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 |
|---|---|---|---|---|
'''simple docstring'''
from __future__ import annotations
class lowerCamelCase__:
def __init__( self , __UpperCAmelCase , __UpperCAmelCase ):
"""simple docstring"""
__lowercase , __lowercase = text, pattern
__lowercase , __lowercas... | 566 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_avai... | 566 | 1 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( lowerCAmelCase_ ):
"""simple docstring"""
__UpperCamelCase = (CMStochasticIterativeScheduler,)
__U... | 340 |
'''simple docstring'''
from collections import deque
def __a ( lowerCAmelCase__ : int ):
a__ : int = len(lowerCAmelCase__ )
a__ : str = deque()
a__ : List[Any] = [False for _ in range(lowerCAmelCase__ )]
a__ : int = [-1 for _ in r... | 340 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 1 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 387 | # 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 a... | 387 | 1 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won... | 473 |
a_ :dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.60_93_44,
"knot": 1.8_52,
}
a_ :dict[str, float] = {
"km/h": 1.0,
"m/s": 0.2_77_77_77_78,
"mph": 0.6_21_37_11_92,
"knot": 0.5_39_95_68_03,
}
def lowercase_ (A : float , A : str , ... | 478 | 0 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedIte... | 287 | '''simple docstring'''
def _UpperCamelCase ( _a : int ):
"""simple docstring"""
if bit_count < 0:
raise ValueError('The given input must be positive' )
# get the generated string sequence
__UpperCamelCase : Dict = gray_code_sequence_string(_a )
#
# convert them t... | 287 | 1 |
import re
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ ):
snake_case_ = re.compile(
R'''^(?:0|94|\+94|0{2}94)''' R'''7(0|1|2|4|5|6|7|8)''' R'''(-| |)''' R'''\d{7}$''' )
return bool(re.search(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) )
if... | 39 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging ... | 39 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase : List[str] = {'configuration_vit_mae': ['VIT_MAE_PRETRAINE... | 361 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_dif... | 361 | 1 |
import random
class _lowerCAmelCase :
@staticmethod
def __a ( _UpperCamelCase ) -> tuple[list[int], list[int]]:
lowerCAmelCase_ = [ord(_UpperCamelCase ) for i in text]
lowerCAmelCase_ = []
lowerCAmelCase_ = []
for i i... | 290 |
from collections.abc import Callable
def lowerCamelCase__ ( __lowerCAmelCase : Callable[[float], float] , __lowerCAmelCase : float , __lowerCAmelCase : float ):
"""simple docstring"""
lowerCAmelCase_ = a
lowerCAmelCase_ =... | 290 | 1 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer, FlaxM... | 402 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
__a: str ... | 402 | 1 |
'''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 Bas... | 697 |
'''simple docstring'''
def a ( _UpperCAmelCase ) -> int:
"""simple docstring"""
assert column_title.isupper()
a_ = 0
a_ = len(_UpperCAmelCase ) - 1
a_ = 0
while index >= 0:
a_ = (ord(column_title[index] ) - 6_4) * po... | 697 | 1 |
def _UpperCAmelCase ( a : float , a : float ) -> float:
"""simple docstring"""
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f"""{price_plus_tax(1_0_0, 0.25) = }""")
print(f"""{price_plus_tax(125.50, 0.05) = }""")
| 715 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
A: Tuple = l... | 7 | 0 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_atte... | 598 |
import operator as op
def a_ ( __magic_name__ ) -> Any:
"""simple docstring"""
snake_case : str = []
snake_case : Any = lambda __magic_name__ , __magic_name__ : int(x / y ) # noqa: E731 integer division operat... | 598 | 1 |
'''simple docstring'''
import os
import sys
UpperCamelCase =os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSequenceCl... | 711 |
'''simple docstring'''
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("3.8"):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
U... | 543 | 0 |
'''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_p... | 210 |
"""simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, r... | 346 | 0 |
"""simple docstring"""
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
... | 397 |
"""simple docstring"""
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED... | 397 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"""google/bigbird-roberta-base... | 93 |
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...... | 307 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase = {
"""configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}
try:
if not is_torch_available():
rai... | 718 |
"""simple docstring"""
def A__ ( _UpperCAmelCase : int = 1_00_00_00 ) -> int:
'''simple docstring'''
snake_case__ : List[Any] = limit + 1
snake_case__ : Union[str, Any] = [0] * limit
for first_term in range(1 , _UpperCAmelCase ):
for n in range(_UpperCAmel... | 150 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
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 imp... | 56 |
