code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase (... | 266 |
"""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():
imp... | 266 | 1 |
"""simple docstring"""
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def lowerCAmel... | 85 | """simple docstring"""
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowerCAmelCase (__UpperCamelCase : dict , __UpperCamelCase : str , __UpperCamelCase : set , __UpperCamelCase : set , __UpperCamelCase : dict , __UpperCamelCase ... | 85 | 1 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 50 ) -> Dict:
_lowerCAmelCase : Dict = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 ,5 ):
for tile_start in range... | 44 |
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
UpperCAmelCase : Union[str, Any] = datasets.utils.logging.get_logger(__name__)
@dataclass
class __low... | 252 | 0 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
__A = version.parse(version.parse(torch.__version__).base_ve... | 360 |
from ..utils import DummyObject, requires_backends
class _SCREAMING_SNAKE_CASE ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = ["torch", "torchsde"]
def __init__(self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCas... | 273 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
... | 206 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
lowerCamelCase : Any = logging.get_... | 124 | 0 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTeste... | 366 |
lowerCamelCase : Optional[int] ={
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],
'''G''': ['''C'''],
}
... | 196 | 0 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase : Tuple = logging.get_logger(... | 218 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : Union[str, Any] = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class __magic_name__ ( lo... | 218 | 1 |
'''simple docstring'''
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowerCamelCase : Union[str, Any] = 300 # TEMPERATURE (unit = K)
def __lowerCamelCase ( A__ , A__ , A__ , ) -> float:
... | 249 |
'''simple docstring'''
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE ( _a ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = (UnCLIPScheduler,)
def A ( ... | 249 | 1 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase=0.2 , _lowerCamelCase=0.2 ):
a :T... | 94 |
UpperCAmelCase__ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',... | 5 | 0 |
'''simple docstring'''
def __snake_case( _lowerCAmelCase ) -> tuple[int, int]:
try:
snake_case__ : Any = float(_lowerCAmelCase )
except ValueError:
raise ValueError("""Please enter a valid number""" )
snake_case__ : int = deci... | 43 |
'''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
if is_torch... | 43 | 1 |
"""simple docstring"""
def _snake_case ( UpperCamelCase : List[Any] , UpperCamelCase : Any ):
return int((input_a, input_a).count(1 ) != 0 )
def _snake_case ( ):
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
assert or_gate(... | 109 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase__ : List[str] = logging.get_logger(__name__)
UpperCAmelCase__ : Union[str, Any] = {
'xl... | 121 | 0 |
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassification,
MobileViTVaForSe... | 354 |
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
lowerCamelCase_ = logging.get_logger(__name__)
def __magic_name__ ( __a : Optional[int] ):
'''simple docstring'''
... | 178 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase ( UpperCAmelCase ) -> list[int]:
if num <= 0:
snake_case_ = f'{num}: Invalid input, please enter a positive integer.'
raise ValueError(UpperCAmelCase )
... | 69 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class lowerCAmelCase__ :
def __init__( self : Union[str, Any] ) ->Union[str, Any]:
'''simple docstring'''
... | 234 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
cl... | 353 |
"""simple docstring"""
from typing import Any
def _snake_case ( lowercase__ ):
if not input_list:
return []
_lowerCamelCase : Any = [input_list.count(lowercase__ ) for value in input_list]
_lowerCamelCase : Dict = max... | 12 | 0 |
'''simple docstring'''
_SCREAMING_SNAKE_CASE : 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.... | 85 |
'''simple docstring'''
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
_SCREAMING_SNAKE_CASE : Optional[int] = argparse.ArgumentParser()
parser.add_a... | 85 | 1 |
def _lowerCamelCase( lowercase__ ) -> str:
'''simple docstring'''
__lowercase= 0
# if input_string is "aba" than new_input_string become "a|b|a"
__lowercase= ''
__lowercase= ''
# append each character + "|" in new_string for range(0, length-1)
for i in input_s... | 304 |
from math import factorial, radians
def _lowerCamelCase( lowercase__ , lowercase__ = 1_8 , lowercase__ = 1_0 ) -> float:
'''simple docstring'''
__lowercase= angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from degrees to radians
__l... | 304 | 1 |
def a__ ( A_, A_ ):
'''simple docstring'''
if digit_amount > 0:
return round(number - int(A_ ), A_ )
return number - int(A_ )
