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 |
|---|---|---|---|---|
__UpperCamelCase : Tuple = {
"""a""": """AAAAA""",
"""b""": """AAAAB""",
"""c""": """AAABA""",
"""d""": """AAABB""",
"""e""": """AABAA""",
"""f""": """AABAB""",
"""g""": """AABBA""",
"""h""": """AABBB""",
"""i""": """ABAAA""",
"""j""": """BBBAA""",
"""k""":... | 80 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 | 0 |
from importlib import import_module
from .logging import get_logger
_snake_case : Tuple = get_logger(__name__)
class a :
"""simple docstring"""
def __init__( self : str , lowerCamelCase : str , lowerCamelCase : Dict=None ... | 81 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaT... | 615 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if n_term == "":
return []
UpperCAmelCase_ = []
for temp in range(int(lowerCAmelCase__ ) ):
series.append(f"""1/{temp + 1}""" if series else "1" )
return series
if __name... | 82 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 615 | 0 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class __snake_case ( nn.Module):
snake_case__ : int
snake_case__ : int
sna... | 83 |
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase__ = np.zeros((n + 1,) )
lowerCAmelCase__ = ... | 615 | 0 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class A_ ( __lowerCamelCase ):
'''simple docstring'''
_Upp... | 84 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 | 0 |
import math
from collections.abc import Callable
def _a ( lowercase__ : Callable[[float], float] , lowercase__ : float , lowercase__ : float ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : float = xa
SCREAMING_SNAKE_CASE__ : float ... | 85 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__a :Any = {
'configuration_chinese_clip': [
'CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ChineseCLIPConfig',
'ChineseCLIPOnn... | 86 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCamelCase : List[Any] = {
"""configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}
try:
if not... | 87 |
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
from t... | 615 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase__ ( A_ ,uni... | 88 |
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
__magic_name__ : Optional[int] = get_te... | 615 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 89 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 0 |
'''simple docstring'''
def _snake_case ( A ) -> int:
if n == 1 or not isinstance(A , A ):
return 0
elif n == 2:
return 1
else:
lowerCAmelCase__ = [0, 1]
for i in range(2 , n... | 90 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 0 |
"""simple docstring"""
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
_lowercase = logging.get_logger(__name__)
def _snake_case ( snake_case__ : Dict=None , snake_case__... | 91 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 0 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __magic_name__ : list[list[int]] ) -> int:
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessi... | 92 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 | 0 |
"""simple docstring"""
__A = tuple[float, float, float]
__A = tuple[float, float, float]
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->Vectorad:
"""simple docstring"""
lowerCAmelCase__ :Tuple = end_pointa[0] - end_pointa[0]
... | 93 |
import logging
from transformers.configuration_utils import PretrainedConfig
__magic_name__ : Tuple = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
lowercase_ : Tuple = "masked_bert"
def __init__( self : List[Any] , _... | 615 | 0 |
'''simple docstring'''
import numpy
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : Union[str, Any] , UpperCAmelCase : numpy.ndarray , UpperCAmelCase : numpy.ndarray ) -> None:
'''simple docstring'''
lowercase : An... | 94 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 615 | 0 |
"""simple docstring"""
from __future__ import annotations
lowerCamelCase_ = 8.988E9 # units = N * m^s * C^-2
def snake_case ( A__ ,A__ ,A__ ,A__ ):
UpperCAmelCase_ : str = abs(chargea * chargea )
if (force, chargea, chargea, distance).count(0 ) != 1:
... | 95 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPC... | 615 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class __A :
def __init__( self : List[str] , __snake_case : list[str] ) -> Optional[Any]:
__magic_name__: list[dict] = []
... | 96 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 | 0 |
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepie... | 97 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase = None ):
lowerCAmelCase__ = word_bank or []
# create a table
lowerCAmelCase__ = len(__lowerCAmelCase ) + 1
lowerCAmelCase__ = []
for _ in range(__lowerCA... | 615 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def a__ ( lowercase : Dict, lowercase : str, lowercase : str, lowercase : Path, lowercase : str =... | 98 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 | 0 |
from collections.abc import Callable
def a (lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
__a = a
__a = b
if function(lowerCAmelCase__ ) == 0: # one of the a or b is a root for the function
return a
elif function(lowerCAmelCase__ ) == 0:
... | 99 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__magic_name__ : List[Any] = logging.get_logger(__name__)
def a_ ( __lowerCAmelCase , __lowerCAmelC... | 615 | 0 |
def __snake_case ( lowerCAmelCase_=2_8_1_2_3 ) -> Union[str, Any]:
SCREAMING_SNAKE_CASE__ = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1 ):
sum_divs[k * i... | 100 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : List[str] = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxCon... | 615 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Union[str, Any] =logging.get_logger(__name__)
lowerCAmelCase__ : List[Any] ={
'BAAI/AltCLIP': 'https://huggingface.co/BA... | 101 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_... | 615 | 0 |
"""simple docstring"""
import numpy
class lowercase__ :
"""simple docstring"""
def __init__( self , _A , _A ):
'''simple docstring'''
UpperCamelCase : Dict = input_array
... | 102 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 | 0 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, 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 ... | 103 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaT... | 615 | 0 |