'''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
#
... | 56 | 1 |
'''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 SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ):
... | 68 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
fro... | 68 | 1 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from to... | 203 |
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__lowercase ... | 203 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.functional import Int... | 717 |
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedIterator
from tqdm im... | 321 | 0 |
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 datase... | 0 |
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils ... | 0 | 1 |
import argparse
import gc
import json
import os
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 Accelera... | 708 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {}
class __snake_case ( SCREAMING_SNAKE_CASE ):
SCREAMING_SNAKE_CASE__ = 'llama'
SCREAMING_SNAKE_CASE... | 604 | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, Flax... | 492 |
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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
ViltFor... | 492 | 1 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('''dataset_size''' , [None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize('''input_in_memory_max_size''' , ['''default''', 0, 1_00 * 2**20, 9_00 * 2**20] ... | 718 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 288 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless req... | 154 |
def lowerCAmelCase ( UpperCAmelCase = 6008_5147_5143 ) ->int:
"""simple docstring"""
try:
__magic_name__ : Optional[int] = int(UpperCAmelCase )
except (TypeError, ValueError):
raise TypeError('''Parameter n must... | 154 | 1 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return round(float(moles / volume ) * nfactor )
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
return round(float((m... | 712 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {"""configuration_encoder_decoder""": ["""EncoderDecoderConfig"""]}
try:
if not is_torch_availabl... | 152 | 0 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_... | 16 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase ( __lowerCamelCase : str , __lowerCamelCase : str ) ->str | Literal[False]:
_SCREAMING_SNAKE_CASE = list(__lowerCamel... | 314 | 0 |
'''simple docstring'''
def a_ ( ):
lowerCAmelCase = []
lowerCAmelCase = 1
while len(lowerCamelCase ) < 1e6:
constant.append(str(lowerCamelCase ) )
i += 1
lowerCAmelCase = ''.join(lowerCamelCase )
return (
int(constant[0] )
... | 712 |
'''simple docstring'''
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def a_ ( lowerCamelCase : str , lowerCamelCase : List[str] , lowerCamelCase : Any ):
lowerCAmelCase = ... | 513 | 0 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch... | 407 |
'''simple docstring'''
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__A ='<<<<<<< This should probably be modified because it mentions: '
__A ='===... | 407 | 1 |
def A__ ( __A , __A ):
'''simple docstring'''
_lowerCamelCase : Union[str, Any] = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
_lowerCamelCase : str = n - k
# Calculate C(n,k)
for i in rang... | 719 | import math
def A__ ( __A ):
'''simple docstring'''
assert isinstance(__A , __A ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or not numbe... | 15 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCamelCase : Dict = {'''processing_layo... | 4 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : ... | 4 | 1 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__UpperCamelCase : Optional[Any] = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__UpperCamelCase ... | 713 |
def a_ ( _A = 4000000 ) -> int:
"""simple docstring"""
snake_case__ = [0, 1]
snake_case__ = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
snake_cas... | 372 | 0 |
'''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
a_ : List[Any] = logging.getLogger(__name__)
class __UpperCamelCase ( A__ ):
lowercase : Union[str, Any] ='masked_bert'
def __init__( self, ... | 676 |
import argparse
import json
import subprocess
def __lowercase ( _UpperCamelCase, _UpperCamelCase ) ->Optional[int]:
"""simple docstring"""
lowercase : int = []
lowercase : int = (
f"""curl -H \"Accept: application/vnd.github+js... | 319 | 0 |
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Con... | 441 |
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCamelCase ( _a , _a , _a ) -> List[... | 441 | 1 |
'''simple docstring'''
import math
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : Union[str, Any] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(lowerCamelCase__ )
def a ( lowerCam... | 667 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as... | 667 | 1 |
def _lowercase ( SCREAMING_SNAKE_CASE_ : str ):
"""simple docstring"""
assert column_title.isupper()
UpperCamelCase = 0
UpperCamelCase = len(SCREAMING_SNAKE_CASE_ ) - 1
UpperCamelCase = 0
while index >= 0:
UpperCa... | 181 |
import math
import unittest