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolate(35.345, 1))
print(deci... | 88 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import ConfigTester... | 273 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase : Dict = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitPr... | 186 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_... | 186 | 1 |
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.utils.testing_utils import... | 278 |
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
__lowerCAmelCase = logging.get_logger(__name__)
def snake_case_ ( snake_case , snake_ca... | 196 | 0 |
from timeit import timeit
def SCREAMING_SNAKE_CASE__( _UpperCamelCase : int ) -> Union[str, Any]:
'''simple docstring'''
if number < 0:
raise ValueError("the value of input must not be negative" )
UpperCamelCase__ = 0
while number:
... | 370 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__( _UpperCamelCase : Dict , _UpperCamelCase : str , _UpperCamelCase : Optional[int] , _UpperCamelCase : str ) -> Dict: # noqa: E741
'''simple docstri... | 31 | 0 |
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome is truly tiny -
# all files ~60KB. A... | 307 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : int = logging.get_logger(__name__)
__UpperCamelCase : List[Any] = {
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface.co/tanreinama... | 307 | 1 |
"""simple docstring"""
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
snake_case__ : int = '''src/transformers'''
# This is to make su... | 314 |
"""simple docstring"""
def _snake_case ( _snake_case : int = 50000000 ):
lowerCAmelCase : List[str] = set()
lowerCAmelCase : List[Any] = int((limit - 24) ** (1 / 2) )
lowerCAmelCase : Optional[int] = set(range(3 , prime_square_limit + 1 , ... | 314 | 1 |
# 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 applicabl... | 43 | 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
__lowercase = logging.get_logger(__name__)
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase ... | 43 | 1 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def lowerCamelCase_ ( lowerCAmelCase: str , lowerCAmelCase: complex , lowerCAmelCase: str = "x" , lowerCAmelCase: float = 10**-10 , lowerCAmelCase: int = 1 , )... | 260 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
lowerCAmelCase_ = logging.getLogger()
@unittest.skip("""Temporarily disable the doc tests.""" ... | 260 | 1 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print("Program to check whether a number is a Perfect number or n... | 23 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCamelCase_ ( ... | 178 | 0 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
A_ : List[Any] = 6_3_7_8_1_3_7.0
A_ : Dict = 6_3_5_6_7_5_2.3_1_4_2_4_5
A_ : int = 6_3_7_8_1_3_7
def ... | 360 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
de... | 349 | 0 |
import argparse
import json
import os
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
from accelerate import Acce... | 13 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'VisionEncoderDecoderOnnxConfi... | 12 | 0 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_... | 93 |
# 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 require... | 93 | 1 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokeni... | 304 |
'''simple docstring'''
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent you shou... | 304 | 1 |
def _a ( a :list ) -> list:
if len(a ) <= 1:
return lst
a = 1
while i < len(a ):
if lst[i - 1] <= lst[i]:
i += 1
else:
a , a = lst[i], lst[i - 1]
i -= 1
if i == 0:
a = 1
return lst
if __name__ == "__main_... | 26 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase_ ( lowercase ):
'''simple docstring'''
__snake_case = ['''image_processor''', '''tokenizer''']
__... | 26 | 1 |
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.huggingface import Huggin... | 186 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE_GEN... | 186 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
... | 242 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_a... | 242 | 1 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {'''vocab_... | 108 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__SCREAMING_SNAKE_CASE : Optional[int] = {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCH... | 31 | 0 |
def SCREAMING_SNAKE_CASE_ ( __A : list[int] ) -> list[int]:
"""simple docstring"""
a_ : List[str] = len(__A )
for i in range(__A ):
for j in range(i + 1 , __A ):
if numbers[j] < numbers[i]:
... | 120 |
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
UpperCAmelCase_ : str = 1.054571817e-34 # unit of ℏ : J * s
UpperCAmelCase_ : Dict = 3e8 # unit of c : m * s^-1
def SCR... | 120 | 1 |
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
_SCREAMING_SNAKE_CASE : Dict = '''src/transformers'''
# This is to make sure the transformers module i... | 314 |
from __future__ import annotations
def UpperCAmelCase_ ( _A , _A = None ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = word_bank or []
# create a table
SCREAMING_SNAKE_CASE__ = len(_A ) + 1
