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 |
|---|---|---|---|---|
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
snake_case : List[str] = get_tests_d... | 94 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_acceler... | 94 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_: str ={
'configuration_speecht5': [
'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 356 | '''simple docstring'''
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class __A :
@property
def _lowercase (self : int ... | 106 | 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
... | 17 |
"""simple docstring"""
# 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/LICENS... | 173 | 0 |
"""simple docstring"""
def _lowerCamelCase( lowercase__ ) -> list[int]:
'''simple docstring'''
__lowercase= len(lowercase__ )
for i in range(lowercase__ ):
for j in range(i + 1 , lowercase__ ):
if numbers[j] < numbers[i]:
__lowercase, ... | 367 |
from __future__ import annotations
import numpy as np
def _lowerCamelCase( lowercase__ ) -> str:
'''simple docstring'''
return np.maximum(0 , lowercase__ )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 304 | 0 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_SCREAMING_SNAKE_CASE )
class lowerCamelCase (_SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase__ = field(default... | 118 |
"""simple docstring"""
from __future__ import annotations
import math
def _A ( lowercase ):
"""simple docstring"""
if num <= 0:
a =f'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(lowercase )
a =[Tr... | 81 | 0 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, ... | 335 |
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
... | 335 | 1 |
"""simple docstring"""
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_co... | 249 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_mode... | 141 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokeniz... | 353 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCamelCase = {
"configuration_conditional_detr": [
"CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MA... | 13 | 0 |
'''simple docstring'''
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_ge... | 47 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCamelCase : Optional[Any] = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
... | 106 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : Any = logging.get_logger(__name__)
A_ : Optional[int] = {
"facebook/data2vec-text-base": "https://huggingface.co... | 351 |
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class _a (__magic_name__ ):
'''simple docstring'''
UpperCAmelCase__: Optional[Any] = '''MCTCTFeatureExtractor'''
UpperCAmelCase__: Optional[int] = '''... | 141 | 0 |
def _A ( _lowercase , _lowercase ) -> bool:
"""simple docstring"""
__UpperCamelCase = len(_lowercase )
__UpperCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0)... | 310 |
'''simple docstring'''
def __UpperCAmelCase ( A : int ) -> list:
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError('''The given input must be positive''' )
# get the generated string sequence
UpperCAmelCase_ : int = gr... | 304 | 0 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test... | 328 |
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,
AutoTokeniz... | 328 | 1 |
"""simple docstring"""
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
SCREAMING_SNAKE_CASE_ : Dict = {
'n_samples': 6_4,
'horizon': 3_2,
'num_inference_steps': 2_0,
'n_guide_steps': 2, # can set to 0 for faster ... | 335 |
"""simple docstring"""
class a :
"""simple docstring"""
def __init__( self: Dict ):
"""simple docstring"""
A__ = {}
def UpperCamelCase ( self: List[str] ):
"""simple docstring"""
... | 335 | 1 |
'''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_tf, require_torch... | 184 |
'''simple docstring'''
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def _SCREAMING_SNAKE_CASE ( UpperCamelCase , UpperCamelCase = True , UpperCamelCase = math.inf , UpperCamelCase = -math.inf , UpperCamelCase = math.inf ... | 184 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import rand... | 70 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCAmelCase : Union[str, Any] = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
"""attn""": """attenti... | 13 | 0 |
'''simple docstring'''
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/c... | 104 |
'''simple docstring'''
from __future__ import annotations
def _A (lowerCAmelCase__ :int ) -> list[int]:
'''simple docstring'''
_a = 2
_a = []
while i * i <= n:
if n % i:
i += 1
... | 104 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import... | 86 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : Union[str, Any]=2_81_23 ):
'''simple docstring'''
__lowercase =[1] * (limit + 1)
for i in range(2, int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1, l... | 141 | 0 |
'''simple docstring'''
def a_ ( lowerCamelCase : int , lowerCamelCase : float , lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def a_ ( lowerCamelCase : float , lowerCamelCase : floa... | 55 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common im... | 55 | 1 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowercase__ : Optional[int] = "\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n ... | 328 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
from a... | 328 | 1 |
'''simple docstring'''
__UpperCAmelCase :dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.60_9344,
"knot": 1.852,
}
__UpperCAmelCase :dict[str, float] = {
"km/h": 1.0,
"m/s": 0.2_7777_7778,
"mph": 0.6_2137_1192,
"knot": 0.5... | 367 |
'''simple docstring'''
def _a ( _lowercase : int = 600851475143 ):
'''simple docstring'''
