code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from transformers import AutoTok... | 463 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class _SCREAMING_SNAKE_CASE :
lowerCAmelCase__ = 42 # [batch_size x 3]
lowerCAmelCase__ = 42 # [batch_size x 3]
lowerCAmelCase__ = 42 # [batch_size x 3]
lowerCAmelCase__ = 42... | 463 | 1 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCamelCase (a_ :str = "isbn/0140328726") -> dict:
lowercase :List[Any] = olid.strip().strip('''/''') # Remove leading/trail... | 475 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import Base... | 475 | 1 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCamelCase__ ( unittest.TestCase):
"""simple docstring"""
a__ : Tuple = JukeboxTokenizer
a__ : Union[str, Any] = {
"artist": "Zac Brown Band",
... | 2 |
def SCREAMING_SNAKE_CASE_ ( _snake_case :bytes ) -> str:
return "".join([hex(_snake_case )[2:].zfill(2 ).upper() for byte in list(_snake_case )] )
def SCREAMING_SNAKE_CASE_ ( _snake_case :str ) -> bytes:
# Check data validity, following RFC3548
# https://... | 2 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> Dict:
"""simple docstring"""
stooge(SCREAMING_SNAKE_CASE_ ,0 ,len(SCREAMING_SNAKE_CASE_ ) - 1 )
return arr
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ) ... | 715 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("KEY")
lowerCamelCase__ = TypeVar("VAL")
@dataclass(frozen=_UpperCamelCase , slots=_UpperCamelCase )
class __SCR... | 51 | 0 |
"""simple docstring"""
from math import isqrt
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
return all(number % divisor != 0 for divisor in range(2 , isqrt(__UpperCamelCase ) + 1 ) )
def lowerCAmelCase ( __UpperCamelCase = 10**6 ):
''... | 65 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : Tuple ) ->Optional[Any]:
'''simple docstring'''
a : Any = []
a : List[str] = set({"(", "[", "{"} )
a : int = set({")", "]", "}"} ... | 633 | 0 |
"""simple docstring"""
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational i... | 544 |
"""simple docstring"""
lowerCAmelCase__ = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
lowe... | 544 | 1 |
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`")
| 124 |
def SCREAMING_SNAKE_CASE_ ( UpperCamelCase__ = 2_0_0_0_0_0_0 ):
UpperCamelCase__ : Dict = [0 for i in range(n + 1 )]
UpperCamelCase__ : Any = 1
UpperCamelCase__ : int = 1
for i in range(2 , int(n**0.5 ) + 1 ):
... | 285 | 0 |
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
__magic_name__ = get_tests_dir('''fixtures/spiec... | 314 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TimeSeriesTransformerC... | 314 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 430 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
"microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json... | 193 | 0 |
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
to_channel_dimensi... | 260 |
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, logging
__lower... | 260 | 1 |
'''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
@req... | 24 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class UpperCAmelCase__ :
def __init__( self : Any,__A : int=2,__A : Any=3,__A : Optional[int]=6_4,__A : ... | 44 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowerCamelCase = {'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}
try:
if not is_torch_availabl... | 112 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.hugg... | 112 | 1 |
from maths.prime_factors import prime_factors
def lowerCamelCase_(lowerCamelCase_ ) -> str:
if not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase = F'Input value of [number={number}] must be an integer'
raise TypeError(lowerCAmelCase__ ... | 323 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__SCREAMING_SNAKE_CASE = logging.getLogger(__name__)
class lowerCAmelCase__ :
"""simple... | 688 | 0 |
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
SCREAMING_SNAKE_CASE__ = 0
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, ... | 710 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prophe... | 688 | 0 |
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_up_block
... | 54 |
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property... | 54 | 1 |
def lowerCamelCase ( UpperCAmelCase_ : Optional[int] )-> List[str]:
"""simple docstring"""
a =len(UpperCAmelCase_ )
a =sum(UpperCAmelCase_ )
a =[[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 , ... | 321 |
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase_ : list[int] , UpperCAmelCase_ : int , UpperCAmelCase_ : int , UpperCAmelCase_ : int )-> None:
"""simple docstring"""
if (direction == 1 and array[indexa] > arra... | 321 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
... | 143 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase: List[Any] = logging.get_logger(__name__)
_lowercase: int = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}
