
|
|||
)
|
||||
|
||||
|
||||
_import_structure = {
|
||||
"configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig", "ConvNextOnnxConfig"]
|
||||
}
|
||||
_import_structure = {"configuration_convnext": ["ConvNextConfig", "ConvNextOnnxConfig"]}
|
||||
|
||||
try:
|
||||
if not is_vision_available():
|
||||
|
@ -42,7 +40,6 @@ except OptionalDependencyNotAvailable:
|
|||
pass
|
||||
else:
|
||||
_import_structure["modeling_convnext"] = [
|
||||
"CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
|
||||
"ConvNextForImageClassification",
|
||||
"ConvNextModel",
|
||||
"ConvNextPreTrainedModel",
|
||||
|
@ -62,7 +59,7 @@ else:
|
|||
]
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig
|
||||
from .configuration_convnext import ConvNextConfig, ConvNextOnnxConfig
|
||||
|
||||
try:
|
||||
if not is_vision_available():
|
||||
|
@ -80,7 +77,6 @@ if TYPE_CHECKING:
|
|||
pass
|
||||
else:
|
||||
from .modeling_convnext import (
|
||||
CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
|
||||
ConvNextBackbone,
|
||||
ConvNextForImageClassification,
|
||||
ConvNextModel,
|
||||
|
|
|
@ -28,9 +28,6 @@ from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feat
|
|||
logger = logging.get_logger(__name__)
|
||||
|
||||
|
||||
from ..deprecated._archive_maps import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP # noqa: F401, E402
|
||||
|
||||
|
||||
class ConvNextConfig(BackboneConfigMixin, PretrainedConfig):
|
||||
r"""
|
||||
This is the configuration class to store the configuration of a [`ConvNextModel`]. It is used to instantiate an
|
||||
|
|
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue