code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
... | 16 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class _A :
_SCREAMING_SNAKE_CASE : List[str]
_... | 16 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common im... | 16 |
'''simple docstring'''
from statistics import mean
import numpy as np
def lowercase_ ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAm... | 16 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availa... | 16 |
'''simple docstring'''
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, r... | 16 | 1 |
'''simple docstring'''
from math import log
from scipy.constants import Boltzmann, physical_constants
_UpperCamelCase = 300 # TEMPERATURE (unit = K)
def lowercase_ ( lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : flo... | 16 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_... | 16 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 16 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 16 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : bool , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : float ):
"... | 16 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enab... | 16 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inp... | 16 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 ) -> None:
'''simple docstring'''
__UpperCAmelCase , __UpperCAmelC... | 16 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as... | 16 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCamelCase = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRETRAINED_... | 16 | 1 |
'''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 16 |
'''simple docstring'''
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
... | 16 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_... | 16 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class _A ( __SCREAMING_SNAKE_CASE ):
_SC... | 16 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available... | 16 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configura... | 16 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/mai... | 16 |
'''simple docstring'''
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as tran... | 16 | 1 |
'''simple docstring'''
import os
def lowercase_ ( lowerCAmelCase__ : str = "input.txt" ):
"""simple docstring"""
with open(os.path.join(os.path.dirname(lowerCAmelCase__ ) , lowerCAmelCase__ ) ) as input_file:
__UpperCAmelCase : List[Any] = [
... | 16 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .... | 16 | 1 |
'''simple docstring'''
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
_UpperCamelCase = '''src/diffusers'''
# Matches is_xxx_available()
_UpperCamelCase ... | 16 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
_UpperCamelCase = logging.ge... | 16 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImage... | 16 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {
'... | 16 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def lowercase_ ( lowerCAmelCase__ : str ):
... | 16 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class _A ( __SCREAMING_SNAKE_CASE ):
def __init__( self , *__Uppe... | 16 | 1 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParam... | 16 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, requi... | 16 | 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 BatchFeat... | 16 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _A ( metaclass=__SCREAMING_SNAKE_CASE ):
_SCREAMING_SNAKE_CASE : List[str] = ["sentencepiece"]
def __init__( self , *__UpperCAmelCase , **__UpperCAmelCase ) -> ... | 16 | 1 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_ava... | 16 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _A :
def __init__( self , __UpperCAmelCase=2 , __UpperCAmelCase=3 , __UpperCAmelCase=64 , __UpperCAmelCase... | 16 | 1 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class _A :
def __init__( self , __UpperCAmelCase ) -> Any:
'''simple docstring'''
__UpperCAmelCase : Union[str, Any] = str(id_ )
__UpperCAm... | 16 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, ... | 16 | 1 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def lowercase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : flo... | 16 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[int] | None = None ):
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__UpperCAmelCase ... | 16 | 1 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
_UpperCamelCase = logging.getLogger(__nam... | 16 |
'''simple docstring'''
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase=None , __UpperCAmelCase=None ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : int = data
__UpperCAmelCase : int = prev... | 16 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : Any = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowercase_ ( lowerCAmelCase__ : int ):
"""... | 16 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class _A :
_SCREAMING_SNAKE_CASE : List[str]
_... | 16 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _A ( metaclass=__SCREAMING_SNAKE_CASE ):
_SCREAMING_SNAKE_CASE : Optional[Any] = ["note_seq"]
def __init__( self , *__UpperCAmelCase , **__UpperCAmelCase ) -> ... | 16 |
'''simple docstring'''
from statistics import mean
import numpy as np
def lowercase_ ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAm... | 16 | 1 |
'''simple docstring'''
import os
def lowercase_ ( ):
"""simple docstring"""
with open(os.path.dirname(lowerCAmelCase__ ) + """/p022_names.txt""" ) as file:
__UpperCAmelCase : Union[str, Any] = str(file.readlines()[0] )
__UpperCAmelCase : int =... | 16 |
'''simple docstring'''
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, r... | 16 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enab... | 16 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_... | 16 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCamelCase = {'''configuration_encoder_decoder''': ['''EncoderDecoderConfig''... | 16 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 16 | 1 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _A ( __SCREAMING_SNAKE_CASE ):
_SCREAMING_SNAKE_CASE : List[Any] = ""
_SCREAMING_SNAKE_... | 16 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enab... | 16 | 1 |
'''simple docstring'''
import datasets
_UpperCamelCase = '''\
@InProceedings{conneau2018xnli,
author = "Conneau, Alexis
and Rinott, Ruty
and Lample, Guillaume
and Williams, Adina
and Bowman, Samuel R.
