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 |
|---|---|---|---|---|
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'microsoft/git-base': 'https://huggingface.co/mi... | 101 |
print((lambda quine: quine % quine)('''print((lambda quine: quine %% quine)(%r))'''))
| 47 | 0 |
"""simple docstring"""
from itertools import permutations
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 102 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.ber... | 47 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
snake_case = log... | 103 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
"""simple docstring"""
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import Iterab... | 104 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase( metaclass=__lowerCamelCase ):
__SCREAMING_SNAKE_CASE : Optional[Any] = ['''torch''', '''transformers''', '''onnx''']
def __init__( self : Dict , *SCREAMING_SNAKE_CAS... | 47 | 0 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class lowerCAmelCase_ ( nn.Module ):
__a : int
__a : int
__a : float ... | 105 |
import math
from datetime import datetime, timedelta
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
__a : Union[str, Any] = year % 1_9
__a : int = year % 4
__a : Optional[int] = year % 7
__a : Dict... | 47 | 0 |
from __future__ import annotations
def lowerCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
if len(lowerCAmelCase__ ) < k or k < 0:
raise ValueError('Invalid Input' )
A = A ... | 106 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''huggingface/informer-tourism-monthly''': (
'''https://... | 47 | 0 |
'''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_avail... | 107 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase( __lowerCamelCase ):
__SCREAMING_SNAKE_CASE : int = (DDIMParallelScheduler,)
__SCREAMING_SNAKE_CASE : Union[str, Any]... | 47 | 0 |
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
__a: Union[str, Any] = logging.get_logger(__name__)
__... | 108 |
def UpperCAmelCase__ ( lowerCamelCase_ : list[int] , lowerCamelCase_ : list[int] ):
# Check if the input is valid
if not len(lowerCamelCase_ ) == len(lowerCamelCase_ ) == 3:
raise ValueError('Please enter a valid equation.' )
if equa... | 47 | 0 |
'''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,
nested... | 109 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 47 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import... | 110 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE__ = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerC... | 47 | 0 |
"""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 UpperCAmelCase_ ( __lowerCame... | 76 |
from string import ascii_lowercase, ascii_uppercase
def UpperCAmelCase__ ( lowerCamelCase_ : str ):
if not sentence:
return ""
__a : Union[str, Any] = dict(zip(lowerCamelCase_ , lowerCamelCase_ ) )
return lower_to_upper.get(sente... | 47 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils... | 58 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-1... | 47 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,... | 436 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ = TypeVar('''T''')
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
return (position - 1) // 2
def UpperCAmelCase__ ( low... | 47 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logg... | 210 |
from collections.abc import Sequence
from queue import Queue
class _UpperCamelCase:
def __init__( self : Tuple , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Tuple , SCREAMIN... | 47 | 0 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class A( unittest.TestCase ):
'''simple docstring'''
def a__ ( se... | 70 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MA... | 47 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE = {
'configuration_speecht5': [
'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 553 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
lowerCAmelCase_ : Optional[int] = 6378137.0
lowerCAmelCase_ : Tuple = 6356752.314245
lowerCAmelCase_ : Any = 6378137
def __A ( ... | 414 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 47 | 0 |
'''simple docstring'''
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
_UpperCAmelCase : str = TypeVar('''T''')
def _SCREAMING_SNAKE_CASE ( __snake_case : int ):
return (position - 1) // 2
def _SCREAMING_SNAKE_... | 107 |
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[int] , lowerCamelCase_ : List[str] ):
__a : Any = ''
for i in table:
res += inp[i - 1]
return res
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[... | 47 | 0 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
lowerCAmelCase : str = logging.get_logger("""transformers.models.speecht5""")
def _A ( A ,A ,A ... | 372 |
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers impo... | 47 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _SCREAMING_SNAKE_CASE ( metaclass=__lowerCamelCase ):
"""simple docstring"""
_a : Optional[Any] = ['''torch''', '''transformers''', '''onnx''']
def __init__( self , *lowerCamelCa... | 200 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''roberta-... | 47 | 0 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