class lowerCa... | 192 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class _SCREAMING_SNAKE_CASE :
def __init__( self : Any , __UpperCamelCase : int ) -> None:
"""simple docstring"""
snake_case__ : Optional[int] = ... | 574 |
'''simple docstring'''
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
_lowercase : List[Any] =TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow... | 574 | 1 |
from timeit import timeit
UpperCamelCase : Dict = {
"""MALAYALAM""": True,
"""String""": False,
"""rotor""": True,
"""level""": True,
"""A""": True,
"""BB""": True,
"""ABC""": False,
"""amanaplanacanalpanama""": True, # "a man a plan a canal panama"
}
# Ensure ou... | 37 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB... | 279 | 0 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a__ : List[str] ... | 702 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def A__ ( __lowerCamelCase ):
"""simple docstring"""
return np.maximum(0, __lowerCamelCase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 309 | 0 |
import heapq
def _UpperCamelCase ( lowercase__ ):
__SCREAMING_SNAKE_CASE : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Priority Queue
# heapq works with a min pr... | 696 | 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 import CORPUS_NAME,... | 271 | 0 |
def lowerCAmelCase_ ( snake_case_ ):
_A : Tuple = [int(snake_case_ ) for i in ip_va_address.split(""".""" ) if i.isdigit()]
return len(snake_case_ ) == 4 and all(0 <= int(snake_case_ ) <= 254 for octet in octets )
if __name__ == "__main__":
_snake_case = input(... | 54 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : List[str] = list(snake_case_ )
_A : List[Any] = list(snake_case_ )
_A : Tuple = 0
fo... | 54 | 1 |
def _a ( __UpperCamelCase : int ,__UpperCamelCase : int ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__UpperCamelCase ,int(b / 2 ) ) * actual_power(__UpperCamelCase ,int(b / 2 ) )
else:
return a * actual_power(__UpperCamelCase ... | 233 |
from math import log
from scipy.constants import Boltzmann, physical_constants
A__ : Optional[Any] = 3_0_0 # TEMPERATURE (unit = K)
def _a ( __UpperCamelCase : float ,__UpperCamelCase : float ,__UpperCamelCase : float ,):
if donor_conc <= 0:
raise Val... | 233 | 1 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_fu... | 704 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 129 | 0 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
lowerCAmelCase: List[Any] =logging.get_logger("transformers.models.speecht5")
def __snake_case ... | 607 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def __snake_case ( __A ) -> Any:
lowercase : List[str] = os.path.join(args.tf_model_dir ,"""para... | 607 | 1 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
blenderbot,
blend... | 715 |
import collections
import os
import re
from pathlib import Path
lowercase : int = """src/transformers"""
# Matches is_xxx_available()
lowercase : List[str] = re.compile(r"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowercase : str = re.compil... | 392 | 0 |
def lowerCamelCase__ ( _lowercase , _lowercase ):
'''simple docstring'''
if not (isinstance(_lowercase , _lowercase ) and isinstance(_lowercase , _lowercase )):
raise ValueError('''longest_common_substring() takes two strings for inputs''' )
UpperCAmelCase_ : ... | 30 |
'''simple docstring'''
import operator
def A__ ( __lowerCAmelCase : list , __lowerCAmelCase : bool = False , __lowerCAmelCase : list | None = None ):
lowerCamelCase__ = operator.lt if reverse else operator.gt
lowerCamelCase__ = solution o... | 50 | 0 |
'''simple docstring'''
from __future__ import annotations
def __A ( _SCREAMING_SNAKE_CASE : Optional[Any] , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : List[Any] ): # noq... | 564 |
'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def __A ( _SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
if not sentence:
return ""
__SCREAMING_SNAKE_CASE : str = dict(... | 564 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : list, __snake_case : list, __snake_case : int ) -> Any:
"""simple docstring"""
if len(_lowerCamelCase ) != len(_lowerCamelCase ):
raise ValueError("""The length of profit and wei... | 215 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowercase__ ... | 581 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configurati... | 719 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_m... | 183 | 0 |
def lowercase ( __A : str , __A : str ) -> bool:
'''simple docstring'''
snake_case : str = len(__A )
snake_case : Union[str, Any] = len(__A )
snake_case : Union[str, Any] = [[False for _ in range(m + 1 )] for _ in rang... | 36 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
... | 385 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
a : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class a ... | 593 |
'''simple docstring'''
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
a ... | 593 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
