code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
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 import ConfigTester
from ..... | 302 |
from __future__ import annotations
__a = 8.988E9 # units = N * m^s * C^-2
def a ( snake_case__: float , snake_case__: float , snake_case__: float , snake_case__: float ):
'''simple docstring'''
lowercase_ = abs(chargea * chargea )
if (forc... | 97 | 0 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMix... | 668 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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_tensor, random_attention_... | 97 | 0 |
"""simple docstring"""
def snake_case ( A__ = 1_00_00_00 ):
UpperCAmelCase_ : Any = 1
UpperCAmelCase_ : List[str] = 1
UpperCAmelCase_ : int = {1: 1}
for inputa in range(2 ,snake_case__ ):
UpperCAmelCase_ : Optional[int] = 0
Upper... | 95 |
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
require_... | 97 | 0 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def __UpperCAmelCase ( __a : str ) -> Optional[int]:
"""simple docstring"""
return "".join(sorted(snake_case__ ) )
def __UpperCAmelCase ( __a :... | 14 |
def a ( snake_case__: int ):
'''simple docstring'''
if not isinstance(snake_case__ , snake_case__ ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divisor for di... | 97 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterM... | 281 |
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
__a = namedtuple(
'_TestCommandArgs',
[
'dataset',
... | 97 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a :int = logging.get_logger(__name__)
a :int = {
"facebook/wav2vec2-base-960h": "https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/co... | 680 |
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def a ( snake_case__: List[Any] ):
'''simple docstring'''
if "cls_token" in name:
lowercase_ = name.replace(... | 97 | 0 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__=5 ):
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
_UpperCAm... | 657 |
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 .tokenization_bar... | 97 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf... | 209 |
from __future__ import annotations
from math import pi, sqrt
def a ( snake_case__: float , snake_case__: float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance <= 0:
rais... | 97 | 0 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class __magic_name__ ( lowerCamelCase__ ):
"""simple docstring"... | 454 |
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 = {
'xlm-mlm-en-2048': 'https://huggingface.co/xlm-mlm-en-2048/re... | 97 | 0 |
"""simple docstring"""
from timeit import timeit
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
if number < 0:
raise ValueError("""the value of input must not be negative""" )
snake_case_ : Dict = ... | 480 |
import os
# Precomputes a list of the 100 first triangular numbers
__a = [int(0.5 * n * (n + 1)) for n in range(1, 1_0_1)]
def a ( ):
'''simple docstring'''
lowercase_ = os.path.dirname(os.path.realpath(snake_case__ ) )
lowercase_ = os.path.join(sna... | 97 | 0 |
"""simple docstring"""
import functools
from typing import Any
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase ) -> Tuple:
"""simple docstring"""
if not isinstance(snake_case__ , snake_case__ ) or len(snake_case__ ) == 0:
raise ValueError("the string sh... | 610 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('''dataset_size''' , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize('''input_in_memory_max_size''' , ['''default''', 0, 100 * 2**20, 900 * 2**20] )
def a ( ... | 97 | 0 |
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 (
center_crop,
get... | 302 |
import unittest
from knapsack import knapsack as k
class lowercase__( unittest.TestCase ):
"""simple docstring"""
def _lowercase ( self : Optional[int] ) -> str:
lowercase_ = 0
lowercase_ = [0]
lowercase_ = [0]
lowercase_ ... | 97 | 0 |
from __future__ import annotations
def lowerCAmelCase_ (lowercase__ : int , lowercase__ : int ) -> Any:
'''simple docstring'''
if partitions <= 0:
raise ValueError('''partitions must be a positive number!''' )
if partitions > number_... | 668 |
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'vocab_file': 'vocab.json',
'tokenizer_config_file': 'tokenizer_config.json',... | 97 | 0 |
"""simple docstring"""
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_c... | 95 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
class lowercase__( UpperCAmelCase ):
"""simple docstring"""
a :List[str] = 'encoder-decoder'
a :Any = Tr... | 97 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqLM,
... | 14 |
from __future__ import annotations
def a ( snake_case__: Optional[int] , snake_case__: Optional[int] , snake_case__: Any , snake_case__: Optional[int] ): # noqa: E741
'''simple docstring'''
while r - l > 1:
lowercase_ = (l + r) // 2
if v[m] >=... | 97 | 0 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__magic_name__ : int = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import che... | 281 |
__a = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'
def a ( snake_case__: bytes ):
'''simple docstring'''
# Make sure the supplied data is a bytes-like object
if not isinstance(snake_case__ , snake_case__ ):
lowercase_ = F'''... | 97 | 0 |
"""simple docstring"""
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
a :List[str] = logging.get_logger(__name__)
a :Optional[int] = ... | 680 |
from __future__ import annotations