SCREAMING_SNAKE_CASE__ = []
for _ in range(... | 314 | 1 |
"""simple docstring"""
def _snake_case ( lowerCamelCase__ : list[list[int]] , lowerCamelCase__ : int , lowerCamelCase__ : int , lowerCamelCase__ : list[int] ) -> bool:
# 1. Validate that path exists between current and next vertices
... | 209 |
"""simple docstring"""
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
A__ : int = {
'n_samples': 64,
'horizon': 32,
'num_inference_steps': 20,
'n_guide_steps': 2, # can set to 0 for faster sampling, does not use value network
's... | 209 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCAmelCase : List[Any] = logging.get_logger(__name__) # pylint: disable=invalid-name
class __lowercase ( a_... | 252 |
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 ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 252 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
UpperCamelCase__ = ... | 102 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
UpperCamelCase__ = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path""", default=None, type=str, required=True, ... | 102 | 1 |
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load_metric
from .utils imp... | 36 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcessor, BlipImagePr... | 273 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def lowerCAmelCase_ ( __a , __a , __a ) -> List[str]:
"""simple docstring"""
lowerCamelCase__: int =("dense.weight", "attention.self.query"... | 273 | 1 |
'''simple docstring'''
def snake_case_ ( __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : list[str] ):
"""simple docstring"""
lowercase_ : List[str] = ''''''
for word_or_phrase in separated:
... | 93 |
'''simple docstring'''
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class lowerCAmelCase__ :
lowerCAmelCase_ = None
def _snake_case ( self ):
"""simple docst... | 93 | 1 |
"""simple docstring"""
import re
def lowerCamelCase_( _lowerCamelCase ) -> str:
'''simple docstring'''
if len(re.findall("[ATCG]" , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError("Invalid Strand" )
return dna.translate(dna.maketrans("ATCG... | 361 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> float:
'''simple docstring'''
_validate_point(_lowerCamelCase )
_validate_point(_lowerCamelCase )
if len(_lowerCamelCase ) != len(_lowerCamelCase ):
raise ValueError("Both poin... | 340 | 0 |
from __future__ import annotations
import typing
from collections import Counter
def lowerCAmelCase_ ( snake_case_ ):
_A : typing.Counter[int] = Counter()
for base in range(1,max_perimeter + 1 ):
for perpendicular in range(snake_case_,max_perimeter +... | 26 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
_snake_case = logging.get_logger(__name__)
_snake_case = [
["attention", "attn"],
["encoder_atten... | 26 | 1 |
'''simple docstring'''
from typing import Union
import fire
import torch
from tqdm import tqdm
def UpperCAmelCase_ ( __lowercase : str , __lowercase : str = "cpu" , __lowercase : Union[str, None] = None ) -> None:
'''simple docstring'''
... | 156 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class A_ ( lowerCAmelCase_ ):
_lowerCamelCase : str
_lowerCamelCase : int
def UpperCAmelCase_ ( __lowercase : str ) -> list[str]:
'''simple docstring'''
i... | 156 | 1 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipel... | 242 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax... | 242 | 1 |
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionScheduler
from ...utils i... | 323 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import... | 323 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_sing... | 120 |
'''simple docstring'''
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class __snake_case ( _SCREAMING_SNAKE_CASE):
"""simple docstring"""
lowercase = (IPNDMSchedul... | 120 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : Tuple , __UpperCAmelCase : List[str] ) -> List[Any]:
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
SCREAMING_SNAKE_CASE_ = (boundary[1] - boundary[0]) / steps
SCREAM... | 210 |
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_vision, slow, torch_device
from transfo... | 210 | 1 |
_a = 65_521
def lowerCAmelCase__(__snake_case ) -> int:
'''simple docstring'''
lowerCamelCase__ = 1
lowerCamelCase__ = 0
for plain_chr in plain_text:
lowerCamelCase__ = (a + ord(__snake_case )) % MOD_ADLER
lowerCamelCase__ = ... | 209 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __A ( lowerCAmelCase ):
'''simple docstring'''
lowerCAmelCase_ = """Speech2TextFeatureExtractor"""
lowerCAmelCase_ = """Speech2TextTokenizer... | 209 | 1 |
'''simple docstring'''
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPText... | 240 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
S... | 240 | 1 |
"""simple docstring"""
def lowercase ( _snake_case : int ) ->list:
"""simple docstring"""
if bit_count < 0:
raise ValueError('''The given input must be positive''' )
# get the generated string sequence
__snake_case : int = gray_code_sequence_string(_snake_ca... | 102 |
"""simple docstring"""
