code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
class snake_case__ :
"""simple docstring"""
def __init__( self : Union[str, Any] ) -> None:
"""simple docstring"""
snake_case : dict[str, TrieNode] = {} # Mapping from char to TrieNode
... | 638 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 1 |
'''simple docstring'''
lowercase__ = range(2, 2_0 + 1)
lowercase__ = [1_0**k for k in range(ks[-1] + 1)]
lowercase__ = {}
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCRE... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 1 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_... | 638 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 638 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 | 1 |
'''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_ava... | 638 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 638 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import... | 638 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
lowercase__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, ... | 638 | 1 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAna... | 638 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowercase__ = TypeVar("T")
class snake_case__ ( Generic[T] ):
"""simple docstring"""
def __init__( se... | 638 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class snake_case__ ( metaclass=__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase = ["""flax"""]
def __init__( self : List[Any] , *UpperCamelCa... | 638 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 | 1 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...t... | 638 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simp... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_te... | 638 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> float:
'''simple docstring'''
def get_matched_characters(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> str:
snake_case : Dict = []
s... | 638 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 | 1 |
'''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import pi
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> dict[str, float]:
'''simple docstring'''
if (inductance, frequency, reactance)... | 638 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 1 |
'''simple docstring'''
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timest... | 638 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 1 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__=False ) -> str:
'''simple docstring'''
snake_case :... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective... | 638 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def _UpperCamelCase ... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class snake_case__ ( __SCREAMING_SNA... | 638 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.u... | 638 | 1 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "https://www.worldometers.info/coronavirus" ) -> dict:
'''simple docstring'''
snake_case : List[str] = BeautifulSoup(requests.get(SCREA... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 | 1 |
'''simple docstring'''
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def lowerCAmelCase ( self : str , UpperCame... | 638 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 1 |
'''simple docstring'''
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase = (DDPMParallelScheduler,)
... | 638 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
... | 638 | 1 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.array:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 638 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 1 |
'''simple docstring'''
class snake_case__ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCamelCase__ : str = "" , UpperCamelCase__ : bool = False ) -> None:
"""simple docstring"""
snake_case : di... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffu... | 638 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 638 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 | 1 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
lowercase__ = HfArgumentParser(InitializationArguments)
lowercase__ = parser.parse_args()
# Lo... | 638 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 638 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
lowercase__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, ... | 638 | 1 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowercase__ = TypeVar("T")
class snake_case__ ( Generic[T] ):
"""simple docstring"""
def __init__( se... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : Optional[Any] = [0 for i in range(n + 1 )]
snake_case : Optional[int] = 1
snake_case : Tuple = ... | 638 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 | 1 |
'''simple docstring'''
lowercase__ = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ... | 638 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simp... | 638 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import P... | 638 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 | 1 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 | 1 |
'''simple docstring'''
import os
from distutils.util import strtobool
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> Optional[Any]:
'''simple docstring'''
for e in env_keys:
snake_case : str = int(os.environ.get(... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> bool:
'''simple docstring'''
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(SCREAMIN... | 638 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 3 , SCREAMING_SNAKE_CASE__ = 7 , SCREAMING_SNAKE_CASE__ = 100_0000 ) -> int:
'''simple docstring'''
snake_case : str = 0
snake_case : Tuple = 1
for curr... | 638 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 1 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
lowercase__ = True
except (ImportError, ModuleNotFoundError):
lowercase__ = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("... | 638 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
@staticmethod
@abstractmethod
def lowerCAmelCase ( UpperCamelCase__ : Argum... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective... | 638 | 1 |
'''simple docstring'''
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase ... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 1 |
'''simple docstring'''
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 638 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.u... | 638 | 1 |
'''simple docstring'''
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configurati... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 | 1 |
'''simple docstring'''
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto impor... | 638 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 1 |
'''simple docstring'''
lowercase__ = {
"joule": 1.0,
"kilojoule": 1_0_0_0,
"megajoule": 1_0_0_0_0_0_0,
"gigajoule": 1_0_0_0_0_0_0_0_0_0,
"wattsecond": 1.0,
"watthour": 3_6_0_0,
"kilowatthour": 3_6_0_0_0_0_0,
"newtonmeter": 1.0,
"calorie_nutr": 4_1_8_6.8,
... | 638 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
... | 638 | 1 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , ... | 638 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 1 |
'''simple docstring'''
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
lowercase__ ... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 1 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class snake_case__... | 638 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 | 1 |
'''simple docstring'''
lowercase__ = {}
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left,... | 638 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
lowercase__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, ... | 638 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
lowercase__ ... | 638 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowercase__ = TypeVar("T")
class snake_case__ ( Generic[T] ):
"""simple docstring"""
def __init__( se... | 638 | 1 |
'''simple docstring'''
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
... | 638 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
lowercase__ = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
class snake_case__ :
"""... | 638 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simp... | 638 | 1 |
'''simple docstring'''