"""simple docstring"""
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTI... | 104 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 615 | 0 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_utils import... | 105 |
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase__ = np.zeros((n + 1,) )
lowerCAmelCase__ = ... | 615 | 0 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configur... | 106 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils ... | 107 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__a: Union[str, Any] = {'''configuration_swin''': ['''SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SwinConfig''', '''SwinOnnxConfig''']}
try:
if not is_torch_a... | 108 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 | 0 |
'''simple docstring'''
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_t... | 109 |
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
from t... | 615 | 0 |
from __future__ import annotations
from random import choice
def __lowerCamelCase ( __a :Optional[Any] ) -> Dict:
"""simple docstring"""
return choice(__lowerCAmelCase )
def __lowerCamelCase ( __a :Union[str, Any] ... | 176 |
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
__magic_name__ : Optional[int] = get_te... | 615 | 0 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
fro... | 479 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 0 |
def __lowerCAmelCase ( a__ ) -> Any:
__a = []
if len(__lowerCAmelCase ) == 1:
return [nums.copy()]
for _ in range(len(__lowerCAmelCase ) ):
__a = nums.pop(0 )
__a = permute(__lowerCAmelCase )
for... | 219 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
... | 444 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 0 |
"""simple docstring"""
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 lowerCamelCase_ ( ... | 357 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 | 0 |
import logging
from transformers.configuration_utils import PretrainedConfig
lowerCAmelCase__ = logging.getLogger(__name__)
class a__ ( _a ):
"""simple docstring"""
__lowerCamelCase = "masked_bert"
def __init__( self , lowercase=30522 , low... | 514 |
import logging
from transformers.configuration_utils import PretrainedConfig
__magic_name__ : Tuple = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
lowercase_ : Tuple = "masked_bert"
def __init__( self : List[Any] , _... | 615 | 0 |
'''simple docstring'''
import sys
_UpperCamelCase = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""125406987471585238630507156932909632952... | 459 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 615 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...s... | 539 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPC... | 615 | 0 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowerCamelCase :str = None
try:
import msvcrt
except ImportError:
lowerCamelCase :Dict = None
try:
import fcntl
except Impor... | 667 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase = {"""configuration_plbart""": ["""PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PLBartConf... | 492 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase = None ):
lowerCAmelCase__ = word_bank or []
# create a table
lowerCAmelCase__ = len(__lowerCAmelCase ) + 1
lowerCAmelCase__ = []
for _ in range(__lowerCA... | 615 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
_lowerCAmelCase : List[Any] = {
"""asapp/sew-tiny-100k""": """https://huggin... | 289 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 | 0 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, ... | 176 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__magic_name__ : List[Any] = logging.get_logger(__name__)
def a_ ( __lowerCAmelCase , __lowerCAmelC... | 615 | 0 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import Pa... | 479 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : List[str] = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxCon... | 615 | 0 |
import argparse
import os
import re
import packaging.version
A : int = """examples/"""
A : Any = {
"""examples""": (re.compile(R'^check_min_version\(\"[^\"]+\"\)\s*$', re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.compile(R'^__version__\s+=\s+\"([^\"]+... | 219 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_... | 615 | 0 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : List[Any] = 0
while num > 0:
digit_sum += num % 1_0
num //= 1_0
return digit_sum
... | 444 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 | 0 |
"""simple docstring"""
import os
from collections.abc import Iterator
def A_ ( __lowercase = "." ):
for dir_path, dir_names, filenames in os.walk(__lowerCAmelCase ):
UpperCamelCase_ : Dict =[d for d in dir_names if d != 'scripts' and d[0] not in '._']
for filename in filenames:
i... | 357 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaT... | 615 | 0 |
import numpy as np
lowerCAmelCase__ = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x""", """y""", """z"""],
]
class ... | 514 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 615 | 0 |
'''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,
)
if is_sentencepiece_av... | 459 |
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase__ = np.zeros((n + 1,) )
lowerCAmelCase__ = ... | 615 | 0 |
'''simple docstring'''
from manim import *
class __lowercase ( _a ):
def UpperCamelCase__ ( self ) -> int:
__a = Rectangle(height=0.5 , width=0.5 )
__a = Rectangle(height=0.46 , width=0.46 ).set_s... | 539 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 | 0 |
'''simple docstring'''
def a ( ):
'''simple docstring'''
for n in range(1 , 1_00_00_00 ):
yield n * (n + 1) // 2
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : Optional[Any] = 1
A_ : List[str] = 2
while ... | 667 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 | 0 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError("To use the rich extension, install rich with `pip install rich`")
| 492 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 | 0 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"The `inpainting.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionInpaintPipeline` instead."