@flax.struct.dataclass... | 479 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_common impor... | 479 | 1 |
def __lowerCAmelCase ( __magic_name__ ):
_lowercase: Any = 0
while num > 0:
digit_sum += num % 1_0
num //= 1_0
return digit_sum
def __lowerCAmelCase ( __magic_name__ = 1_0_0 ):
_lowercase: Any = 1
_lowercase: Optional[int] = 2
for i in r... | 206 |
def __lowerCAmelCase ( __magic_name__ , __magic_name__ , __magic_name__ ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(__magic_name__ , n - 1 , __magic_name__ ) * a) % mod
else:
_lowercase: int = binary_exponentiation(__magic_n... | 206 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effe... | 50 |
"""simple docstring"""
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenize... | 255 | 0 |
import os
def A_ ( a = "matrix.txt" ):
"""simple docstring"""
with open(os.path.join(os.path.dirname(a ) , a ) ) as in_file:
SCREAMING_SNAKE_CASE_ : Optional[int] = in_file.read()
SCREAMING_SNAKE_CASE_ : List[str] = [[int(a )... | 702 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCAmelCase : Dict = logging.get_logger(__name__)
lowe... | 353 | 0 |
'''simple docstring'''
def a__ ( lowercase : int = 1, lowercase : int = 1000 ) -> int:
"""simple docstring"""
_UpperCamelCase = 1
_UpperCamelCase = 0
for divide_by_number in range(lowercase, digit + 1 ):
_UpperCam... | 98 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
... | 353 | 0 |
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class _lowerCamelCase ( UpperCamelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ = '''MCTCTFeatureExtractor'''
SCREAMING_SNAKE_CASE_ = '''AutoTokenizer'''
... | 705 |
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
lowerCamelCase =logging.get_logger(__name__) # pylint: disable=invalid-name
def SCREAMING_SNAKE_CASE_ ( U... | 462 | 0 |
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
__A : Optional[Any] = logging.get_logger(__name__)
__A : List[Any] ... | 130 |
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class A_ (a_ ):
UpperCAmelCase__ = None
UpperCAmelCa... | 130 | 1 |
"""simple docstring"""
def _lowerCAmelCase(a : str ) -> str:
_SCREAMING_SNAKE_CASE =0
# if input_string is "aba" than new_input_string become "a|b|a"
_SCREAMING_SNAKE_CASE =''''''
_SCREAMING_SNAKE_CASE =''''''
# append each character + "|" in new_string ... | 165 |
"""simple docstring"""
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
UpperCAmelCase_ : Tuple = coll... | 165 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_ba... | 52 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __UpperCAmelCase ( snake_case_ : str = "isbn/0140328726" ) -> dict:
"""simple docstring"""
_lowerCAmelCase = olid.strip().str... | 156 | 0 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@requi... | 243 |
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STA... | 243 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available... | 407 |
'''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBe... | 407 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def snake_case_ (UpperCamelCase : str ):
'''simple docstring'''
_a , _a = analyze_text(UpperCamelCase ... | 377 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
_snake_case : List[str] = '\nimport os\n'
_snake_case : Dict = '\ndef foo():\n import os\n return False\n'
_snake_case : List[Any] =... | 377 | 1 |
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_available, is_vision_availabl... | 105 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mo... | 450 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ = 2_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = [0 for i in range(n + 1 )]
UpperCAmelCase = 1
UpperCAmelCase = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
for j in ... | 627 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 1 |
# 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
#
# Unless re... | 475 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class lowercase__ ( uni... | 475 | 1 |
from __future__ import annotations
def _lowerCAmelCase( __A ): # This function is recursive
UpperCAmelCase = len(__snake_case )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if array_length <= 1:
return array
# Else
UpperCAmelCas... | 711 |
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
from accelerate import Acceler... | 1 | 0 |
'''simple docstring'''
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 impo... | 370 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowercase = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfi... | 370 | 1 |
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from transformers import (
... | 193 |
from __future__ import annotations
def lowerCamelCase__ ( _a , _a):
if b == 0:
return (1, 0)
((SCREAMING_SNAKE_CASE) ,(SCREAMING_SNAKE_CASE)) : Tuple = extended_euclid(_a , a % b)
SCREAMING_SNAKE_CASE : Dict = a // b
return (y, x - k * y)
def ... | 193 | 1 |
'''simple docstring'''