try:
__UpperCAmelCase : str = int(_lowercase )
except (TypeError, ValueError):
raise TypeError('''Parameter n must b... | 240 | 0 |
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_attent... | 184 |
import math
import os
import sys
def lowercase_ ( _A : str ):
"""simple docstring"""
lowerCamelCase__ : str = ""
try:
with open(_A , "rb" ) as binary_file:
lowerCamelCase__ : Union[str, Any] = binary_... | 184 | 1 |
'''simple docstring'''
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils ... | 91 |
'''simple docstring'''
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils ... | 91 | 1 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from numpy import array
def _A ( A__ ):
"""simple docstring"""
__lowercase = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works for 2x... | 104 |
'''simple docstring'''
def _A ( A__ = 10 , A__ = 22 ):
"""simple docstring"""
__lowercase = range(1 , A__ )
__lowercase = range(1 , A__ )
return sum(
1 for power in powers for base in bases if len(str(base**power ) ) == pow... | 104 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_:Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_:List[str] = {
"""microsoft/unispeech-large-1500h-cv""": (
"""https://huggingfac... | 115 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __UpperCamelCase ( ) -> Dict:
"""simple docstring"""
A : str = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
A : int = ... | 115 | 1 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
a_ : Union[str, Any] = TypeVar("""KEY""")
a_ : Tuple = TypeVar("""VAL""")
@dataclass(frozen=lowercase , slots=lowercase )... | 55 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class snake_case ( l... | 55 | 1 |
"""simple docstring"""
from __future__ import annotations
def _A (__a , __a ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = get_failure_array(__a )
# 2) Step through text searching for pattern
SCREAMING_SNAKE_CASE_ , ... | 318 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffus... | 318 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__A : List[str] = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 33 |
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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
fro... | 240 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
'facebook/convnextv2-tiny-1k-224': 'https://hugg... | 366 |
def lowerCAmelCase_ ( UpperCamelCase_ ) -> int:
UpperCamelCase_ = len(UpperCamelCase_ )
UpperCamelCase_ = len(matrix[0] )
UpperCamelCase_ = min(UpperCamelCase_ , UpperCamelCase_ )
for row in range(UpperCamelCase... | 328 | 0 |
"""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_ba... | 91 |
"""simple docstring"""
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, ... | 91 | 1 |
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
if not arr:
return None, None, ... | 357 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def lowerCAmelCase_ ( __lowerCamelCase ):
__snake_case : Any = []
__snake_case : Optional[Any] = ... | 134 | 0 |
"""simple docstring"""
from collections.abc import Callable
def lowerCamelCase ( _UpperCamelCase : Callable[[float], float] , _UpperCamelCase : float , _UpperCamelCase : float ) -> float:
'''simple docstring'''
__UpperCAmelCase :... | 115 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class lowerCamelCase__ ( ctypes.Structure ):
"""simple docstring"""
__a = ... | 115 | 1 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _A ( _a : Callable , _a : float , _a : float , _a : float , _a : float ):
"""simple docstring"""
A = int... | 77 |
"""simple docstring"""
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ) -> Any:
A = 0
A = 0
A = {}
def UpperCamelCase__ ( self ,lowerCamelCase_ ) ... | 77 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowercase : Tuple = logging.get_logger(__name__)
__lowercase : Tuple = {
'''fac... | 318 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : str = logging.get_logger(__name__)
__lowercase : Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __lowercase ( _lowercas... | 318 | 1 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
__a :List[str] = logging.get_logger(__name__)
class _a ( snake_case_ ):
"""simple docstring"""
def __init__( self : str , *UpperCAmelCase : ... | 329 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
__a :Optional[Any] = logging.get_logger(__name__)
class _a ( snake_case_ ):
"""simple docstring"""
def __init__( self : List[str] , *UpperCAmelCas... | 329 | 1 |
def __snake_case ( __UpperCamelCase : int ,__UpperCamelCase : list[int] ,__UpperCamelCase : int ):
"""simple docstring"""
def count_of_possible_combinations(__UpperCamelCase : int ) -> int:
if target < 0:
... | 312 |
import math
def A_ ( snake_case : int ) -> bool:
'''simple docstring'''
return math.sqrt(snake_case ) * math.sqrt(snake_case ) == num
def A_ ( snake_case : int ) -> bool:
'''simple docstring'''
... | 328 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from... | 357 |
'''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 ...t... | 311 | 0 |
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase__ : List[str] = logging.getLogger(__name__)
class UpperCAmelCase ( lowercase_ ):
'''simple docstring'''
lowerCAmelCase_ = '''masked_bert'''
... | 187 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case : Union[str, Any] = logging.get_logger(__name__)
__snake_case : int = {
... | 134 | 0 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCAmelCase( __lowerCamelCase , __lowerCamelCase = "cpu" , __lowerCamelCase = None ):
__a = torch.load(__a , map_location=__a )
for k, v in tqdm(state_dict.items() ):
... | 350 | def lowerCAmelCase( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