and S... | 16 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 ) -> None:
'''simple docstring'''
__UpperCAmelCase , __UpperCAmelC... | 16 | 1 |
'''simple docstring'''
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
_UpperCamelCase = Lock()
def lowercase_ ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Dict , l... | 16 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCamelCase = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRETRAINED_... | 16 | 1 |
'''simple docstring'''
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
C... | 16 |
'''simple docstring'''
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
... | 16 | 1 |
'''simple docstring'''
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
_UpperCamelCase = logging.get_... | 16 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class _A ( __SCREAMING_SNAKE_CASE ):
_SC... | 16 | 1 |
'''simple docstring'''
from importlib import import_module
from .logging import get_logger
_UpperCamelCase = get_logger(__name__)
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase=None ) -> Optional[Any]:
'''simple do... | 16 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configura... | 16 | 1 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowercase_ ( ):
"""simple docstring"""
__UpperCAmelCase : Optional[Any] = A... | 16 |
'''simple docstring'''
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as tran... | 16 | 1 |
'''simple docstring'''
from graphs.minimum_spanning_tree_kruskal import kruskal
def lowercase_ ( ):
"""simple docstring"""
__UpperCAmelCase : List[str] = 9
__UpperCAmelCase : Dict = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
... | 16 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .... | 16 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {
'''configuration_layoutlm... | 16 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
_UpperCamelCase = logging.ge... | 16 | 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
_UpperCamelCase = logging.get_logger(__name__)
_Upper... | 16 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {
'... | 16 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase = {... | 16 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class _A ( __SCREAMING_SNAKE_CASE ):
def __init__( self , *__Uppe... | 16 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class _A :
_SCREAMING_SNAKE_CASE : List[str]
_... | 16 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, requi... | 16 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/... | 16 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _A ( metaclass=__SCREAMING_SNAKE_CASE ):
_SCREAMING_SNAKE_CASE : List[str] = ["sentencepiece"]
def __init__( self , *__UpperCAmelCase , **__UpperCAmelCase ) -> ... | 16 | 1 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCamelCase = log... | 16 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _A :
def __init__( self , __UpperCAmelCase=2 , __UpperCAmelCase=3 , __UpperCAmelCase=64 , __UpperCAmelCase... | 16 | 1 |
'''simple docstring'''
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelC... | 16 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, ... | 16 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, ... | 16 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[int] | None = None ):
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__UpperCAmelCase ... | 16 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
_UpperCamelCase = {'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''... | 16 |
'''simple docstring'''
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase=None , __UpperCAmelCase=None ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : int = data
__UpperCAmelCase : int = prev... | 16 | 1 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int = 100 ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = set()
__UpperCAmelCase : Dict = 0
__UpperCAmelCase : List[str] = n + 1 # maximum limit
fo... | 16 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class _A :
_SCREAMING_SNAKE_CASE : List[str]
_... | 16 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class _A ( unittest.TestCase ... | 16 |
'''simple docstring'''
from statistics import mean
import numpy as np
def lowercase_ ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAm... | 16 | 1 |
'''simple docstring'''
import torch
def lowercase_ ( ):
"""simple docstring"""
if torch.cuda.is_available():
__UpperCAmelCase : Dict = torch.cuda.device_count()
else:
__UpperCAmelCase : str = 0
print(f'Successfully ran on {num_gp... | 16 |
'''simple docstring'''
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, r... | 16 | 1 |
'''simple docstring'''
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> Any:
'''simple docstring'''
__UpperCAmelCase : List[Any] = name
__UpperCAmelCase : Any = value
__Uppe... | 16 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_... | 16 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class _A ( __SCREAMING_SNAKE_CASE ):
def __init__( self , *__UpperC... | 16 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 16 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
_UpperCamelCase = logging.get_lo... | 16 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enab... | 16 | 1 |
'''simple docstring'''
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_M... | 16 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 ) -> None:
'''simple docstring'''
__UpperCAmelCase , __UpperCAmelC... | 16 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils impo... | 16 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCamelCase = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRETRAINED_... | 16 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:... | 16 |
'''simple docstring'''
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
... | 16 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''facebook/s2t-wav2vec2-large-en-de''': (
'''https://huggingface.co/facebook/s2t-wav2vec2-... | 16 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class _A ( __SCREAMING_SNAKE_CASE ):
_SC... | 16 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers imp... | 16 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configura... | 16 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils im... | 16 |
'''simple docstring'''
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as tran... | 16 | 1 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def lowercase_ ( ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = HfArgumentParser(lowerCAmelCase__ )
__UpperCAmelCase : int ... | 16 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .... | 16 | 1 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase_ ( lowerCAmelCase__ : Optional[int] ):
"""simple docstring"""