def lowerCamelCase (_SCREAMING_SNAKE_CASE : str ):
__a : Dict = [0] * len(_SCREAMING_SNAKE_CASE )
for i in range(1 , len(_SCREAMING_SNAKE_CASE ) ):
# use last results for better performance - dynamic programming
__a : Any ... | 476 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def lowerCamelCase (_SCREAMING_SNAKE_CASE : int = 3 ):
if isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
raise TypeE... | 476 | 1 |
"""simple docstring"""
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common imp... | 717 |
"""simple docstring"""
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMix... | 556 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : Dict = {
"""disti... | 87 | """simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_para... | 656 | 0 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, Traini... | 710 | from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class __snake_case ( __lowerCAmelCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : Optional[Any] ... | 15 | 0 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from... | 343 |
import sys
UpperCamelCase = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098711121... | 66 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a : str = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if no... | 700 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
__a : int = logging.get_logger(__name__)
__a... | 298 | 0 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def lowerCamelCase_ ( __UpperCamelCase : Optio... | 292 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase_ ( __UpperCamelCase : list , __UpperCamelCase : int | None = None , __UpperCamelCase : int | None = None ) -> None:
"""simple docstring"""
if start i... | 292 | 1 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowercase__ =datasets.load_iris()
lowercase__ =np.array(data['data'])
lowercase__ =np.array(data['target'])
lowercase__ ... | 719 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def UpperCamelCase_ ( A__ ):
# getting number of pixels in the image
a_ , a_ = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
for i in range(A__ ):
for j in range(A_... | 511 | 0 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : List[Any] ):
lowerCAmelCase = args.pruning_method
lowerCAmelCase = args.thresho... | 4 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 317 | 0 |
'''simple docstring'''
from __future__ import annotations
import time
import numpy as np
A_ : Dict =[8, 5, 9, 7]
A_ : List[Any] =[
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
A_ : str =[
[3, 2, 1, 4],
... | 606 | '''simple docstring'''
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
A_ : List[str] =logging.get_logger(__name__)
def snake_case_ ( __snake_case : int) -> in... | 606 | 1 |
"""simple docstring"""
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from ... | 19 |
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 import (
Fla... | 105 | 0 |
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
require_torch... | 718 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : Union[str, Any] = {
"configuration_ber... | 364 | 0 |
"""simple docstring"""
from timeit import timeit
lowerCAmelCase = {
"""MALAYALAM""": True,
"""String""": False,
"""rotor""": True,
"""level""": True,
"""A""": True,
"""BB""": True,
"""ABC""": False,
"""amanaplanacanalpanama""": True, # "a man a plan a canal pan... | 174 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestM... | 174 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
_UpperCAmelCase... | 713 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
_UpperCAmelCase : str = {
"""configuration_gpt_neox_japanese""": ["""GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MA... | 474 | 0 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class __A (... | 78 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 343 | 0 |
import colorsys
from PIL import Image # type: ignore
def _SCREAMING_SNAKE_CASE ( snake_case_ : float , snake_case_ : float , snake_case_ : int ):
__magic_name__ = x
__magic_name__ = y
for step in range(snake_case_ ): # noqa: B007
__magic_name__ ... | 701 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvailable()
exce... | 678 | 0 |
"""simple docstring"""
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class UpperCamelCase_ (__A ):
__magic_name__ = ''''''
__magic_name__ = (
None # protocol passe... | 95 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : Optional[int] = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : int = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.j... | 226 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase : Union[str, Any] = {
"configuration_rag": ["RagConfig"],
"retrieval_rag": ["RagRetriever"],
"tokenization_rag": ["RagTokenizer"],
}
... | 713 |
def snake_case__ ( lowerCamelCase_ , lowerCamelCase_ ):
return x if y == 0 else greatest_common_divisor(lowerCamelCase_ , x % y )
def snake_case__ ( lowerCamelCase_ , lowerCamelCase_ ):