def a ( snake_case__: list[list[int]] ):
'''simple docstring'''
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in rang... | 97 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sent... | 657 |
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
__a = logging.get_logger(__name__)
__a = '▁'
__a = {'vocab_file':... | 97 | 0 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
UpperCamelCase_ = [int(0.5 * n * (n + 1)) for n in range(1, 1_01)]
def lowerCamelCase ( ) -> str:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :List[str] = os.path.d... | 209 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'facebook/wav2vec2-base-960h': 'https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/config.json',
# See al... | 97 | 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
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
@requi... | 454 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def a ( snake_case__: Any ... | 97 | 0 |
'''simple docstring'''
lowercase__ : List[Any] = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\... | 98 |
'''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, slow, ... | 98 | 1 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DE... | 98 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_fl... | 98 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
_snake_case : Any = ['image_processor', 'tokenizer'... | 98 |
'''simple docstring'''
def a__ ( lowercase : str ) -> int:
"""simple docstring"""
assert column_title.isupper()
_UpperCamelCase = 0
_UpperCamelCase = len(lowercase ) - 1
_UpperCamelCase = 0
while index >=... | 98 | 1 |
'''simple docstring'''
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
class ... | 98 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_token... | 98 | 1 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list[list[int]] ) -> int:
"""simple docstring"""
for i in range(1, len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in... | 98 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_... | 98 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
_snake_case : str
_snake_case : int
def a__ ( lowercase : str ) -> list... | 98 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : int ) -> float:
"""simple docstring"""
_UpperCamelCase = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
... | 98 | 1 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list, lowercase : int ) -> List[Any]:
"""simple docstring"""
if len(lowercase ) <= 1 or n <= 1:
return
insert_next(lowercase, n - 1 )
rec_insertion_sort(low... | 98 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__magic_name__ ):
"""simple docstring"""
_snake_case : Dict = ['transformers', 'torch', 'note_seq']
def __init__( self : Tuple ... | 98 | 1 |
'''simple docstring'''
def a__ ( lowercase : str ) -> int:
"""simple docstring"""
assert column_title.isupper()
_UpperCamelCase = 0
_UpperCamelCase = len(lowercase ) - 1
_UpperCamelCase = 0
while index >=... | 98 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ : int = argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False)
parser.add_argu... | 98 | 1 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : float, lowercase : float ) -> float:
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def a__ ( lowercase : float, lowercase : float, lowercase : ... | 98 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Tuple = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Opti... | 98 | 1 |
'''simple docstring'''
import math
import flax.linen as nn
import jax.numpy as jnp
def a__ ( lowercase : jnp.ndarray, lowercase : int, lowercase : float = 1, lowercase : float = 1, lowercase : float = 1.0e4, lowercase : bool = False, lowercase : float = 1.0, ) ... | 98 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowercase__ : str = '\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Sa... | 98 | 1 |
'''simple docstring'''
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
lowercase__ : Union[str, Any] = 0
lowercase__ : Optional[Any] = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are ob... | 98 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impor... | 98 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ : Any = {
'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}
try:
... | 98 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : str ) ... | 98 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowercase__ : Tuple = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvai... | 98 |
'''simple docstring'''
from __future__ import annotations
import queue
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : str , lowerCAmelCase__ : Optional[int] ) -> str:
'''simple docstring'''
_UpperCamelC... | 98 | 1 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def a__ ( lowercase : Union[str, Any] ) -> Optional[int]:
"""simple docstring"""
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
... | 98 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def a__ ( ) -> Tuple:
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as... | 98 | 1 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def a__ ( lowercase : str = "", ) -> bool:
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(''' ''', '''''' ).lower() ).values() ) < 2
def a__... | 98 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 98 | 1 |
'''simple docstring'''
# 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... | 98 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stabl... | 98 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.u... | 98 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list, lowercase : int ) -> List[Any]:
"""simple docstring"""
if len(lowercase ) <= 1 or n <= 1:
return
insert_next(lowercase, n - 1 )
rec_insertion_sort(low... | 98 | 1 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def a__ ( lowerca... | 98 |
'''simple docstring'''
# 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... | 98 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[str] = logging.get_logger(__name__)
lowercase__ : Tuple = {
'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
... | 98 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.dat... | 98 | 1 |
'''simple docstring'''
lowercase__ : List[str] = 'Alexander Joslin'
import operator as op
from .stack import Stack
def a__ ( lowercase : str ) -> int:
"""simple docstring"""
_UpperCamelCase = {'''*''': op.mul, '''/''': op.truediv, ''... | 98 |
'''simple docstring'''
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : Any = ... | 98 | 1 |
'''simple docstring'''
import inspect
import unittest
from math import floor
from transformers import CvtConfig
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_conf... | 98 |
'''simple docstring'''
def a__ ( lowercase : Dict, lowercase : Optional[Any] ) -> int:
"""simple docstring"""
_UpperCamelCase = 0
_UpperCamelCase = len(lowercase ) - 1
while left <= right:
# avoid divided by 0 durin... | 98 | 1 |
'''simple docstring'''
lowercase__ : Optional[int] = 2_56
# Modulus to hash a string
lowercase__ : Any = 1_00_00_03
def a__ ( lowercase : str, lowercase : str ) -> bool:
"""simple docstring"""
_UpperCamelCase = len(low... | 98 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DE... | 98 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta i... | 98 |
'''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, slow, ... | 98 | 1 |
'''simple docstring'''
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
fro... | 98 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_fl... | 98 | 1 |
'''simple docstring'''
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration... | 98 |
'''simple docstring'''
def a__ ( lowercase : str ) -> int:
"""simple docstring"""
assert column_title.isupper()
_UpperCamelCase = 0
_UpperCamelCase = len(lowercase ) - 1
_UpperCamelCase = 0
while index >=... | 98 | 1 |
'''simple docstring'''
from PIL import Image
def a__ ( lowercase : Image ) -> Image:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase = image.size
_UpperCamelCase = 0
_UpperCamelCase = ima... | 98 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_token... | 98 | 1 |
'''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,
require_tokenizers... | 98 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_... | 98 | 1 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : str = {
'google/umt5-small': 'htt... | 98 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : int ) -> float:
"""simple docstring"""
_UpperCamelCase = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
... | 98 | 1 |
'''simple docstring'''
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def a__ ( ... | 98 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__magic_name__ ):
"""simple docstring"""
_snake_case : Dict = ['transformers', 'torch', 'note_seq']
def __init__( self : Tuple ... | 98 | 1 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def a__ ( lowercase : int, lowercase : Un... | 98 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ : int = argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False)
parser.add_argu... | 98 | 1 |
'''simple docstring'''
from __future__ import annotations
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : str , lowerCAmelCase__ : int = 0 ) -> Dict:
'''simple docstring'''
_UpperCamelCase = ... | 98 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Tuple = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Opti... | 98 | 1 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import... | 98 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowercase__ : str = '\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Sa... | 98 | 1 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : Optional[int] ) -> List[str]:
'''simple docstring'''
... | 98 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impor... | 98 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pr... | 98 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : str ) ... | 98 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testi... | 98 |
'''simple docstring'''
from __future__ import annotations
import queue
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : str , lowerCAmelCase__ : Optional[int] ) -> str:
'''simple docstring'''
_UpperCamelC... | 98 | 1 |
'''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_availab... | 98 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def a__ ( ) -> Tuple:
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as... | 98 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowercase__ : Any = False
class __lowerCAmelCase ( unitte... | 98 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 98 | 1 |
'''simple docstring'''
from manim import *
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def snake_case__ ( self : Dict ) -> Dict:
'''simple docstring'''