__magic_name__ = Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io # n... | 250 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
tr... | 76 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers... | 47 | 0 |
"""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/licen... | 58 |
print((lambda quine: quine % quine)('''print((lambda quine: quine %% quine)(%r))'''))
| 47 | 0 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
_SCREAMING_SNAKE_CASE : int = (7_20, 12_80) # Height, Width
_SCREAMING_SNAKE_CASE : Optional[int] = (0.4, ... | 436 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.ber... | 47 | 0 |
'''simple docstring'''
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCamelCase__ ( A : Dict , A : Optional[Any] , A : Dict ):
'''simple docstring'''
UpperCAmelCase = AutoConfig.from_pret... | 210 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's easier to use for... | 70 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase( metaclass=__lowerCamelCase ):
__SCREAMING_SNAKE_CASE : Optional[Any] = ['''torch''', '''transformers''', '''onnx''']
def __init__( self : Dict , *SCREAMING_SNAKE_CAS... | 47 | 0 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfig
from... | 553 |
import math
from datetime import datetime, timedelta
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
__a : Union[str, Any] = year % 1_9
__a : int = year % 4
__a : Optional[int] = year % 7
__a : Dict... | 47 | 0 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowerCAmelCase_ : Optional[int] = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_he... | 414 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''huggingface/informer-tourism-monthly''': (
'''https://... | 47 | 0 |
'''simple docstring'''
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_UpperCAmelCase : List[Any] = {1: (1, 1), 2: (2, 1), 3: (... | 107 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase( __lowerCamelCase ):
__SCREAMING_SNAKE_CASE : int = (DDIMParallelScheduler,)
__SCREAMING_SNAKE_CASE : Union[str, Any]... | 47 | 0 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase : Tuple = logging.getLogger(__name__)
def _A ( ) -> List[str]:
lowercase : Union[str, Any] = argparse.Argum... | 372 |
def UpperCAmelCase__ ( lowerCamelCase_ : list[int] , lowerCamelCase_ : list[int] ):
# Check if the input is valid
if not len(lowerCamelCase_ ) == len(lowerCamelCase_ ) == 3:
raise ValueError('Please enter a valid equation.' )
if equa... | 47 | 0 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
__snake_case = logging.get_log... | 200 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 47 | 0 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
fro... | 250 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE__ = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerC... | 47 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a_ = {'processing_layoutxlm':... | 76 |
from string import ascii_lowercase, ascii_uppercase
def UpperCAmelCase__ ( lowerCamelCase_ : str ):
if not sentence:
return ""
__a : Union[str, Any] = dict(zip(lowerCamelCase_ , lowerCamelCase_ ) )
return lower_to_upper.get(sente... | 47 | 0 |
"""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/licen... | 58 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-1... | 47 | 0 |
'''simple docstring'''
import os
_SCREAMING_SNAKE_CASE : Optional[Any] = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 1_00, "D": 5_00, "M": 10_00}
def _UpperCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
__magic_name__ : ... | 436 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ = TypeVar('''T''')
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
return (position - 1) // 2
def UpperCAmelCase__ ( low... | 47 | 0 |
'''simple docstring'''
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_... | 210 |
from collections.abc import Sequence
from queue import Queue
class _UpperCamelCase:
def __init__( self : Tuple , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Tuple , SCREAMIN... | 47 | 0 |
import numpy
# List of input, output pairs
lowerCamelCase : Union[str, Any] = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowerCamelCase : Tuple = (((515, 22, 13), 555), ((61, 35, 49)... | 70 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MA... | 47 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sche... | 553 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class __lowerCAmelCase :
def __init__(self , lowerCAmelCase__ ):
_UpperCAmelCase : str = str(id_ )
_UpperCAmelCase : Option... | 414 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 47 | 0 |
'''simple docstring'''
import re
import string
import numpy as np
import datasets
_UpperCAmelCase : Tuple = '''
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
'''
_UpperCAmelCase :... | 107 |
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[int] , lowerCamelCase_ : List[str] ):
__a : Any = ''
for i in table:
res += inp[i - 1]
return res
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[... | 47 | 0 |
'''simple docstring'''
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
... | 372 |