__UpperCAmelCase : Any = [
... | 16 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
_UpperCamelCase = logging.ge... | 16 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Generic, TypeVar
_UpperCamelCase = TypeVar('''T''')
class _A ( Generic[T] ):
def __init__( self , __UpperCAmelCase ) -> None:
'''simple docstring'''
... | 16 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {
'... | 16 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def lowercase_ ( lowerCAmelCase__ : NDArray[floataa] , lowerCAmelCase__ : NDArray[floataa] , lowerCAmelCase__ : list[int]... | 16 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class _A ( __SCREAMING_SNAKE_CASE ):
def __init__( self , *__Uppe... | 16 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
_UpperCame... | 350 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, requi... | 16 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from... | 351 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _A ( metaclass=__SCREAMING_SNAKE_CASE ):
_SCREAMING_SNAKE_CASE : List[str] = ["sentencepiece"]
def __init__( self , *__UpperCAmelCase , **__UpperCAmelCase ) -> ... | 16 | 0 |
'''simple docstring'''
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_UpperCamelCase = ... | 352 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _A :
def __init__( self , __UpperCAmelCase=2 , __UpperCAmelCase=3 , __UpperCAmelCase=64 , __UpperCAmelCase... | 16 | 0 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
_UpperCamelCase = HfArgumentParser(InitializationArguments)
_UpperCamelCase = parser.parse_args()
... | 353 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, ... | 16 | 0 |
'''simple docstring'''
from __future__ import annotations
_UpperCamelCase = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],
'''G... | 354 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[int] | None = None ):
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__UpperCAmelCase ... | 16 | 0 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
_UpperCamelCase = '''docs/source/en/_toctree.yml'''
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Any = default... | 355 |
'''simple docstring'''
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase=None , __UpperCAmelCase=None ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : int = data
__UpperCAmelCase : int = prev... | 16 | 0 |
'''simple docstring'''
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow... | 356 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class _A :
_SCREAMING_SNAKE_CASE : List[str]
_... | 16 | 0 |
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(__SCREAMING_SNAKE_CASE ... | 357 |
'''simple docstring'''
from statistics import mean
import numpy as np
def lowercase_ ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAm... | 16 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase = {
'configuration_whisper': ['WHISPER_PRETRAINED... | 358 |
'''simple docstring'''
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, r... | 16 | 0 |
'''simple docstring'''
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
_UpperCamelCase = {
"""Acehnese Arabic""": """ace_Arab""",
"""Acehnese Latin""": """ace_Latn""",
"""Mesopotamian Arabic""": """acm_Arab""",
"""Ta'izzi-Aden... | 359 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_... | 16 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {
'''configuration_perceiver''': ['''PERCEIVER_PR... | 360 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 16 | 0 |
'''simple docstring'''
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def lo... | 361 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enab... | 16 | 0 |
'''simple docstring'''
from PIL import Image
def lowercase_ ( lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : int ):
"""simple docstring"""
def brightness(lowerCAmelCase__ : Dict ) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.... | 362 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 ) -> None:
'''simple docstring'''
__UpperCAmelCase , __UpperCAmelC... | 16 | 0 |
'''simple docstring'''
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_UpperCamelCase = 10
def lowercase_ ( lowerCAmelCase__ : Any , lowerCAmelCa... | 363 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCamelCase = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRETRAINED_... | 16 | 0 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : Optional[int] = 600851475143 ):
"""simple docstring"""
try:
__UpperCAmelCase : Tuple = int(a_ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable to i... | 364 |
'''simple docstring'''
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
... | 16 | 0 |
'''simple docstring'''
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils imp... | 365 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class _A ( __SCREAMING_SNAKE_CASE ):
_SC... | 16 | 0 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
"""simple docstring"""
return int(input_a == input_a == 0 )
def lowercase_ ( ):
"""simple docstring"""
print("""Truth Table of NOR Gate:"... | 366 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configura... | 16 | 0 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmel... | 367 |
'''simple docstring'''
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as tran... | 16 | 0 |
'''simple docstring'''
import math
def lowercase_ ( lowerCAmelCase__ : List[Any] ):
"""simple docstring"""
__UpperCAmelCase : Any = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(a__ )
def lowercase_ ( lowerCAmelCase__ : ... | 368 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .... | 16 | 0 |
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
_UpperCamelCase = '''Usage of script: script_name <size_of_canvas:int>'''
_UpperCamelCase = [0] * 100 + [1] * 10
random.shuffle(choice)
def ... | 369 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
_UpperCamelCase = logging.ge... | 16 | 0 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
_UpperCamelCase = pd.read_csv('''sample_data.csv''', h... | 370 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {
'... | 16 | 0 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class _A :
@property
def __A ( self ) -> ... | 371 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_UpperCamelCase = logging.get_logger(__name__)
class _A ( __SCREAMING_SNAKE_CASE ):
def __init__( self , *__Uppe... | 16 | 0 |
'''simple docstring'''
import os
from typing import Dict, List, Tuple, TypeVar, Union
_UpperCamelCase = TypeVar('''T''')
_UpperCamelCase = Union[List[T], Tuple[T, ...]]