def _lowercase ( SCREAMING_SNAKE_CASE_ : int ):
"""simple docstring"""
assert isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < n... | 181 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
a__ : List[Any] = 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_copies # noqa: E402
# This is the ref... | 188 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
a__ : Any = logg... | 188 | 1 |
'''simple docstring'''
from collections.abc import Generator
def __UpperCAmelCase ( ) -> Generator[int, None, None]:
"""simple docstring"""
__a , __a = 0, 1
while True:
__a , __a = b, a + b
yield b
def __UpperCA... | 270 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
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_con... | 270 | 1 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from tra... | 508 |
'''simple docstring'''
def __snake_case ( lowercase : int ):
snake_case_ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def __snake_case ( lowercase : int ):
snake_case_ = 0
while number > 0:
snake_ca... | 508 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
_A : Optional[int] ={'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
... | 720 |
'''simple docstring'''
def __UpperCamelCase ( _lowercase, _lowercase ) -> list:
_lowercase : List[str] = word.split()
def justify(_lowercase, _lowercase, _lowercase ) -> str:
_lowercase : Dict = max_width - width
_lowercase : Tupl... | 4 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Any = {"tokenization_tapex": ["TapexTokenizer"]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : Tuple = ... | 591 |
'''simple docstring'''
import math
def lowerCAmelCase_ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = 0 , SCREAMING_SNAKE_CASE_ = 0 ) -> list:
"""simple docstring"""
_SCREAMING_SNAKE_CASE = end or len(SCREAMING_SNAKE_CASE_ )
for i in range(SCREAMING_SNAKE_CASE_ ... | 591 | 1 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
from .test_pipelines_... | 478 |
from datetime import datetime as dt
import os
from github import Github
__lowerCamelCase = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def _a ( ):
a_ : List[str] ... | 478 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_v... | 92 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow... | 92 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__SCREAMING_SNAKE_CASE : Optional[Any] = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 697 |
'''simple docstring'''
import numpy as np
from PIL import Image
def _snake_case ( lowercase , lowercase , lowercase ) -> np.ndarray:
__a : Any = np.array(lowercase )
if arr.shape[0] != arr.shape[1]:
raise ValueError("""The input array i... | 697 | 1 |
'''simple docstring'''
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 dedupli... | 435 | '''simple docstring'''
from sklearn.metrics import fa_score
import datasets
lowerCAmelCase_ : int = """
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
"""
lowerCAmelCase_ ... | 435 | 1 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
UpperCAmelCase = ... | 711 |
'''simple docstring'''
from __future__ import annotations
def A ( A_ : list[int] , A_ : int ):
snake_case : list[list[int]] = []
snake_case : list[int] = []
snake_case : int = 0
snake_case : int... | 555 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMi... | 518 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
... | 518 | 1 |
def _snake_case ( __snake_case ):
def merge(__snake_case , __snake_case ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
retu... | 71 | import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@require_to... | 71 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmelCase_ (a__ ... | 223 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
requi... | 223 | 1 |
"""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 AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testi... | 544 |
"""simple docstring"""
import argparse
from collections import defaultdict
def a__ ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
"""simple docstring"""
UpperCamelCase = F"{file}_{class_name}_{test_... | 544 | 1 |
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,
MobileViTVaForS... | 699 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
"microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/main/config.json",
# See all BioGPT models at https://huggin... | 699 | 1 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils i... | 611 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _A ( __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__=1024 ):
lowercase__ , lowercase__ = [], []
lowercas... | 611 | 1 |
from __future__ import annotations
class lowerCAmelCase_ :
def __init__( self, SCREAMING_SNAKE_CASE_ ) -> None:
UpperCamelCase : List[Any] = order
# a_{0} ... a_{k}
UpperCamelCase : Tuple = [1.0] + [0.0] * ... | 40 |
from math import factorial
class __lowercase :
"""simple docstring"""
def __init__( self , __UpperCAmelCase , __UpperCAmelCase ) -> Optional[int]:
A : Union[str, Any] = real
if isinstan... | 542 | 0 |
'''simple docstring'''