)
| 289 |
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
from t... | 615 | 0 |
from __future__ import annotations
def __lowerCamelCase ( __a :str , __a :List[Any] = None ) -> Any:
"""simple docstring"""
A__ = word_bank or []
# create a table
A__ = len(__lowerCAmelCase ) + 1
A__ = []
f... | 176 |
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
__magic_name__ : Optional[int] = get_te... | 615 | 0 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a : str = {
"""facebook/mask2former-swin-small-coco-instance""": (
"""https://huggingface.co/facebook/mask2forme... | 479 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, require_... | 219 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 0 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
lowerCAmelCase : Optional[Any] = datasets.utils.loggin... | 444 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 0 |
"""simple docstring"""
from __future__ import annotations
__SCREAMING_SNAKE_CASE = list[tuple[int, int]]
__SCREAMING_SNAKE_CASE = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1... | 357 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipel... | 514 |
import logging
from transformers.configuration_utils import PretrainedConfig
__magic_name__ : Tuple = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
lowercase_ : Tuple = "masked_bert"
def __init__( self : List[Any] , _... | 615 | 0 |
'''simple docstring'''
from __future__ import annotations
def a_ ( _lowerCAmelCase ) -> Any:
__lowerCamelCase : str = 2
__lowerCamelCase : Optional[int] = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.a... | 459 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 615 | 0 |
'''simple docstring'''
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def SCREAMING_SNAKE_CASE ( a_ : Union[str, Any] ):
__a = [
'decoder.version',
'd... | 539 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPC... | 615 | 0 |
'''simple docstring'''
import sys
lowerCamelCase :List[str] = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""125406987471585238630507156932909632952... | 667 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 | 0 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
_UpperCamelCase = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input("Search: ")))
print("Googlin... | 492 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase = None ):
lowerCAmelCase__ = word_bank or []
# create a table
lowerCAmelCase__ = len(__lowerCAmelCase ) + 1
lowerCAmelCase__ = []
for _ in range(__lowerCA... | 615 | 0 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE__ : int ) -> Any:
'''simple docstring'''
_UpperCAmelCase : Union[str, Any] = len(__lowerCAmelCase )
_UpperCAmelCase : ... | 289 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | 176 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__magic_name__ : List[Any] = logging.get_logger(__name__)
def a_ ( __lowerCAmelCase , __lowerCAmelC... | 615 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversati... | 479 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : List[str] = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxCon... | 615 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.set_ve... | 219 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_... | 615 | 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, Vi... | 444 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 | 0 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def A_ ( __lowercase ):
UpperCamelCase_ : Any =prime_factors(__lowerCAmelCase )
if is_square_free(__lowerCAmelCase ):
return -1 if len(__lowerCAmelCase ) % 2 else 1
r... | 357 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaT... | 615 | 0 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs("""hub/hopper-medium-v2/unet/hor32""", exist_ok=True)
os.makedirs("""hub/hopper-medium-v2/unet/hor128""", exist_ok=True)
os.makedirs("""hub/hopper-medium-v2/value_function""", exist_ok=True)
def lowerCAmelCase__ ( ... | 514 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 615 | 0 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def a_ ( _lowerCAmelCase ) -> List[Any]:
__lowerCamelCase : Any = year % 19
__lowerCamelCase : Dict = year % 4
__lowerCamelCase : Any = year % 7
__low... | 459 |
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase__ = np.zeros((n + 1,) )
lowerCAmelCase__ = ... | 615 | 0 |
'''simple docstring'''
import warnings
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(__n... | 539 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 | 0 |
'''simple docstring'''
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
... | 667 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_UpperCamelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
_UpperCamelCase ... | 492 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 | 0 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def __snake_case ( SCREAMING_SNAKE_CASE__ : List[str] = "https://www.worldometers.info/coronavirus" ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase : Optional[int] = BeautifulS... | 289 |
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
from t... | 615 | 0 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import Ta... | 176 |
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
__magic_name__ : Optional[int] = get_te... | 615 | 0 |
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_utils import OnnxRuntimeMo... | 479 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 0 |
def __lowerCAmelCase ( a__ ) -> List[str]:
__a = ''''''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def __lowerCAmelCase ( a__ ) -> List[str]:
__a = ... | 219 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowercase (_A ):
"""simple docstring"""
if not nums:
return 0
_lowerCAmelCase : Any = nums[0]
_lowerCAmelCase ... | 444 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 0 |
"""simple docstring"""
from __future__ import annotations
