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 torch
from transformers import AutoModel
class __UpperCamelCase ( torch.nn.Module ):
def __init__( self , __a="sayef/fsner-bert-base-uncased" ):
'''simple docstring'''
super(__a , self ).__init__()
__a ... | 27 |
'''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_single_gpu,
)
from accelerate.... | 27 | 1 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def UpperCAmelCase ( _lowerCamelCase ):
A : List[str] = FileLock(str(tmpdir / "foo.lock" ) )
A : Optional[Any] = FileLock(str(tmpdir / "foo.lock"... | 256 |
from collections import deque
from .hash_table import HashTable
class lowerCamelCase_ ( _A ):
'''simple docstring'''
def __init__( self : Optional[int] , *__lowerCamelCase : int , **__lowerCamelCase : Tuple ) -> Optional[Any]:
su... | 256 | 1 |
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
lowercase__ :Optional[int] = logging.get_logger(__name__)
lowercase__ :Optional[int] = "T5Config"
def ... | 101 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__lowerCAmelCase = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''EncodecConfig''',
],
... | 196 | 0 |
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
_lowerCamelCase : ... | 362 |
from __future__ import annotations
import time
_lowerCamelCase : Tuple = list[tuple[int, int]]
_lowerCamelCase : int = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],... | 191 | 0 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when swi... | 69 | """simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def UpperCAmelCase ( ) -> int:
snake_case_ = HfArgumentParser(UpperCAmelCase )
snake_case_ = parser.parse_args_into_dataclasses()[0]
... | 69 | 1 |
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_... | 201 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case = {
"""configuration_autoformer""": [
"""AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AutoformerConfig""",
... | 201 | 1 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowerCamelCase_ ( SCREAMING_SNAKE_CASE__ : dict, SCREAMING_SNAKE_CASE__ : str, SCREAMING_SNAKE_CASE__ : set, SCREAMING_SNAKE_CASE__ : set, SCREAMING_SNAKE_CASE__ : dict... | 125 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class __a (lowerCamelCase ):
__a : Dict = "SpeechT5FeatureExtractor"
__a : Any = "SpeechT5Tokenizer"
def __init__( self : Any , __magic_name__ : Union... | 125 | 1 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokeniz... | 359 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffusion.modeling_roberta_series... | 60 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowerCamelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCame... | 81 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _A (__a , __a , __a ) -> Dict:
"""simple d... | 91 | 0 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class lowerCAmelCase :
def __init__( self :int , _lowercase :List[Any] ):
'''simple docstring'''
lowercase__ = data
lowercase__ = [0X67452301... | 201 |
def _A ( __magic_name__ ):
lowercase__ = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def _A ( __magic_name__ ):
lowercase__ = [chr(i + 65 ) for i in range(26 )]
# Remove duplicate... | 201 | 1 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCamelCase : Tuple = None
try:
import msvcrt
except ImportError:
__lowerCamelCase : Optional[Any] = None
try:
import fcntl
except ImportError:
__lowerCam... | 52 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase : List[Any] = logging.get_logger(__name__)
__lowerCamelCase : str = {
"""roberta-b... | 52 | 1 |
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_available():
... | 315 |
# 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... | 315 | 1 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def snake_case_ ( _lowerCAmelCase : str = "https://www.worldometers.info/coronavirus" ) -> dict:
UpperCAmelCase : str = BeautifulSoup(requests.get(_lowerCAmelCase ).text , ... | 23 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
... | 23 | 1 |
'''simple docstring'''
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMi... | 346 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _lowerCamelCase ( ) -> str:
_a = HfArgumentParser(lowercase )
_a = parser.parse_args_into_dataclasses()[0]
_a =... | 346 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class a ( metaclass=SCREAMING_SNAKE_CASE_ ):
snake_case_ = ["keras_nlp"]
def __init__( self : Optional[int] , *lowercase_ : Tuple , **lowercase_ : Any ):
... | 56 |
'''simple docstring'''
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.tra... | 208 | 0 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class lowercase__ ( _snake_case ):
"""simple docstring"""
def A_ ( self : str , UpperCAmelCase_ : str ):
... | 363 |
from __future__ import annotations
from collections.abc import Generator
def _lowercase ( ) -> Generator[int, None, None]:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = {}
SCREAMING_SNAKE_CASE__ = 2
while True:
SCREAMING_SNAKE_CASE... | 169 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase__( UpperCAmelCase ):
"""simple do... | 30 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def __lowerCamelCase ( a_ : str , a_ : Dict , a_ : Any , a_ : str ) -> str:
__SCREAMING_SNAKE_CASE :... | 191 | 0 |
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class UpperCamelCase_ (__A ):
__magic_name__ = DistilBertTokenizer... | 369 |
"""simple docstring"""
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..ut... | 253 | 0 |
'''simple docstring'''
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
snake_case_ : Any = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.pa... | 83 |
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 | 0 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test... | 228 |
'''simple docstring'''
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... | 228 | 1 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: list ,__UpperCamelCase: list ):
"""simple docstring"""
_validate_point(_snake_case )
_validate_point(_snake_case )
if len(_snake_case ) != len(_snake_case ):
raise ValueError('... | 251 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (... | 60 | 0 |
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_tokenization_common import TokenizerTeste... | 50 | def __lowercase ( lowerCamelCase : int ):
if not isinstance(lowerCamelCase , lowerCamelCase ):
raise TypeError('only integers accepted as input' )
else:
UpperCamelCase_ : Any = str(abs(lowerCamelCase ) )
UpperCamelCase_ : Any = [list(lowerCamelCase ) ... | 50 | 1 |
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = 'T5Config'
... | 201 |
class lowercase__ :
'''simple docstring'''
def __init__( self, __magic_name__ = "", __magic_name__ = False ) -> None:
"""simple docstring"""
# Mapping from the first character of the prefix of the node
UpperCamelCase__ : di... | 201 | 1 |
"""simple docstring"""
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCamelCase_ = "s... | 239 |
"""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
lowerCamelCase_ = logging.get_logger(__name__)
lowerCam... | 239 | 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 applic... | 295 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar, enabl... | 295 | 1 |
def __lowerCamelCase (UpperCAmelCase__ : int ):
SCREAMING_SNAKE_CASE = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def __lowerCamelCase (UpperCAmelCase__ : int ):
SCREAMING_SNAKE_CASE = ... | 206 | import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_lowerCamelCase : Dict = re.compile(r'''\b(a|an|the)\b''', re.UNICODE)
_lowerCamelCase : Optional[int] = None
def __lowerCamelCase ():
... | 206 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get... | 42 | """simple docstring"""
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils imp... | 213 | 0 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class a__ :
def __SCREAMING_SNAKE_CASE ( self , UpperCAmelCase ) -> Optional[Any]:
raise NotImplementedError()
... | 197 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase_ : Dict = {"""configuration_speech_encoder_decoder""": ["""SpeechEncoderDecoderConfig"""]}
try:
if not is_torch_available():
raise OptionalDep... | 197 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__snake_case = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-la... | 97 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : Union[str, Any] = {
"configuration_blenderbot_small": [
"B... | 169 | 0 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ... | 277 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ... | 277 | 1 |
'''simple docstring'''
import re
import string
import numpy as np
import datasets
UpperCAmelCase : Dict = '\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n'
UpperCAmelCase : List[str... | 267 |
import argparse
from collections import defaultdict
import yaml
lowerCAmelCase : Dict = 'docs/source/en/_toctree.yml'
def A_ ( a ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[int] = defaultdict(a )
for doc in model_doc:
... | 253 | 0 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( _snake_case : list[list[int]] ) -> int:
'''simple docstring'''
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the... | 363 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
a = HUGGINGFACE_HUB_CACHE
a = '''config.json'''
a = '''diffusion_pytorch_model.bin'''
a = '''diffusion_flax_model.msgpack'''
a = '''mode... | 271 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ : List[Any] = {"""configuration_fnet""": ["""FNET_PRET... | 165 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__:int = logging.get_logger(__name__)
class snake_case__ ( snake_case_ ):