_UpperCamelCase = Union[T, List[T], Dict[str, T]]
_UpperCamelCase = Union[str, ... | 350 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, requi... | 16 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
... | 351 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _A ( metaclass=__SCREAMING_SNAKE_CASE ):
_SCREAMING_SNAKE_CASE : List[str] = ["sentencepiece"]
def __init__( self , *__UpperCAmelCase , **__UpperCAmelCase ) -> ... | 16 | 0 |
'''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 lowercase_ ( ... | 352 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _A :
def __init__( self , __UpperCAmelCase=2 , __UpperCAmelCase=3 , __UpperCAmelCase=64 , __UpperCAmelCase... | 16 | 0 |
'''simple docstring'''
import itertools
import math
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, al... | 353 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, ... | 16 | 0 |
'''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,
WavaVecaProcessor,
l... | 354 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[int] | None = None ):
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__UpperCAmelCase ... | 16 | 0 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
"""simple docstring"""
if not isinstance(lowercase__ , lowercase__ ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstanc... | 355 |
'''simple docstring'''
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase=None , __UpperCAmelCase=None ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : int = data
__UpperCAmelCase : int = prev... | 16 | 0 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers ... | 356 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class _A :
_SCREAMING_SNAKE_CASE : List[str]
_... | 16 | 0 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
_UpperCamelCase = '''\
@misc{wu2016googles,
title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author... | 357 |
'''simple docstring'''
from statistics import mean
import numpy as np
def lowercase_ ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAm... | 16 | 0 |
'''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : List[str] = prime_factors(_UpperCamelCase )
if is_square_free(_UpperCa... | 358 |
'''simple docstring'''
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, r... | 16 | 0 |
'''simple docstring'''
import torch
from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool
if is_datasets_available():
from datasets import load_dataset
class _A ( __SCRE... | 359 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_... | 16 | 0 |
'''simple docstring'''
import operator as op
_UpperCamelCase = 'scaler.pt'
_UpperCamelCase = 'pytorch_model'
_UpperCamelCase = 'random_states'
_UpperCamelCase = 'optimizer'
_UpperCamelCase = 'scheduler'
_UpperCamelCase = 'p... | 360 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 16 | 0 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTes... | 361 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enab... | 16 | 0 |
'''simple docstring'''
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import ... | 362 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = 0 ) -> None:
'''simple docstring'''
__UpperCAmelCase , __UpperCAmelC... | 16 | 0 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import ... | 363 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCamelCase = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRETRAINED_... | 16 | 0 |
'''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 DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from... | 364 |
'''simple docstring'''
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
... | 16 | 0 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : str ):
"""simple docstring"""
__UpperCAmelCase : Any = []
__UpperCAmelCase : Union[str, Any] = set({"""(""", """[""", """{"""} )
__UpperCAmelCase : Optional[int] = set({""")""", """]""",... | 365 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class _A ( __SCREAMING_SNAKE_CASE ):
_SC... | 16 | 0 |
'''simple docstring'''
import os
import sys
_UpperCamelCase = os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
... | 366 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configura... | 16 | 0 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolForme... | 367 |
'''simple docstring'''
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as tran... | 16 | 0 |
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