# Return True if there is node that has not iterated.
__a = [False] * len(__lowerCamelCase )
__a = []
queue.append(__lowerCamelCase )
... | 197 | 0 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 77 | """simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 77 | 1 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {'''vocab_file''': '''vocab.json'''}
_UpperCamelCase = {
... | 365 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transfo... | 335 | 0 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
lowerCAmelCase__ :str = logging.get_logger(__name__)
def lowerCAmelCase__ ( a__: Any ... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( A_ , A_ ):
while second != 0:
lowerCAmelCase__ : List[Any] = first & second
first ^= second
lowerCAmelCase__ : Optional[Any] = c << 1
return first
if __name__ == "__main__":
import doctest
... | 74 |
"""simple docstring"""
from __future__ import annotations
import math
__UpperCamelCase : Dict = '''2020.9.26'''
__UpperCamelCase : Tuple = '''xcodz-dot, cclaus, dhruvmanila'''
def __SCREAMING_SNAKE_CASE ( A_ , A_ , A_ , A_ , A_ ):
if n... | 74 | 1 |
import re
from ..utils import cached_file
# docstyle-ignore
_lowercase : str ="\nHuman: <<task>>\n\nAssistant: "
_lowercase : int ="huggingface-tools/default-prompts"
_lowercase : List[str] ={"chat": "chat_prompt_template.txt", "run": "run_prompt_template.txt"}
de... | 170 |
'''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def lowercase ( __magic_name__ ):
'''simple docstring'''
for param in module.parameters():
UpperCAmelCase : Any = False
def lowercase ... | 311 | 0 |
'''simple docstring'''
def __lowercase ( __lowercase , __lowercase ) -> bool:
'''simple docstring'''
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 368 |
'''simple docstring'''
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, TensorFlowBe... | 174 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
... | 84 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : List[Any] =logging.get_logger(__name__)
__lowerCAmelCase : Union[str, Any] ={
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-J... | 197 | 0 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...ut... | 371 |
from collections import defaultdict
from math import ceil, sqrt
def lowercase__ ( __snake_case : int = 1_000_000 , __snake_case : int = 10 ):
'''simple docstring'''
UpperCAmelCase_ : defaultdict = defaultdict(__snake_case )
... | 145 | 0 |
'''simple docstring'''
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
f... | 158 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE_ : str = parse(importlib.metadata.version('torch'))
def _snake_case ( Uppe... | 335 | 0 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self : Optional[Any] ) -> None:
_UpperCamelCase = {} # Mapping from char to TrieNode
_UpperCamelCase = False
def _UpperCamelCase ( self : List[str] , ... | 54 | """simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nest... | 54 | 1 |
"""simple docstring"""
from math import pow, sqrt
def _snake_case ( *snake_case__ : float ):
A = len(snake_case__ ) > 0 and all(value > 0.0 for value in values )
return result
def _snake_case ( snake_case__ : float , snake_case__ : float ... | 74 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowercase = {'''configuration_deit''': ['''DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeiTConfig''... | 74 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
_A = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""SPEECHT5_PRETRAINED_HIFIGA... | 369 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_A = {
"""configuration_layoutlmv3""": [
"""LAYOUTLMV3_P... | 166 | 0 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nic... | 103 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : Optional[Any] = {
"""config... | 174 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
... | 371 |
'''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,
)
fr... | 3 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_utils_ba... | 18 | '''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class A__ :
"""simple docstring"""
def __init__( self : Any , lowerCAmelCase__ : Any ) -> Dict:
"""simple docstring"""
_UpperCAmelCase ... | 145 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def UpperCAmelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase = 100 , ) -> Optional[int]:
snake_case_ = x_start
snake_case_ = fnc(lowerCamelCase_ )