_snake_case : O... | 261 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Optional[Any] = {
'''configuration_clipseg''': [
'''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''CLIPSegConfig''',
... | 74 |
"""simple docstring"""
from manim import *
class SCREAMING_SNAKE_CASE ( a_ ):
"""simple docstring"""
def __lowerCAmelCase ( self : List[Any] ):
lowerCAmelCase__ : List[str] = Rectangle(height=0.5 ,width=0.5 )
lowerCAmelCase__ : ... | 74 | 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 app... | 50 |
# 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 app... | 50 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, loggin... | 350 |
'''simple docstring'''
def __UpperCamelCase ( _UpperCAmelCase ):
try:
__UpperCAmelCase : Union[str, Any] = float(_UpperCAmelCase )
except ValueError:
raise ValueError("Please enter a valid number" )
__UpperCAmelCase : str = decimal - int(_U... | 37 | 0 |
'''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
... | 239 | '''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : list ) -> list:
if any(not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) or x < 0 for x in sequence ):
raise TypeError("""Sequence must be list of non-negative integers""" )
for _ in ... | 239 | 1 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
_A = loggi... | 205 |
"""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': 'https://hug... | 205 | 1 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ ):
'''simple docstring'''
return [ord(lowerCamelCase__ ) - 96 for elem in plain]
def a ( lowerCamelCase__ ):
'''simple docstring'''
return "".join(chr(elem + 96 ) for elem in encoded ... | 206 |
'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def a ( lowerCamelCase__ ):
'''simple docstring'''
if not sentence:
return ""
A_ : Optional[int] = dict(zip(lowerCamelCase__ , lowerCamelCase__ ) )
return lower_to_upper.get(senten... | 206 | 1 |
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
lowercase : str = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\n booktitl... | 358 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 36 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
__lowerCAmelCase : Dict ... | 197 | """simple docstring"""
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__lowerCAmelCase : int =logging.getLogger(__name__)
class _A :
... | 197 | 1 |
'''simple docstring'''
import math
class a__ :
def SCREAMING_SNAKE_CASE__ ( self : List[str] , a : list[list[float]] , a : list[int] ):
"""simple docstring"""
__lowerCamelCase = 0.0
__lowerCamelCase = 0.0
... | 237 | '''simple docstring'''
__UpperCAmelCase ="ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def __lowerCAmelCase ( ) -> None:
__lowerCamelCase = input('''Enter message: ''' )
__lowerCamelCase = input('''Enter key [alphanumeric]: ''' )
__lowerCamelCase = input... | 237 | 1 |
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 Ac... | 277 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
a_ :Optional[Any] = {"configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "ReformerConf... | 277 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case_ = {"""co... | 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 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transfo... | 185 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
def ... | 225 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCAmelCase = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Chine... | 5 |
'''simple docstring'''
import json
import os
import shutil
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 AutoConfig, BertConfig, GPTaConfig
fr... | 5 | 1 |
"""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
_lowercase = namedtuple(
'''_TestCommandArgs''',
... | 74 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json''',
}... | 74 | 1 |
'''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
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase ... | 5 |
'''simple docstring'''
import json
import os
import shutil
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 AutoConfig, BertConfig, GPTaConfig
fr... | 5 | 1 |
import os
__lowerCAmelCase : int = {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1000}
def a__ ( A_ ):
'''simple docstring'''
__magic_name__ = 0
__magic_name__ = 0
while index < len(A_ ) - 1:
__... | 88 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from... | 37 | 0 |
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.testing_utils import TOKEN, USER, get_... | 19 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available, is_vision_available
f... | 19 | 1 |
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 a ( A__ : Union[str, Any] ... | 205 |
# 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 ... | 205 | 1 |
'''simple docstring'''
from math import ceil, sqrt
def _snake_case ( _SCREAMING_SNAKE_CASE : int = 1_000_000 ) -> int:
"""simple docstring"""
lowerCAmelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width... | 187 |
'''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICom... | 187 | 1 |
"""simple docstring"""
def _snake_case ( lowercase__ , lowercase__ ):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
_lowerCamelCase : List[Any] = (boundary[1] - boundary[0]) / steps
_lowerCamelCase : Tuple = b... | 96 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.rob... | 36 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
__lowerCamelCase : Optional[int] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/... | 286 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def SCREAMING_SNAKE_CASE ( snake_case_ : int ):
for param in module.parameters():
snake_case__ : Tuple = False
def SCREAMING_SNAKE_CASE ( ):
snake_case__ : Any = "... | 286 | 1 |
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase , _UpperCAmelCase ) -> float:
_validate_point(_UpperCAmelCase )
_validate_point(_UpperCAmelCase )
if len(_UpperCAmelCase ) != len(_UpperCAmelCase ):
raise ValueError('Both points must be in the same n-dimensional space' )
... | 50 |
'''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 |
def lowerCamelCase ( lowerCAmelCase : int = 1000 ):
"""simple docstring"""
__magic_name__ : List[Any] = 2**power
__magic_name__ : Tuple = str(_a )
__magic_name__ : Optional[Any] = list(_a )
__magic_name__ : Optional[int] = ... | 361 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase :Any = logging.get_logger(__name__)
lowerCAmelCase :int = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/mai... | 275 | 0 |
'''simple docstring'''
from math import isqrt, loga
def a__ ( lowerCAmelCase__ ) -> list[int]:
UpperCAmelCase__ : int = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in ... | 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 |
def lowerCAmelCase_ ( snake_case_ ):
if num <= 0:
raise ValueError("""Input must be a positive integer""" )
_A : Union[str, Any] = [True] * (num + 1)
_A : Optional[Any] = 2
while p * p <= num:
if primes[p... | 343 |
from __future__ import annotations
from collections.abc import Callable
_snake_case = list[list[float | int]]
def lowerCAmelCase_ ( snake_case_,snake_case_ ):
_A : int = len(snake_case_ )
_A : Matrix = [[0 for _ in range(size + 1 ... | 343 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase__ = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
'''Chi... | 5 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class lowe... | 5 | 1 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A_ : Optional[Any] ... | 349 |
'''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
A_ : Union[str, Any] = logging.get_logger(__name__)
A_ ... | 349 | 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
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''google/vit-ba... | 5 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class lowe... | 5 | 1 |
def __snake_case ( _lowerCAmelCase : str , _lowerCAmelCase : str ) -> bool:
A_ : Optional[Any] = len(_lowerCAmelCase ) + 1
A_ : Optional[int] = len(_lowerCAmelCase ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
# length i of inp... | 70 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 70 | 1 |
__A ='''0.18.2'''
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_librosa_available,
is_note_seq_availabl... | 19 |
import unittest
from transformers import 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 ModelTesterMixin, ids_tensor
from .... | 19 | 1 |
def A ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> float:
'''simple docstring'''
UpperCAmelCase_ = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
return total
def ... | 344 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OPTConfig"]}
t... | 344 | 1 |
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
lowercase__ : Optional[int] = [
# (stable-diffusion, HF Diffusers)
("time_embed.0.weight", "time... | 187 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal... | 187 | 1 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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 impor... | 46 |
'''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, PreTrainedTokenizer
from ...utils import logging
_a : Dict = logging.get_logger(__name__)
_a : Optional[i... | 46 | 1 |
"""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_available... | 286 |
"""simple docstring"""
import copy
import random
from transformers import CLIPTokenizer
class _UpperCAmelCase ( UpperCAmelCase__ ):
'''simple docstring'''
def __init__( self , *snake_case_ , **snake_case_ ):
"""simple docstring"""
super().__init_... | 286 | 1 |
import numpy as np
def A_ ( A__ ) -> np.ndarray:
return 1 / (1 + np.exp(-vector ))
def A_ ( A__ ) -> np.ndarray:
return vector * sigmoid(A__ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 225 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase : str = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderConfig""", """VisionEncod... | 225 | 1 |
'''simple docstring'''
from __future__ import annotations
__lowerCAmelCase = 8.988e9 # units = N * m^s * C^-2
def __lowerCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) -> dict[str, float]:
_a : Tuple = ... | 89 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
_UpperCamelCase = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and must be smaller tha... | 275 | 0 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_H... | 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 |
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 lowerCAmelCase ( lowerCAmelCase... | 262 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassifica... | 262 | 1 |
"""simple docstring"""
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
_UpperCamelCase : Tuple = datasets.load_iris()
_UpperCamelCase : Union[str, Any] = np.array(data['data'])
_UpperCamelCase ... | 186 |
"""simple docstring"""
_UpperCamelCase : List[Any] = 8.31_44_62 # Unit - J mol-1 K-1
def snake_case (A_ :float , A_ :float , A_ :float ):
'''simple docstring'''
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('Invalid inputs. E... | 186 | 1 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a__ : Any ... | 349 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class UpperCAmelCase__ ( logging.LoggerAdapter):
@staticmethod
def __lowerCamelCase ( lowercase ) -> Dict:
__UpperCamelCase = PartialState()
return not main_process_... | 349 | 1 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyN... | 364 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_commo... | 254 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax... | 70 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...... | 70 | 1 |
"""simple docstring"""
import inspect
import re
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
UpperCAmelCase_ = """src/transformer... | 354 |
"""simple docstring"""
UpperCAmelCase_ : Optional[int] = 8.3_1_4_4_5_9_8
def _A (__a , __a ) -> float:
"""simple docstring"""
if temperature < 0:
raise Exception('''Temperature cannot be less than 0 K''' )
if molar_mass <= 0:
... | 318 | 0 |
'''simple docstring'''
def UpperCAmelCase ( a_ , a_ , a_ ) -> float:
"""simple docstring"""
A_ : Optional[Any] = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
return total
... | 344 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : Optional[int] = {'configuration_yolos': ['YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP', 'YolosConfig', '... | 344 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : int = logging.get_logger(__name__)
lowercase : str = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
# See all BioGPT models at https://hu... | 369 |
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : int , _lowerCamelCase : int) -> int:
'''simple docstring'''
return int((input_a, input_a).count(0) == 0)
def _SCREAMING_SNAKE_CASE ( ) -> None:
'''simple docstring'''
... | 151 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : list[str] | None = None , SCREAMING_SNAKE_CASE : dict[str, float] | None = None , SCREAMING_SNAKE_CASE ... | 46 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_... | 46 | 1 |
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_available():
import torc... | 200 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepiece
@slow #... | 200 | 1 |
from statistics import mean
import numpy as np
def _lowerCAmelCase (_lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase):
UpperCamelCase_ = 0
# Number of processes finished
UpperCamelCase_ = 0
# Displays the finished p... | 128 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Data2VecAudioConfig"""],
"""c... | 293 | 0 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ : list , lowercase__ : int | None = None , lowercase__ : int | None = None ) -> None:
'''simple docstring'''
if start is None:
lowerCAmelCas... | 1 |
"""simple docstring"""
from __future__ import annotations
__UpperCAmelCase = 1.6021e-19 # units = C
def _snake_case ( lowercase__ : float , lowercase__ : float , lowercase__ : float , ) -> tuple[str, float]:
'''simple docstring'''
... | 1 | 1 |
"""simple docstring"""
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 A__ ( datasets.BuilderConfig ):
'''simple doc... | 269 |
"""simple docstring"""
import re
def _lowercase ( __snake_case ) -> str:
if len(re.findall("[ATCG]" ,__snake_case ) ) != len(__snake_case ):
raise ValueError("Invalid Strand" )
return dna.translate(dna.maketrans("ATCG" ,"TAGC" ) )
if __name__ == "_... | 269 | 1 |
import unittest
import numpy as np
def UpperCAmelCase ( a_ , a_ , a_ , a_ = None , ) -> np.ndarray:
"""simple docstring"""