_UpperCamelCase = Rectangle(height=0.... | 98 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stabl... | 98 | 1 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ : int = argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False)
parser.add_argu... | 98 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list, lowercase : int ) -> List[Any]:
"""simple docstring"""
if len(lowercase ) <= 1 or n <= 1:
return
insert_next(lowercase, n - 1 )
rec_insertion_sort(low... | 98 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Dict = {
'configuration_gpt_bigcode': ['GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTBigCodeConfig'],
}
try:
if no... | 98 |
'''simple docstring'''
# 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... | 98 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def a__ ( lowercase : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 98 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.dat... | 98 | 1 |
'''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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IM... | 98 |
'''simple docstring'''
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : Any = ... | 98 | 1 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction... | 98 |
'''simple docstring'''
def a__ ( lowercase : Dict, lowercase : Optional[Any] ) -> int:
"""simple docstring"""
_UpperCamelCase = 0
_UpperCamelCase = len(lowercase ) - 1
while left <= right:
# avoid divided by 0 durin... | 98 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lowercase__ : int = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/c... | 98 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DE... | 98 | 1 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_configuration_common import... | 98 |
'''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, slow, ... | 98 | 1 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
lowercase__ : Optional[int] = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that devel... | 98 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_fl... | 98 | 1 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase__ : Optional[Any] = '\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},... | 98 |
'''simple docstring'''
def a__ ( lowercase : str ) -> int:
"""simple docstring"""
assert column_title.isupper()
_UpperCamelCase = 0
_UpperCamelCase = len(lowercase ) - 1
_UpperCamelCase = 0
while index >=... | 98 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from .... | 98 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_token... | 98 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
lo... | 98 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_... | 98 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
... | 98 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : int ) -> float:
"""simple docstring"""
_UpperCamelCase = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
... | 98 | 1 |
'''simple docstring'''
def a__ ( lowercase : int ) -> int:
"""simple docstring"""
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def a__ ( lowercase : int ) -> bool:
"""simple docstring"""
_UpperCamelCa... | 98 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__magic_name__ ):
"""simple docstring"""
_snake_case : Dict = ['transformers', 'torch', 'note_seq']
def __init__( self : Tuple ... | 98 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_... | 98 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ : int = argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False)
parser.add_argu... | 98 | 1 |
'''simple docstring'''
import qiskit
def a__ ( lowercase : int, lowercase : int ) -> qiskit.result.counts.Counts:
"""simple docstring"""
_UpperCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
_UpperCamelCase = qiski... | 98 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Tuple = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Opti... | 98 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class __lowerCAmelCase ( u... | 98 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowercase__ : str = '\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Sa... | 98 | 1 |
'''simple docstring'''
from math import factorial
lowercase__ : dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def a__ ( lowercase : int ) -> int:
"""simple docstring"""
if not isinstance(lowercase, lowercase ):
r... | 98 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impor... | 98 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 98 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : str ) ... | 98 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.ut... | 98 |
'''simple docstring'''
from __future__ import annotations
import queue
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : str , lowerCAmelCase__ : Optional[int] ) -> str:
'''simple docstring'''
_UpperCamelC... | 98 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer, TF... | 98 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def a__ ( ) -> Tuple:
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as... | 98 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
lowercase__ : List[str] = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
de... | 98 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 98 | 1 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.dat... | 98 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stabl... | 98 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Generic, TypeVar
lowercase__ : Any = TypeVar('T')
class __lowerCAmelCase ( Generic[T] ):
"""simple docstring"""