lowercase = {
'''a''': '''AAAAA''',
'''b''': '''AAAAB''',
'''c''': '''AAABA''',
'''d''': '''AAABB''',
'''e''': '''AABAA''',
'''f''': '''AABAB''',
'''g''': '''AABBA''',
'''h''': '''AABBB''',
'''i''': '''ABAAA''',
'''j''': '''BBBAA''',
... | 715 |
'''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... | 564 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( lowerCamelCase_) -> bool:
if not isinstance(lowerCamelCase_ , lowerCamelCase_):
raise ValueError('check_bouncy() accepts only integer arguments')
UpperCamelCase__ : Any = str(lowerCamelCase_)
UpperCamel... | 596 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
... | 596 | 1 |
"""simple docstring"""
def snake_case__ ( _SCREAMING_SNAKE_CASE ) ->int:
UpperCAmelCase__ = [[0 for _ in range(_SCREAMING_SNAKE_CASE )] for _ in range(m + 1 )]
for i in range(m + 1 ):
UpperCAmelCase__ = 1
for n in range(m + 1 ):
for k in range(1 , _SCREAMING_SNAKE_... | 422 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Dict = logging.get_logger(__name__)
a : Tuple = {
'''junnyu/rofo... | 422 | 1 |
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self : int ):
'''simple docstring'''
__a = (0, 0)
__a = None
__a = 0
__a = 0
__a = 0
def __eq__( self : Union[str, Any] , ... | 225 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import Reg... | 225 | 1 |
from collections import deque
from math import floor
from random import random
from time import time
class lowercase__ :
def __init__( self ):
lowerCAmelCase_ : Optional[Any] = {}
def UpperCAmelCase__ ( self , _lowercase , _lowercase , ... | 440 |
UpperCAmelCase_ : str = """Alexander Joslin"""
import operator as op
from .stack import Stack
def _lowerCAmelCase ( _a : str ) -> int:
lowerCAmelCase_ : Any = {"""*""": op.mul, """/""": op.truediv, """+""": op.add, """-""": op.sub}
lowerCAmelCas... | 440 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : int = 10_00 ) -> int:
'''simple docstring'''
_A = 2**power
_A = str(_snake_case )
_A = list(_snake_case )
_A = 0
for i in list_num:
sum_of_num += int(_snake... | 7 |
"""simple docstring"""
import argparse
a = '''docs/source/_static/js/custom.js'''
def _snake_case ( _snake_case : Dict ) -> Any:
'''simple docstring'''
with open(_snake_case , encoding='utf-8' , newline='\n' ) as f:
_... | 7 | 1 |
from math import factorial
__a : dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def _SCREAMING_SNAKE_CASE ( __lowercase : int ) -> int:
"""simple docstring"""
if not isinstance(__lowercase , __lowercase ):
raise ... | 199 |
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
__a : List[Any] = "Usage of script: script_name <size_of_canvas:int>"
__a : Dict = [0] * 100 + [1] * 10
random.shuffle(choice)
def _SCREAMING_... | 199 | 1 |
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
_lowerCamelCase = {
'sample_size': 32,
'in_channels': 3,
'out_channels': 3,
'layers_per_block': 2,
'num_class_embeds': 1000,
... | 114 |
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,
... | 114 | 1 |
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
UpperCAmelCase_ : List[Any] = logging.getLogger()
def UpperCamelCase ... | 705 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
ren... | 232 | 0 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
UpperCamelCase__ = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saura... | 75 |
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
__snake_case = logging.ge... | 472 | 0 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __lowerCamelCase ( A__ = "AAPL" ) -> str:
"""simple docstring"""
UpperCamelCase = F"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
UpperCamelCas... | 324 |
'''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
impor... | 324 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : Optional[Any] = {
"configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}
try:
if not ... | 656 | """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 .tokeni... | 656 | 1 |
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 .tokenizati... | 559 |
from __future__ import annotations
def a_ ( __snake_case ) -> list:
'''simple docstring'''
if len(__snake_case ) == 0:
return []
UpperCamelCase_ , UpperCamelCase_ = min(__snake_case ), max(__snake_case )
UpperCamelCase_ ... | 559 | 1 |
"""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_vision,... | 88 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCAmelCase : Optional[int] ={
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIV... | 359 | 0 |
from __future__ import annotations
def _snake_case ( __snake_case , __snake_case = None , __snake_case = None ):
if start is None:
_UpperCamelCase = 0
if end is None:
_UpperCamelCase = len(__snake_case ) - 1
if start >= end:
return
... | 71 | import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCAmelCase_ :
@property
def UpperCamelCase_ ( self : ... | 71 | 1 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def lowerCamelCase__ ( a__ , a__=False) -> Optional[int]:
"""simple docstring"""
_snake_case : str = OmegaConf.load(a__)