__A = np.shape(a_ )
__A = np.shape(a_ )
__A = np.shape(a_ )
... | 124 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 124 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class _lowerCamelCase ( unittest.TestCase ):
"""simple... | 186 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""google/pix2struct-textcaps-base""": (
"""https://huggingface.co/google/pix2struct-textcaps-... | 186 | 1 |
'''simple docstring'''
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
UpperCamelCase__ : Optional[Any] = Path(__file__).resolve().parents[3] / 'src'
sys.path.insert(1, str(git_... | 164 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from... | 164 | 1 |
'''simple docstring'''
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def snake_case_ (_a : str , _a : str , _a : Optional[str] = None ):
if version.parse(hfh.__version__ ).... | 34 |
'''simple docstring'''
from collections.abc import Sequence
def lowercase_ ( lowerCAmelCase__ : Sequence[float] , lowerCAmelCase__ : float ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def ... | 254 | 0 |
'''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"microsoft/xprophetnet-large-wiki100-cased": (
"https://huggingface... | 83 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase... | 83 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {'configuration_xgl... | 243 |
"""simple docstring"""
def UpperCamelCase ( UpperCAmelCase ) ->str:
"""simple docstring"""
return " ".join(
"".join(word[::-1] ) if len(UpperCAmelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
pr... | 243 | 1 |
"""simple docstring"""
from math import isqrt, loga
def __snake_case ( SCREAMING_SNAKE_CASE__ : int ) -> list[int]:
'''simple docstring'''
_UpperCAmelCase : Union[str, Any] = [True] * max_number
for i in range(2 , isqrt(max_number - ... | 202 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE__ : List[str] ) -> str:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase : Dict = [], []
while len(SCREAMING_SNAKE_CASE__ ) > 1:
_UpperCAmelCase , _Up... | 202 | 1 |
"""simple docstring"""
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pega... | 246 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {"configuration_yolos": ["YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP", "YolosConfig", "YolosOnnxConfig"]}
try:
if not is_vi... | 151 | 0 |
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_utils import ... | 20 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 20 | 1 |
import qiskit
def lowerCAmelCase_ ( _snake_case : int , _snake_case : int ) -> qiskit.result.counts.Counts:
'''simple docstring'''
__magic_name__ : int = qiskit.Aer.get_backend("aer_simulator" )
# Create a Quantum Circuit acting on the q register
__mag... | 281 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_lza, require_zsta... | 281 | 1 |
"""simple docstring"""
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : List[str] ,_lowerCamelCase : Optional[int] ,_lowerCamelCase : Union[str, Any] ,_lowerCamelCase : int ) -> int: # noqa: E741
while r - l > 1:
_l... | 126 | """simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_model... | 126 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ : list , snake_case_ : int | None = None , snake_case_ : int | None = None ) -> None:
'''simple docstring'''
if start is None:
UpperCAmelCase_... | 1 | '''simple docstring'''
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
SCREAMING_SNAKE_CASE_: Optional[int] =Lock()
def lowerCAmelCase_ ( snake_case_ : Dict , snake_case_ : Dict , snake_case_... | 1 | 1 |
'''simple docstring'''
A__ : Dict = 9.8_06_65
def a_ ( _UpperCAmelCase : Optional[int] ,_UpperCAmelCase : int ,_UpperCAmelCase : Tuple = g ) -> Optional[int]:
if fluid_density <= 0:
raise ValueError('Impossible fluid density' ... | 354 |
'''simple docstring'''
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, requi... | 0 | 0 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase :... | 124 |
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> float:
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
snake_case : Optional[Any] = sum(lowercase ) / len(lowercase ) # Calculate the average
return sum(abs(x -... | 124 | 1 |
"""simple docstring"""
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone_c... | 353 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_M... | 97 | 0 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
fro... | 164 |
'''simple docstring'''
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def _A ( lowercase__ ):
return "".join(sorted(lowercase__ ) )
def _A ( lowercase__ ):
return word_by_signature[signature(lowercase__ )]
... | 164 | 1 |
"""simple docstring"""
lowerCamelCase__ = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> ... | 310 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowerCamelCase__ = "\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\... | 310 | 1 |
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