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER... | 102 | 1 |
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __lowerCamelCase ( __a :np.ndarray , __a :np.ndarray ) -> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b , 2 ... | 276 |
# 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 r... | 276 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Any = logging.get_logger(__name__)
a__ : int = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main... | 349 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_ten... | 349 | 1 |
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE (metaclass=UpperCAmelCase ):
_UpperCamelCase : str = ['torch', 'torchsde']
def __init__( self : List[Any] , *a : Any , **a : Any )-> Union[str, Any]... | 269 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {"""... | 269 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def A_ ( _lowercase ):
'''simple docstring'''
... | 66 |
"""simple docstring"""
def lowercase__ ( _UpperCAmelCase , _UpperCAmelCase ) -> bool:
'''simple docstring'''
lowercase : Optional[int] = len(_UpperCAmelCase ) + 1
lowercase : Any = len(_UpperCAmelCase ) + 1
# dp i... | 255 | 0 |
import numpy as np
from transformers import Pipeline
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase ) -> int:
lowerCamelCase__ : List[str] = np.max(a__ , axis=-1 , keepdims=a__ )
lowerCamelCase__ : int = np.exp(outputs - maxes )
return shifted_exp ... | 370 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class lowerCAmelCase ( pl.LightningModule ):
def __init__( self : List[str] , UpperCAmelCase : Optional[Any] ) ... | 45 | 0 |
import datasets
__lowerCAmelCase : Optional[int] = "\\n@InProceedings{conneau2018xnli,\n author = \"Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n and Schwenk,... | 156 |
def UpperCAmelCase_ ( __lowerCAmelCase ) -> int:
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
__lowercase : List[str] = 0
while number:
# This way we arrive at n... | 156 | 1 |
def _a ( lowerCamelCase: int = 1_00 ) -> int:
'''simple docstring'''
__A = 0
__A = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints*... | 368 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
snake_case__ : Tuple = {
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_C... | 250 | 0 |
'''simple docstring'''
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDif... | 323 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = (CMStochasticIterativeScheduler,)
SC... | 323 | 1 |
from __future__ import annotations
from typing import Any
def _snake_case( SCREAMING_SNAKE_CASE__ : list ) -> int:
'''simple docstring'''
if not postfix_notation:
return 0
A__ = {'+', '-', '*', '/'}
A__ = [... | 282 |
def _snake_case( SCREAMING_SNAKE_CASE__ : int = 1000 ) -> int:
'''simple docstring'''
A__ = 3
A__ = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
res... | 282 | 1 |
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 : List[Any] = logging.get_logger(__name__)
__a : Optional[int] = {
"""hustvl/y... | 210 | import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
__a : List[Any] = logging.getLogger(__name__)
def UpperCAmelCase ( ):
"""simple docstring"""
__lowercase = argparse.ArgumentParser(
... | 210 | 1 |
import os
import sys
import unittest
__UpperCAmelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dum... | 352 |
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionSchedu... | 145 | 0 |
"""simple docstring"""
from PIL import Image
def _snake_case ( lowercase__ : Image , lowercase__ : float ) -> Image:
'''simple docstring'''
def brightness(lowercase__ : int ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if n... | 84 |
'''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
lowerCAmelCase : Dict ... | 223 | 0 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
snake_case_ = HUGGINGFACE_HUB_CACHE
snake_case_ = """config.json"""
snake_case_ = """diffusion_pytorch_model.bin"""
snake_case_ = """diffusion_flax_mode... | 181 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
snake_case_ = None
try:
import msvcrt
except ImportError:
snake_case_ = None
try:
import fcntl
except ImportError:
snake_case_... | 181 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
snake_case : str = {
"configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Wav2Vec2Config"],... | 94 |
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class __lowerCAmelCase ( datasets.BuilderConfig):
_a = None
class __lowerCAmel... | 236 | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test... | 368 |
'''simple docstring'''
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'vocab_file': 'vocab.json',
'merg... | 222 | 0 |
'''simple docstring'''
import argparse
import json
import subprocess
def _A ( snake_case , snake_case ) -> Tuple:
_lowercase : int = []
_lowercase : Union[str, Any] = (
F'''curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {... | 250 |
'''simple docstring'''
import argparse
import os
import re
_snake_case = 'src/transformers'