... | 517 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase__ ( a__) -> bool:
"""simple docstring"""
return len(set(a__)) == len(a__)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 517 | 1 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging impo... | 647 | def __lowerCamelCase (UpperCAmelCase__ : int ):
assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), F"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE = F"The input value o... | 647 | 1 |
"""simple docstring"""
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : str = logging.get_logger(__name__)
_lowercase : Optional[Any] = {
'huggingface/autoformer-tourism-month... | 49 |
"""simple docstring"""
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDCon... | 465 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : List[str] = logging.get_logger(__name__)
__lowercase : List[str] = {
"""huggingface/informer-tourism-monthly""": (
... | 66 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_availabl... | 66 | 1 |
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = (PNDMScheduler,)
UpperCamelCase__ = (('''num_inference_steps''', 50),)
def snake_case_ ... | 632 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''timm_backbone'''
def __init__( self , a__=None , a__=3 , a__=True , ... | 632 | 1 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_si... | 703 |
'''simple docstring'''
import os
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_pegasus import PegasusTokenizer... | 123 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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 im... | 75 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
lowerCAmelCase : List[Any] = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
... | 3 | 0 |
"""simple docstring"""
from datetime import datetime as dt
import os
from github import Github
A_ : Dict = [
"good first issue",
"good second issue",
"good difficult issue",
"feature request",
"new model",
"wip",
]
def lowerCamelCase_ ( ):
lowerCamelCase__ : ... | 712 |
"""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 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 316 |
'''simple docstring'''
def lowerCamelCase_ ( A_ , A_ ):
__lowerCamelCase = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
__lowerCamelCase = n - k
# Calculate C(n,k)
for i in range(A_ ):
result *= n - i
result //= i + 1
retur... | 316 | 1 |
def _lowerCAmelCase ( UpperCamelCase__: list[int] , UpperCamelCase__: list[int] ) -> tuple[float, float]:
"""simple docstring"""
if not len(UpperCamelCase__ ) == len(UpperCamelCase__ ) == 3:
raise ValueError("""Please enter a valid equation.""" )
if equ... | 546 |
import argparse
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 Accelerator, Di... | 546 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
__magic_name__ = logging.get_logger(__name__) # pylint: disable=invalid-name
def ... | 232 |
from __future__ import annotations
def _a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
return len(set(SCREAMING_SNAKE_CASE ) ) == len(SCREAMING_SNAKE_CASE )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 43 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : Optional[int] = logging.get_logger(__name__)
A_ : str = {
"asapp/sew-d-tiny-100k": "https://huggingface.co/asapp/sew-d-tiny-100k/reso... | 705 |
"""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
A_ : Dict = "src/transformers"
# This is to make sure the transformers ... | 696 | 0 |
def a_ ( __magic_name__ ) -> int:
"""simple docstring"""
if not isinstance(__magic_name__ , __magic_name__ ):
snake_case : Union[str, Any] = F"Input value of [number={number}] must be an integer"
raise TypeError(__magi... | 598 |
import unittest
from transformers import DonutProcessor
_a : Optional[int] = 'naver-clova-ix/donut-base'
class a_ ( unittest.TestCase ):
def lowerCAmelCase( self : Tuple ):
"""simple docstring"""
snake_case : Option... | 598 | 1 |
'''simple docstring'''
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
A = 0
A = [
[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],
... | 449 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __snake_case ( a__... | 449 | 1 |
from jiwer import compute_measures
import datasets
__A : Optional[int] = '\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WIL: improved evaluati... | 16 |
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.util... | 37 | 0 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table i... | 715 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , UpperCAmelCase__ : List[Any]=None , UpperCAmelCase__ : Optional[Any]=None ):
'''simple docstring'''
... | 88 | 0 |
from ...configuration_utils import PretrainedConfig
lowerCamelCase__ : List[Any] = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
"""https://h... | 12 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( UpperCAmelCase_ ):
__lowerCAmelCase : int = (DDPMScheduler,)
def lowercase__ ( self , **SCREAMING_SNAKE_CASE_):
'''simple docstring'''
... | 12 | 1 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
snake_case_ : List[str] = "."