def __init__( self : int , lowerCAmelCase__ : ... | 98 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list, lowercase : int ) -> List[Any]:
"""simple docstring"""
if len(lowercase ) <= 1 or n <= 1:
return
insert_next(lowercase, n - 1 )
rec_insertion_sort(low... | 98 | 1 |
'''simple docstring'''
import numpy as np
import qiskit
def a__ ( lowercase : int = 8, lowercase : int | None = None ) -> str:
"""simple docstring"""
_UpperCamelCase = np.random.default_rng(seed=lowercase )
# Roughly 25% of the qubits wil... | 98 |
'''simple docstring'''
# 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... | 98 | 1 |
'''simple docstring'''
def a__ ( lowercase : Dict, lowercase : Optional[Any] ) -> int:
"""simple docstring"""
_UpperCamelCase = 0
_UpperCamelCase = len(lowercase ) - 1
while left <= right:
# avoid divided by 0 durin... | 98 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.dat... | 98 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lowercase__ : Dict = {
'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.j... | 98 |
'''simple docstring'''
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
lowercase__ : int = logging.get_logger(__name__)
lowercase__ : Any = ... | 98 | 1 |
'''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
#
... | 98 |
'''simple docstring'''
def a__ ( lowercase : Dict, lowercase : Optional[Any] ) -> int:
"""simple docstring"""
_UpperCamelCase = 0
_UpperCamelCase = len(lowercase ) - 1
while left <= right:
# avoid divided by 0 durin... | 98 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ : Any = {
'configuration_poolformer': [
'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'PoolFormerConfig',... | 98 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DE... | 98 | 1 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : str ) ... | 98 |
'''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, slow, ... | 98 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : List[str] = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
tr... | 98 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_fl... | 98 | 1 |
'''simple docstring'''
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowercase__ : List[str] = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.se... | 98 |
'''simple docstring'''
def a__ ( lowercase : str ) -> int:
"""simple docstring"""
assert column_title.isupper()
_UpperCamelCase = 0
_UpperCamelCase = len(lowercase ) - 1
_UpperCamelCase = 0
while index >=... | 98 | 1 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stabl... | 98 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_token... | 98 | 1 |
'''simple docstring'''
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class __lowerCAmelCase ( ... | 98 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_... | 98 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ : List[str] = {
'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
'toke... | 98 |
'''simple docstring'''
def a__ ( lowercase : int, lowercase : int, lowercase : int ) -> float:
"""simple docstring"""
_UpperCamelCase = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
... | 98 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_... | 98 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__magic_name__ ):
"""simple docstring"""
_snake_case : Dict = ['transformers', 'torch', 'note_seq']
def __init__( self : Tuple ... | 98 | 1 |
'''simple docstring'''
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTok... | 98 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ : int = argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False)
parser.add_argu... | 98 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__magic_name__ ):
"""simple docstring"""
_snake_case : Dict = ['transformers', 'torch', 'note_seq']
def __init__( self : Tuple ... | 98 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Tuple = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Opti... | 98 | 1 |
'''simple docstring'''
import random
def a__ ( lowercase : list, lowercase : Union[str, Any] ) -> tuple:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase , _UpperCamelCase = [], [], []
for element in data:
... | 98 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowercase__ : str = '\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Sa... | 98 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def a__ ( lowercase : Sequence[int] | None = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError('''Input sequence should not be empty''' )
_UpperCamelCase... | 98 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impor... | 98 | 1 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def a__ ( lowercase : int, lowercase : int, lowercase : int, lowercase : int, lowercase : int, lowercase : int ) -> np.ndarray:
... | 98 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self : str ) ... | 98 | 1 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowercase__ : Dict = da... | 98 |
'''simple docstring'''
from __future__ import annotations
import queue
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : str , lowerCAmelCase__ : Optional[int] ) -> str:
'''simple docstring'''
_UpperCamelC... | 98 | 1 |
'''simple docstring'''
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_modelin... | 98 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def a__ ( ) -> Tuple:
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as... | 98 | 1 |
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