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers impo... | 47 | 0 |
"""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 ...test_conf... | 200 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''roberta-... | 47 | 0 |
def __magic_name__ ( lowerCAmelCase_):
'''simple docstring'''
lowerCamelCase_ : Union[str, Any] = [1]
lowerCamelCase_ : Optional[int] = 0, 0, 0
lowerCamelCase_ : int = ugly_nums[ia] * 2
lowerCamelCase_ : Tuple ... | 250 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=__lowerCamelCase ):
UpperCamelCase =['''flax''']
def __init__( self , *UpperCamelCase_ , **UpperCamelCase_ ) -> Any:
requires_... | 76 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers... | 47 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaV... | 58 |
print((lambda quine: quine % quine)('''print((lambda quine: quine %% quine)(%r))'''))
| 47 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def _UpperCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
if (
(cp... | 436 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.ber... | 47 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : List[str] = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""... | 210 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase : Optional[int] = TypeVar("T")
lowerCamelCase : Optional[Any] = TypeVar("U")
class A( Generic[T, U] ):
'... | 70 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase( metaclass=__lowerCamelCase ):
__SCREAMING_SNAKE_CASE : Optional[Any] = ['''torch''', '''transformers''', '''onnx''']
def __init__( self : Dict , *SCREAMING_SNAKE_CAS... | 47 | 0 |
"""simple docstring"""
import math
def UpperCAmelCase ( a__ = 1_00 ):
'''simple docstring'''
lowerCAmelCase :Dict = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase :List[Any] = int(math.pow(sum(range(1 , n + 1 ) ) , ... | 553 |
import math
from datetime import datetime, timedelta
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
__a : Union[str, Any] = year % 1_9
__a : int = year % 4
__a : Optional[int] = year % 7
__a : Dict... | 47 | 0 |
'''simple docstring'''
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRobertaXLForMas... | 414 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''huggingface/informer-tourism-monthly''': (
'''https://... | 47 | 0 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
_UpperCAmelCase : str = '''\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu}... | 107 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase( __lowerCamelCase ):
__SCREAMING_SNAKE_CASE : int = (DDIMParallelScheduler,)
__SCREAMING_SNAKE_CASE : Union[str, Any]... | 47 | 0 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : List[str] = logging.get_logger(__name__)
lowerCAmelCase : List[str] = {
"""xlnet-base-cased""": """https://huggingface.co/xlnet-base-cased... | 372 |
def UpperCAmelCase__ ( lowerCamelCase_ : list[int] , lowerCamelCase_ : list[int] ):
# Check if the input is valid
if not len(lowerCamelCase_ ) == len(lowerCamelCase_ ) == 3:
raise ValueError('Please enter a valid equation.' )
if equa... | 47 | 0 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _SCREAMING_SNAKE_CASE ( __low... | 200 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 47 | 0 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, loggi... | 250 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE__ = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerC... | 47 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'roberta-base': '... | 76 |
from string import ascii_lowercase, ascii_uppercase
def UpperCAmelCase__ ( lowerCamelCase_ : str ):
if not sentence:
return ""
__a : Union[str, Any] = dict(zip(lowerCamelCase_ , lowerCamelCase_ ) )
return lower_to_upper.get(sente... | 47 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
__lowerCAmelCase : Dict = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq... | 58 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-1... | 47 | 0 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 1 , UpperCamelCase__ = 1000 ):
"""simple docstring"""
__magic_name__ : Dict = 1
__magic_name__ : Optional[Any] = 0
for divide_by_num... | 436 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ = TypeVar('''T''')
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
return (position - 1) // 2
def UpperCAmelCase__ ( low... | 47 | 0 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
_lowercase : Union[str, Any] = 3
def lowerCamelCase__ ( A : int ):
'''simple docstring'''
print('''Generating primitive root of p''' )... | 210 |
from collections.abc import Sequence
from queue import Queue
class _UpperCamelCase:
def __init__( self : Tuple , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Tuple , SCREAMIN... | 47 | 0 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _SCREAMING_SNAKE_CASE ( ... | 70 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MA... | 47 | 0 |
"""simple docstring"""
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class __UpperCamelCase ( __lowerCamelCase ):
def __lt__( self : List[Any] , UpperCAmelCase : T... | 553 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
'''simple docstring'''
import math
import tensorflow as tf