# Inte... | 713 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Optional[Any] = logging.get_logger(__name__)
snake_case_ : Optional[int] = {
"huggingface/informer-tourism-monthly": (
"https://huggingface.co/hugg... | 253 | 0 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
_UpperCAmelCase : Union[str, Any] = get_logger(__name__)
class lowercase_ ( enum.Enum ):
"""simple docstring""... | 107 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _lowercase ( __a ):
_UpperCAmelCase = (DDPMScheduler,)
def UpperCamelCase ( self ,... | 342 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
_lowercase: List[str] = len(UpperCamelCase__ ) + 1
_lowercase: Dict = len(UpperCamelCase__ ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether... | 703 |
"""simple docstring"""
def _lowerCAmelCase ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
return number | (1 << position)
def _lowerCAmelCase ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
return number & ~(1 << position)
def _l... | 272 | 0 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class __A ( UpperCamelCase__ ):
UpperCamelCase = """"""
UpperCamelCase = (
None # pr... | 21 | from typing import Any
def __A ( _A ):
"""simple docstring"""
if not input_list:
return []
__a = [input_list.count(_A ) for value in input_list]
__a = max(_A ) # Gets the maximum count in the input list.
# Gets values of modes
return sorted({input_li... | 197 | 0 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import ... | 710 | '''simple docstring'''
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("""3.8"""):
import importlib_metadata
else:
import importlib.metadata as importlib_... | 512 | 0 |
def __magic_name__ ( ):
'''simple docstring'''
return 1
def __magic_name__ ( lowerCAmelCase_):
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2) + one_pence()
def __magic_name__ ( lowerCAmelCase_):
'''simple doc... | 250 |
# 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 require... | 250 | 1 |
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_uti... | 328 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
__lowerCamelCase = logging.get_logger(__name__)
class _UpperCamelCase( SCREAMING_SNAKE_CASE ):
def __init__( self : Any , *_lowerCamelCase : Any , **_lowerCamelCas... | 328 | 1 |
# 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 ap... | 66 |
'''simple docstring'''
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 374 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE... | 721 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_... | 76 | 0 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a : Any = '''__DUMMY_TRANSFORMERS_USER__'''
a : Optional[Any] = '''Dummy User'''
a : ... | 640 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 667 | 0 |
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 ... | 713 |
def _lowercase ( UpperCamelCase_ , UpperCamelCase_ ) -> str:
'''simple docstring'''
if number < 0 or shift_amount < 0:
raise ValueError('both inputs must be positive integers' )
SCREAMING_SNAKE_CASE__ = str(bin(UpperCamelCase_ ) )
binary_number += "0" * shi... | 400 | 0 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
lowerCamelCase : Tuple = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < ... | 70 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
SCREAMING_SNAKE_CASE_ = '\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value... | 34 | 0 |
"""simple docstring"""
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whit... | 719 |
"""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, Times... | 562 | 0 |
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