# Pattern that looks at the indentation in a line.
_snake_case = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_snake_case = re.compile(r'^\s*"([^"]+)":')
# Pattern that m... | 250 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
... | 43 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load... | 43 | 1 |
"""simple docstring"""
def __lowerCAmelCase (_UpperCamelCase = 1000 ):
__lowerCAmelCase , __lowerCAmelCase : Optional[int] = 1, 1
__lowerCAmelCase : int = 2
while True:
__lowerCAmelCase : Optional[int] = 0
__lowerCAmelCase : L... | 86 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowercase ( lowerCAmelCase__ : Namespace ) -> Tuple:
return ConvertCommand(
args.model_type , args.tf_checkpoint ... | 45 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers... | 358 |
'''simple docstring'''
import pytest
lowerCAmelCase_ = "__dummy_dataset1__"
lowerCAmelCase_ = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", ... | 332 | 0 |
'''simple docstring'''
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
_lowerCamelCase : ... | 28 |
'''simple docstring'''
from math import factorial
def _A ( snake_case , snake_case ) -> int:
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Please ... | 250 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_i... | 48 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
l... | 48 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
if is_flax_available()... | 282 |
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def a_ ( __lowercase : Sequence[float] , __lowercase : int , __lowercase : int ) -> tuple[int | None, int | None, float]:
... | 282 | 1 |
UpperCAmelCase_ : Optional[int] = [0, 2, 4, 6, 8]
UpperCAmelCase_ : List[Any] = [1, 3, 5, 7, 9]
def SCREAMING_SNAKE_CASE_ ( __A : int , __A : int , __A : list[int] , __A : int ) -> int:
"""simple docstring"""
... | 120 |
import json
import sys
def SCREAMING_SNAKE_CASE_ ( __A : Optional[Any] , __A : List[str] ) -> Tuple:
"""simple docstring"""
with open(__A , encoding='utf-8' ) as f:
a_ : Union[str, Any] = json.load(__A )
... | 120 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaS... | 109 | '''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .... | 145 | 0 |
'''simple docstring'''
def __UpperCamelCase ( _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ):
return round(float(moles / volume ) * nfactor )
def __UpperCamelCase ( _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ):
return round(float((moles * 0.0_821 * temperat... | 371 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
lowerCAmelCase__ : int = {
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
"g... | 37 | 0 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
UpperCamelCase__ = True
except (ImportError, ModuleNotFoundError):
UpperCamelCase__ = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', qu... | 181 |
'''simple docstring'''
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
UpperCamelCase__ = namedtuple(
'''_Te... | 181 | 1 |
A_ : Tuple = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ ) -> list[str]:
UpperCam... | 352 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : Tuple = logging.get_logger(__name__)
A_ : Dict = {
'facebook/xglm-564M': 'https://huggingface.co/facebook/xglm-564M/resolve/main/config.json',
# See all XGLM models at https://huggi... | 292 | 0 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
_lowerCamelCase : int = (720, 1280) # Height, Width
_lowerCamelCase : List[str] = (0.4, 0.6) # if height or width lower tha... | 28 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase : Union[str, Any] = {
"configuration_instructblip": [
"INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InstructBlipConfig",
"InstructBlipQFor... | 222 | 0 |
from graphs.minimum_spanning_tree_kruskal import kruskal
def __magic_name__ ( ) -> Union[str, Any]:
__lowerCamelCase = 9
__lowerCamelCase = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
[2, 8, 2],
[8, 6, ... | 339 |
from __future__ import annotations
def __magic_name__ ( __lowerCAmelCase : list[int] ) -> bool:
return len(set(__lowerCAmelCase ) ) == len(__lowerCAmelCase )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 339 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...utils im... | 43 | def lowerCamelCase ( SCREAMING_SNAKE_CASE = 1 , SCREAMING_SNAKE_CASE = 1_000 ):
'''simple docstring'''
__UpperCamelCase :Union[str, Any] = 1
__UpperCamelCase :Any = 0
for divide_by_number in range(SCREAMING_SNAKE_CASE , digit + 1 ):
__UpperCamelCase :list[i... | 43 | 1 |
'''simple docstring'''
from math import factorial
def SCREAMING_SNAKE_CASE_ (UpperCamelCase = 20 ) -> int:
lowerCamelCase__ : List[str] = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
lowerCamelCas... | 129 |
'''simple docstring'''
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentPar... | 129 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__a :Any = {'configuration_vit_mae': ['VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMAEConfig']}
try:
... | 312 |
"""simple docstring"""
_lowercase : Any = '\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https:/... | 332 | 0 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase__ = get_tests_dir('''fixtures/test_sentence... | 360 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(_... | 244 | 0 |