__SCREAMING_SNAKE_CASE = list[list[int]]
# assigning initial values to the grid
__SCREAMING_SNAKE_CASE = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8... | 357 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Optional[int] = {
"""configuration_biogpt""": ["""BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BioGptConfig"""],
"""token... | 615 | 0 |
import copy
import re
class a__ :
"""simple docstring"""
__lowerCamelCase = "hp"
__lowerCamelCase = {}
__lowerCamelCase = None
@classmethod
def UpperCamelCase ( cls , lowercase , lowercase ) -> Tuple:
'''... | 514 |
import logging
from transformers.configuration_utils import PretrainedConfig
__magic_name__ : Tuple = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ (_a ):
lowercase_ : Tuple = "masked_bert"
def __init__( self : List[Any] , _... | 615 | 0 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_UpperCamelCase = logging.get_logger('transformers.models.speecht5')
def a_ ( _lowerCAmelCase ... | 459 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 615 | 0 |
'''simple docstring'''
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers... | 539 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPC... | 615 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=_a ):
__SCREAMING_SNAKE_CASE : Any = ["torch", "scipy"]
def __init__(self , *lowercase , **lowercase ):
requires_backends(self , ["""torch""", ""... | 667 |
from __future__ import annotations
def a_ ( __lowerCAmelCase ):
if not nums:
return 0
lowerCAmelCase__ = nums[0]
lowerCAmelCase__ = 0
for num in nums[1:]:
lowerCAmelCase__ , lowerCAmelCase__ = (
max_excluding + num,
... | 615 | 0 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pip... | 492 |
from __future__ import annotations
def a_ ( __lowerCAmelCase , __lowerCAmelCase = None ):
lowerCAmelCase__ = word_bank or []
# create a table
lowerCAmelCase__ = len(__lowerCAmelCase ) + 1
lowerCAmelCase__ = []
for _ in range(__lowerCA... | 615 | 0 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for te... | 289 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenize... | 615 | 0 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation impo... | 176 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__magic_name__ : List[Any] = logging.get_logger(__name__)
def a_ ( __lowerCAmelCase , __lowerCAmelC... | 615 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_a : Dict = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnx... | 479 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : List[str] = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M100OnnxCon... | 615 | 0 |
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
A : Tuple = logging.get_logger(__name__)
class __A( _a ):
def __init__( self , *_snake_case , **_snake_case ) -> List[str]:
... | 219 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__magic_name__ : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_... | 615 | 0 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowerCAmelCase : Any = get_logger(__name__)
class UpperCamelCase__ ( enum.Enum ):
"... | 444 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ : Optional[Any] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 615 | 0 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__SCREAMING_SNAKE_CASE = get_tests_... | 357 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaT... | 615 | 0 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Dict ) -> str:
'''simple docstring'''
A__ = 0.00
A__ = 0
for resistor in resistors:
if resistor <= 0:
A__ = F'Resistor a... | 514 |
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 615 | 0 |
'''simple docstring'''
def a_ ( _lowerCAmelCase = 4000000 ) -> str:
__lowerCamelCase : List[Any] = []
__lowerCamelCase ,__lowerCamelCase : Any = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__lowerCAmelCase )
__lowerCamelCa... | 459 |
import numpy as np
def a_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
lowerCAmelCase__ = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase__ = np.zeros((n + 1,) )
lowerCAmelCase__ = ... | 615 | 0 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def SCREAMING_SNAKE_CASE ( a_ : int ... | 539 |
from scipy.stats import pearsonr
import datasets
__magic_name__ : Union[str, Any] = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 615 | 0 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
A_ : Optional[int] = []
A_ : List[Any] = []
A_ : str = 0
A_ : Union[str, Any] = sum(__lowerCAmel... | 667 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 615 | 0 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {"""vocab_file""": """vocab.json""", ... | 492 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transform... | 615 | 0 |
"""simple docstring"""
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@re... | 289 |
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
from t... | 615 | 0 |
from __future__ import annotations
class A :
'''simple docstring'''
def __init__( self : Dict , __lowerCAmelCase : int ) -> Optional[Any]:
"""simple docstring"""
A__ = order
# a_{0} ... a_{k}... | 176 |
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
__magic_name__ : Optional[int] = get_te... | 615 | 0 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow_... | 479 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__magic_name__ : Any = TypeVar("""KEY""")
__magic_name__ : Dict = TypeVar("""VAL""")
@dataclass(frozen=_a , slots=_a )
class SCREAMI... | 615 | 0 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
A : int = False
try:
A : str = _is_package_... | 219 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaToken... | 615 | 0 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowerCAmelCase : Optional[int] = datasets.logging.get_logger(__name__)
lowerCA... | 444 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__magic_name__ : List[Any] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input... | 615 | 0 |
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