from packaging import version
def __A ( lowerCAmelCase_ ):
_UpperCAmelCase : Any = tf.convert_to_tensor(lowerCamelCase_ )
_UpperCAmelCase : Any = 0.5 * (1.0 + tf.math.erf(x / tf.... | 414 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 47 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is... | 107 |
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[int] , lowerCamelCase_ : List[str] ):
__a : Any = ''
for i in table:
res += inp[i - 1]
return res
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[... | 47 | 0 |
'''simple docstring'''
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _A ( A ) -> List[Any]:
if not is_accelerate_available():
return method
lowercase : Union[str, Any] = version.parse... | 372 |
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers impo... | 47 | 0 |
"""simple docstring"""
def _lowerCamelCase ( lowerCamelCase__ : list[list] ):
lowercase__ : List[str] = current_set.copy()
for row_index, row in enumerate(lowerCamelCase_ ):
lowercase__ : Optional[int] = row[0]
for column_index, column in enumerate(low... | 200 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''roberta-... | 47 | 0 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers imp... | 250 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
"""simple docstring"""
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ):
__lowercase : str = (... | 76 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers... | 47 | 0 |
"""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 t... | 58 |
print((lambda quine: quine % quine)('''print((lambda quine: quine %% quine)(%r))'''))
| 47 | 0 |
'''simple docstring'''
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, Test... | 436 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.ber... | 47 | 0 |
'''simple docstring'''
from datetime import datetime
import requests
def lowerCamelCase__ ( A : str ):
'''simple docstring'''
UpperCAmelCase = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
UpperCAmelCase = requests.get(base_ur... | 210 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import... | 70 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase( metaclass=__lowerCamelCase ):
__SCREAMING_SNAKE_CASE : Optional[Any] = ['''torch''', '''transformers''', '''onnx''']
def __init__( self : Dict , *SCREAMING_SNAKE_CAS... | 47 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'tiiuae/falcon-7b... | 553 |
import math
from datetime import datetime, timedelta
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
__a : Union[str, Any] = year % 1_9
__a : int = year % 4
__a : Optional[int] = year % 7
__a : Dict... | 47 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowerCAmelCase_ : Dict = TypeVar('''T''')
class __lowerCAmelCase ( Generic[T] ):
def __init__(self , low... | 414 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''huggingface/informer-tourism-monthly''': (
'''https://... | 47 | 0 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_ava... | 107 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase( __lowerCamelCase ):
__SCREAMING_SNAKE_CASE : int = (DDIMParallelScheduler,)
__SCREAMING_SNAKE_CASE : Union[str, Any]... | 47 | 0 |
'''simple docstring'''
def _A ( ) -> str:
lowercase : Union[str, Any] = 0
for i in range(1 ,1_0_0_1 ):
total += i**i
return str(lowerCamelCase_ )[-1_0:]
if __name__ == "__main__":
print(solution())
| 372 |
def UpperCAmelCase__ ( lowerCamelCase_ : list[int] , lowerCamelCase_ : list[int] ):
# Check if the input is valid
if not len(lowerCamelCase_ ) == len(lowerCamelCase_ ) == 3:
raise ValueError('Please enter a valid equation.' )
if equa... | 47 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = '▁'... | 200 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 47 | 0 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __magic_name__ ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_):
'''simple docstring'''
lowerCamelCase_ : Optional[Any] = 0
if start < end:
lowerCam... | 250 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE__ = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerC... | 47 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
... | 76 |
from string import ascii_lowercase, ascii_uppercase
def UpperCAmelCase__ ( lowerCamelCase_ : str ):
if not sentence:
return ""
__a : Union[str, Any] = dict(zip(lowerCamelCase_ , lowerCamelCase_ ) )
return lower_to_upper.get(sente... | 47 | 0 |
"""simple docstring"""
__lowerCAmelCase : int = '''Tobias Carryer'''
from time import time
class _lowerCAmelCase :
"""simple docstring"""
def __init__( self , _lowercase , _lowercase , _lowercase , ... | 58 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-1... | 47 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self: Tuple , __UpperCamelCase: int , __UpperCamelCase: ... | 436 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ = TypeVar('''T''')
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
return (position - 1) // 2
def UpperCAmelCase__ ( low... | 47 | 0 |
'''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
_lowercase : Tuple = logging.get_logger(__name__)
_lowercase : ... | 210 |
from collections.abc import Sequence
from queue import Queue