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone ... | 638 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> Optional[int]:
'''simple docstring'''
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(SCREAMING_SNAKE_CASE__ , ... | 638 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 | 1 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transforme... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 638 | 1 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers imp... | 638 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> str:
'''simple docstring'''
return np.maximum(0 , SCREAMING_SNAKE_CASE__ )
if __name__ == "__main__":
print(np.array(relu... | 638 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 1 |
'''simple docstring'''
import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = ... | 638 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 1 |
'''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> Callable:
'''simple docstring'''
@wraps(SCREAMING_SNAKE_CASE__ )
def _inner_fn(*SCREAMING_SNAKE_CASE__ , **SCREAM... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective... | 638 | 1 |
'''simple docstring'''
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
lowercase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 1 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...tes... | 638 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.u... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
if len(SCREAMING_SNAKE_CASE__ ) != len(SCREAMING_SNAKE_CASE__ ):
raise ValueError('''The length of profit an... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTr... | 638 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaPro... | 638 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
... | 638 | 1 |
'''simple docstring'''
from typing import List
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
snake_case : List[Any] = {key: len(SCREAMING_SNAKE_CASE__ ) for key, value in gen_kwargs.items() if isi... | 638 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> List[str]:
'''simple docstring'''
snake_case : Union[str, Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 1 |
'''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
lowercase__ = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
... | 638 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
lowercase__ = 8.988e9 # units = N * m^s * C^-2
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> dict[str, float]... | 638 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 638 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers im... | 638 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
lowercase__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, ... | 638 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(_... | 638 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowercase__ = TypeVar("T")
class snake_case__ ( Generic[T] ):
"""simple docstring"""
def __init__( se... | 638 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
@staticmethod
@abstractmethod
def lowerCAmelCase ( UpperCamelCase__ : Argum... | 638 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(1 ) != 0 )
def _UpperCamelCase ( ) -> None:
'''simple docstring'''
... | 638 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simp... | 638 | 1 |
'''simple docstring'''
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
lowercase__ = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create two fuzzy sets by defining an... | 638 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 | 1 |
'''simple docstring'''
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> Any:
'''simple docstring'''
monkeypatch.setattr('''datasets.utils.deprecation_utils._emitted_deprecat... | 638 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 | 1 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_a... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 638 | 1 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowercase__ = False
class snake... | 638 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 638 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, Tens... | 638 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = "." ) -> Iterator[str]:
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
snake_case : Optiona... | 638 | 1 |
'''simple docstring'''
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user pa... | 638 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 638 | 1 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import c... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective... | 638 | 1 |
'''simple docstring'''
import copy
import os
from typing import Union
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
lowercase__ = logging.get_l... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 1 |
'''simple docstring'''
import math
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> list:
'''simple docstring'''
snake_case : List[str] = [True] * n
snake_case : Dict = False
snake_case : Any = False
snak... | 638 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.u... | 638 | 1 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def _UpperCamelCase ... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 638 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 |
'''simple docstring'''
from __future__ import annotations
import queue
class snake_case__ :
"""simple docstring"""
def __init__( self : int , UpperCamelCase__ : Optional[int] ) -> Dict:
"""simple docstring"""
... | 638 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"junnyu... | 638 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
... | 638 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers im... | 638 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
fro... | 638 | 1 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 638 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common ... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 638 | 1 |
'''simple docstring'''
import socket
def _UpperCamelCase ( ) -> Optional[int]:
'''simple docstring'''
snake_case : Optional[Any] = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
snake_case : Dict = socket.gethostname()
... | 638 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCo... | 638 | 1 |
'''simple docstring'''
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
lowercase__ = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=Dat... | 638 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> Union[str, Any]: # noqa: E741
'''simple docstring'''
snake_case : Any = len(SCREAMING_SNAKE_CASE__ )
snake_case : Any = 0
snake_case : Tuple = ... | 638 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE... | 638 | 1 |
'''simple docstring'''
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class snake_case__ :
"""simple docstring"""
lowerCamelCase = 42
lowerCamelCase = None
lowerCamelCase = None
... | 638 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
lowercase__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, ... | 638 | 1 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
... | 638 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowercase__ = TypeVar("T")
class snake_case__ ( Generic[T] ):
"""simple docstring"""
def __init__( se... | 638 | 1 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenizat... | 638 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowercase__ = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring... | 638 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> list[list]:
'''simple docstring'''
snake_case : Union[str, Any] = current_set.copy()
for row_index, row in enumerate(SCREAMING_SNAKE_CASE__ ):
snake_case : List[Any] ... | 638 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> np.ndarray:
'''simp... | 638 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"goog... | 638 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase__ = logging.get_logger(__name__)
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def _... | 638 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
try... | 638 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ = 200_0000 ) -> int:
'''simple docstring'''
snake_case : list[int] = [0]
snake_case : int
for id... | 638 | 1 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
f... | 638 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 638 | 1 |
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