return (x * y) // greatest_common_divisor(lowerCa... | 423 | 0 |
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMix... | 70 |
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.schedulers.scheduling_ddpm ... | 147 | 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
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_... | 201 |
'''simple docstring'''
def __lowercase ( __SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 201 | 1 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__lowerCamelCase = ... | 608 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : str = logging.get_logger(__name__)
A_ : List[str] = {
"google/canine-s": "https://huggingface.co/google/canine-s/resolve/main/config.json",
# See all CANINE models... | 696 |
"""simple docstring"""
A_ : List[str] = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
"datacla... | 696 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"""facebook/s2t-wav2vec2-large-en-de""": (
"""https://huggingface.co/facebook/s2t-wav2vec2-large-... | 92 |
from __future__ import annotations
from typing import TypedDict
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
__snake_case = 42
__snake_case = 42
def lowerCamelCase__ (__lowerCamelCase ):
if not isinst... | 249 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=A )
class lowerCamelCase__ ( A ):
'''simple docstring'''
A_ = field(defaul... | 4 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available()... | 4 | 1 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def _lowercase( __a : List[Any] ):
a__ ... | 20 |
# 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... | 419 | 0 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCamelCase__ ( _lowercase , _lowercase = True , _lowercase = math.inf , _lowercase = -math.inf , _lowercase = math.inf , _lowercase = -math.inf , _lowercase = Fa... | 720 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def lowerCamelCase__ ( _lowercase ):
'''simple docstring'''
... | 300 | 0 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class A__... | 154 |
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torch_neuroncore,
... | 154 | 1 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test... | 302 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class _UpperCAmelCase :
'''simple docstring'''
lowercase_ : int
lowercase_ : int
class _Uppe... | 302 | 1 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common imp... | 476 |
'''simple docstring'''
import math
_lowerCAmelCase = 10
_lowerCAmelCase = 7
_lowerCAmelCase = BALLS_PER_COLOUR * NUM_COLOURS
def UpperCamelCase ( a = 20 ) -> str:
'''simple docstring'''
__magic_name__ = math.comb(a , a )
... | 432 | 0 |
'''simple docstring'''
__snake_case : List[Any] = 256
# Modulus to hash a string
__snake_case : str = 1_000_003
def _UpperCAmelCase ( _UpperCamelCase : str, _UpperCamelCase : str ) -> bool:
A_ = len(_UpperCamelCase )
... | 174 | '''simple docstring'''
from itertools import product
def _UpperCAmelCase ( _UpperCamelCase : int, _UpperCamelCase : int ) -> list[int]:
A_ = sides_number
A_ = max_face_number * dice_number
A_ = [0] * (max_total + 1)
... | 174 | 1 |
import json
import sys
def UpperCamelCase ( snake_case__ : Optional[Any] , snake_case__ : Dict ) -> Dict:
with open(snake_case__ , encoding='utf-8' ) as f:
UpperCamelCase : Optional[Any] = json.load(snake_case__ )
UpperCamelCase ... | 40 | from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTester
... | 305 | 0 |
def __lowerCAmelCase ( _UpperCamelCase : int = 2_00_00_00 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = [0 for i in range(n + 1 )]
SCREAMING_SNAKE_CASE = 1
SCREAMING_SNAKE_CASE = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_list[i... | 673 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
a_ : List[str] = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import word_tokenize
a_ : Di... | 673 | 1 |
from math import isqrt
def __A ( _lowercase ):
'''simple docstring'''
_A = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , _lowercase , _lowerc... | 484 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else... | 484 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
UpperCamelCase = {
"""configuration_audio_spectrogram_transformer""": [
"""AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 707 |
"""simple docstring"""
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from p... | 612 | 0 |
def UpperCamelCase_( __magic_name__ : int = 10**12 ):
"""simple docstring"""
_lowerCAmelCase :Union[str, Any] = 1
_lowerCAmelCase :str = 0
_lowerCAmelCase :List[str] = 1
_lowerCAmelCase :Any = 1
... | 687 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
a = """\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},
title = {BLEU: a Method for Automatic Eva... | 687 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding... | 40 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vis... | 40 | 1 |