class _UpperCamelCase:
def __init__( self : Tuple , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : List[Any] , SCREAMING_SNAKE_CASE__ : Tuple , SCREAMIN... | 47 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase : Union[str, Any] = {
"configuration_pegasus_x": ["PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP", "PegasusXConfig"],
}
try:
if not is_torch_... | 70 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MA... | 47 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaP... | 553 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 414 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 47 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import... | 107 |
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[int] , lowerCamelCase_ : List[str] ):
__a : Any = ''
for i in table:
res += inp[i - 1]
return res
def UpperCAmelCase__ ( lowerCamelCase_ : Optional[... | 47 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 372 |
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers impo... | 47 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__snake_case = {
'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'Visio... | 200 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''roberta-... | 47 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json''',
# See all GLPN models at https://... | 250 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
"""simple docstring"""
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class UpperCAmelCase_ ( yaml.SafeLoader ):
def _lowerCamelCase ( self , UpperCamelCase_ ) -> Optional[Any]:
__lo... | 76 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers... | 47 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCAmelCase : Tuple = {
'''configuration_conditional_detr''': [
'''CONDITIONAL_DETR_P... | 58 |
print((lambda quine: quine % quine)('''print((lambda quine: quine %% quine)(%r))'''))
| 47 | 0 |
'''simple docstring'''
from collections.abc import Sequence
from queue import Queue
class _snake_case :
'''simple docstring'''
def __init__( self: Tuple , __UpperCamelCase: List[str] , __UpperCamelCase: List[Any] ... | 436 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.ber... | 47 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.... | 210 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ ... | 47 | 0 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def _SCREAMING_SNAKE_CASE ( lowercase : List[Any] , lowercase : Optional[int] ... | 70 |
from ..utils import DummyObject, requires_backends
class _UpperCamelCase( metaclass=__lowerCamelCase ):
__SCREAMING_SNAKE_CASE : Optional[Any] = ['''torch''', '''transformers''', '''onnx''']
def __init__( self : Dict , *SCREAMING_SNAKE_CAS... | 47 | 0 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def UpperCAmelCase ( a__ ):
'''simple docstring'''
if num <= 0:
raise ValueError('math domain error' )
return quad(lowerCamelCase_ , 0 , lower... | 553 |
import math
from datetime import datetime, timedelta
def UpperCAmelCase__ ( lowerCamelCase_ : int ):
__a : Union[str, Any] = year % 1_9
__a : int = year % 4
__a : Optional[int] = year % 7
__a : Dict... | 47 | 0 |
'''simple docstring'''
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/chec... | 414 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''huggingface/informer-tourism-monthly''': (
'''https://... | 47 | 0 |
'''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,
resize,
... | 107 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase( __lowerCamelCase ):
__SCREAMING_SNAKE_CASE : int = (DDIMParallelScheduler,)
__SCREAMING_SNAKE_CASE : Union[str, Any]... | 47 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_comm... | 372 |
def UpperCAmelCase__ ( lowerCamelCase_ : list[int] , lowerCamelCase_ : list[int] ):
# Check if the input is valid
if not len(lowerCamelCase_ ) == len(lowerCamelCase_ ) == 3:
raise ValueError('Please enter a valid equation.' )
if equa... | 47 | 0 |
"""simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS... | 200 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 47 | 0 |
__magic_name__ = tuple[float, float, float]
__magic_name__ = tuple[float, float, float]
def __magic_name__ ( lowerCAmelCase_ , lowerCAmelCase_):
'''simple docstring'''
lowerCamelCase_ : int = end_pointa[0] - end_pointa[0]
lowerCamelCase_... | 250 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE__ = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerC... | 47 | 0 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class UpperCAmelCase_ ( __lowerCamelCase ):
UpperCamelCase ='''MCTCTFeatureExtractor'''
UpperCamelCase ='''AutoTokenizer'''
def __init__( ... | 76 |
from string import ascii_lowercase, ascii_uppercase
def UpperCAmelCase__ ( lowerCamelCase_ : str ):
if not sentence:
return ""
__a : Union[str, Any] = dict(zip(lowerCamelCase_ , lowerCamelCase_ ) )
return lower_to_upper.get(sente... | 47 | 0 |
"""simple docstring"""
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __lowerCAmelCase ( ):
'''simple docstring'''
... | 58 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-1... | 47 | 0 |
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