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__ : Union[str, Any] = logging.get_logger(__name__)
SCREAM... | 48 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ : List[Any] = {'processing_layoutxlm'... | 48 | 1 |
'''simple docstring'''
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase = "" , _UpperCAmelCase = False):
'''simple docstring'''
__A : dict[str, RadixNode] = {}
# A node will be a le... | 357 |
'''simple docstring'''
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER,... | 190 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( A__ : list[int] , A__ : int ):
'''simple docstring'''
if len(A__ ) < k or k < 0:
raise ValueError("""Invalid Input""" )
lowerCAmelCase_ : ... | 120 |
'''simple docstring'''
def UpperCamelCase_ ( A__ : list[list[float]] ):
'''simple docstring'''
lowerCAmelCase_ : list[list[float]] = []
for data in source_data:
for i, el in enumerate(A__ ):
if len(A__ ) < i + 1:
data_lists... | 120 | 1 |
'''simple docstring'''
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import Bat... | 350 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def __a ( _UpperCamelCase: list[Any] ) -> None:
"""simple docstring"""
create_state_space_tree(_UpperCamelCase , [] , 0 )
def __a ( _UpperCamelCase: ... | 142 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ ) -> List[str]:
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ ) -> Any:... | 14 |
'''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_availab... | 37 | 0 |
"""simple docstring"""
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
__UpperCamelCase : Optional[Any] = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
__UpperCamelCase : List[Any] = typing.Union[n... | 368 |
"""simple docstring"""
from __future__ import annotations
import math
__UpperCamelCase : Dict = '''2020.9.26'''
__UpperCamelCase : Tuple = '''xcodz-dot, cclaus, dhruvmanila'''
def __SCREAMING_SNAKE_CASE ( A_ , A_ , A_ , A_ , A_ ):
if n... | 74 | 0 |
from __future__ import annotations
import requests
_SCREAMING_SNAKE_CASE : Dict = set(
"approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_cat... | 127 |
"""simple docstring"""
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class _UpperCAmelCase :
UpperCamelCase = None
def lowerCamelCase ( self :List[Any] ):
A = self.feature_extraction_... | 292 | 0 |
'''simple docstring'''
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase : int = {
"""facebook/mask2former-swin-small-coco-instance""": (
"""htt... | 370 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : int | float | str , snake_case : int | float | str ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
a : ... | 345 | 0 |
from graphs.minimum_spanning_tree_kruskal import kruskal
def A ( ) -> Any:
'''simple docstring'''
_UpperCAmelCase = 9
_UpperCAmelCase = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
[2, 8, 2],
[8, 6, 6... | 339 |
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def A ( _UpperCAmelCase : str , _UpperCAmelCase : Any , _UpperCAmelCase : List[str] , _UpperCAmelCase : Optional[int]=5 ) -> List[Any]:
'''simple docstring'''
... | 339 | 1 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from datasets.... | 365 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase__ : str ={'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
t... | 118 | 0 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def lowerCAmelCase__ ( lowerCamelCase_ : float ,lowerCamelCase_ : float ,lowerCamelCase_ : bool = False):
'''simple docstring'''
if radian_mode:
... | 129 |
def lowerCAmelCase__ ( lowerCamelCase_ : str):
'''simple docstring'''
lowerCAmelCase__ : Any = [0] * len(lowerCamelCase_)
for i in range(1 ,len(lowerCamelCase_)):
# use last results for better performance - dynamic programming
lowerCAmelCase__ ... | 129 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : str = logging.get_logger(__name__)
A_ : Tuple = {
"google/pix2struct-textcaps-base": (
"https://huggingface.co/... | 316 |
"""simple docstring"""
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 316 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = '... | 244 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import ConfigTester
from... | 244 | 1 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
_a : Tuple = '\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives and FN ... | 126 | """simple docstring"""
import socket
def SCREAMING_SNAKE_CASE ( ) -> str:
_lowerCAmelCase : Optional[int] = socket.socket(socket.AF_INET ,socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] = socket.gethostname()
_lowerCAmelCase : Tuple ... | 126 | 1 |
'''simple docstring'''
from typing import List
import numpy as np
def _lowerCAmelCase ( _UpperCamelCase : dict ) -> int:
"""simple docstring"""
_SCREAMING_SNAKE_CASE ={key: len(_UpperCamelCase ) for key, value in gen_kwargs.items() if isinstance(_UpperC... | 47 |
'''simple docstring'''
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.c... | 190 | 0 |
import pprint
import requests
_lowerCamelCase : Dict = '''https://zenquotes.io/api'''
def __lowerCamelCase ():
return requests.get(API_ENDPOINT_URL + "/today" ).json()
def __lowerCamelCase ():
return requests.get(API_ENDPOINT_URL + "/random" ... | 206 | from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : Any = {'... | 206 | 1 |
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