def SCREAMING_SNAKE_CASE_ ( lowerCAmelCase_: int = 3 , lowerCAmelCase_: int = 7 , lowerCAmelCase_: int = 1_0_0_0_0_0_0 ):
snake_case_ : Optional[Any] = 0
snake_case_ : int = 1
for current_denominator in range(1 , limit + 1 ):
... | 666 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestM... | 292 | 0 |
'''simple docstring'''
import math
def lowerCAmelCase (__A):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are ... | 708 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils im... | 352 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__lowerCAmelCase : Optional[int] = {"tokenization_wav2vec2_phoneme": ["Wav2Vec2PhonemeCTCTokenizer"]}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
__... | 509 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_utils import FeatureE... | 509 | 1 |
'''simple docstring'''
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
__snake_case : List[str] = datasets.utils.logging.get_logger(__name__)
class A ( folder_based_builder.FolderBased... | 691 |
'''simple docstring'''
# 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
#
... | 691 | 1 |
def lowerCAmelCase_ ( A_):
UpperCamelCase__: Union[str, Any] = len(A_)
for i in range(A_):
for j in range(i + 1 ,A_):
if numbers[j] < numbers[i]:
UpperCamelCase__ , UpperCamelCase__: List[str] = numbers[j], numbers[i]
retu... | 380 |
def lowerCAmelCase_ ( A_):
if not all(char in "01" for char in bin_string):
raise ValueError("Non-binary value was passed to the function")
if not bin_string:
raise ValueError("Empty string was passed to the function")
UpperCamelCase__: List[Any] = ""
... | 380 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {
"""configuration_clipseg""": [
"""CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""CLIPSegConfig""",
"""CLIPSegTextConfig""",
... | 601 |
from __future__ import annotations
from statistics import mean
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: list[int] , __lowerCamelCase: list[int] , __lowerCamelCase: int ):
'''simple docstring'''
lowercase_ = [0] * no_of_processes
lowercase_ = [0] * no_of_proce... | 601 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
a_ ... | 76 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A = {
'configuration_blenderbot_small': [
... | 438 | '''simple docstring'''
import math
import os
import sys
def _UpperCamelCase ( SCREAMING_SNAKE_CASE_ ):
lowercase_ : List[str] = ''
try:
with open(SCREAMING_SNAKE_CASE_ , 'rb' ) as binary_file:
lowercase_ : Di... | 438 | 1 |
import qiskit
def UpperCAmelCase ( a_ , a_ ) -> qiskit.result.counts.Counts:
"""simple docstring"""
__A = qiskit.Aer.get_backend("aer_simulator" )
# Create a Quantum Circuit acting on the q register
__A = qiskit.QuantumCircuit(a_ , a_ ... | 55 |
from __future__ import annotations
def a__ ( A_, A_, A_, A_ ):
'''simple docstring'''
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[indexa] < array[indexa]
):
__magic_name__ , __magic_name__ = array[indexa], a... | 529 | 0 |
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def __lowerCAmelCase (SCREAMING_SNAKE_CASE=... | 714 |
def __lowerCAmelCase (SCREAMING_SNAKE_CASE = 6008_5147_5143 )-> int:
"""simple docstring"""
try:
snake_case_ = int(SCREAMING_SNAKE_CASE )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
... | 531 | 0 |
"""simple docstring"""
def UpperCamelCase ( _lowerCAmelCase : str, _lowerCAmelCase : str = " " ) -> list:
_UpperCAmelCase : Optional[int] = []
_UpperCAmelCase : Dict = 0
for index, char in enumerate(_lowerCAmelCase )... | 238 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
def UpperCamelCase ( _lowerCAmelCase : int, _lowerCAmelCase : int ) -> bool:
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
... | 238 | 1 |
from __future__ import annotations
class __lowercase :
def __init__( self , lowercase_) -> None:
__snake_case = data
__snake_case = None
__snake_case = None
def A ( snake_case__ : ... | 702 |
from __future__ import annotations
UpperCAmelCase__ : Dict = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def A ( snake_case__ : list[list[int]] , snake_case__ : list[int] , snake_case__ : list[in... | 676 | 0 |
def __snake_case ( _UpperCamelCase , _UpperCamelCase ) -> int:
while b:
_a , _a = b, a % b
return a
def __snake_case ( _UpperCamelCase , _UpperCamelCase ) -> int:
return a if b == 0 else euclidean_gcd_recursive(_UpperCamelCase , a % b )
... | 487 |
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def __snake_case ( _UpperCamelCase ) -> Optional[Any]:
_a = [
'''encoder.version''',
'''decoder.version''',
'''model.encoder.version''',
... | 487 | 1 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
_lowercase = logging.g... | 162 |
'''simple docstring'''
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowercase = 300 # TEMPERATURE (unit = K)
def A (__lowerCamelCase :float , __lowerCamelCase :float , __lowerCamelCase :float , ):
if donor_conc <= 0:
raise V... | 162 | 1 |
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