... | 358 | """simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 312 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import ... | 54 |
"""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
a__ : Tuple = False
class UpperCamelCase_ ( unittest.Test... | 54 | 1 |
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowerCAmelCase_ = [
# tf -> hf
('''/''', '''.'''),
('''layer_''', '''layers.'''),
('''kernel''', '''wei... | 279 |
import random
from .binary_exp_mod import bin_exp_mod
def lowerCamelCase_ ( _UpperCamelCase , _UpperCamelCase=1_000 ) -> str:
"""simple docstring"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
snake_case_ ... | 279 | 1 |
import unittest
from typing import Dict, List, Optional, Union
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_i... | 103 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}... | 166 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.t... | 250 |
import sys
def _a ( lowerCamelCase: Tuple ) -> Tuple:
'''simple docstring'''
__A = len(lowerCamelCase )
__A = [[0 for x in range(lowerCamelCase )] for x in range(lowerCamelCase )]
__A = [... | 250 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .to... | 44 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
'''simple docstring'''
A : str = BeautifulSoup(requests.get(snake_case__ , params=snake_case__ ).content ... | 3 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case_ = {
"""configuration_bigbird_pegasus""": [
"""BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BigBirdPegasusCo... | 181 |
"""simple docstring"""
def _lowerCAmelCase ( ):
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def _lowerCAmelCase ( lowercase_ ):
UpperCAmelCase = 1
UpperCAmelCase = 2
while i * i <= n:
UpperC... | 181 | 1 |
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,
)
if is_sentencepiece_available():
from ..ta.t... | 0 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Pa... | 312 | 0 |
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 GenerationTesterMixin
from ...test_modeling_com... | 306 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel... | 306 | 1 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class __lowerCAmelCase ( unittest.Test... | 279 |
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... | 279 | 1 |
"""simple docstring"""
def a__ ( __SCREAMING_SNAKE_CASE ) -> float:
if not nums: # Makes sure that the list is not empty
raise ValueError("List is empty" )
__lowerCAmelCase: Optional[int] = sum(__SCREAMING_SNAKE_CASE ) / len(__SCREAMING_SNAKE_CASE ) # Calculate ... | 364 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available()... | 108 | 0 |
'''simple docstring'''
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib im... | 250 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class a__ ( unittest.TestCase ):
def _lowerCamelCase ( self ):
"""simple docstring"""
_lowercase : ... | 250 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
snake_case : List[str] = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
... | 281 |
import math
def __lowerCamelCase ( UpperCAmelCase_ : float , UpperCAmelCase_ : float ):
"""simple docstring"""
return math.pow(UpperCAmelCase_ , 2 ) - a
def __lowerCamelCase ( UpperCAmelCase_ : float ):
"""simple docstring"""... | 281 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ = {'''configuration_reformer''': ['''REFORMER_PRET... | 181 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
UpperCamelCase__ = True
except (ImportError, ModuleNotFoundError):
UpperCamelCase__ = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', qu... | 181 | 1 |
def __lowerCamelCase ( snake_case__ = 1 ,snake_case__ = 10_00 ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = 1
_SCREAMING_SNAKE_CASE = 0
for divide_by_number in range(UpperCAmelCase_ ,digit + 1 ):
_SCREAMING_SNA... | 357 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase = {
'''configuration_layoutlmv3''': [
'''L... | 125 | 0 |
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
_SCREAMING_SNAKE_CASE = TypeVar("""KT""")
_SCREAMING_SNAKE_CASE = TypeVar("""VT""")
class SCREAMING_SNAKE_CASE_ ( Generic[KT, VT] ):
def __init__( sel... | 327 |
from __future__ import annotations
import math
def UpperCamelCase ( __magic_name__ : list , __magic_name__ : list ) -> list:
"""simple docstring"""
if len(__magic_name__ ) != 2 or len(a[0] ) != 2 or len(__magic_name__ ) != 2 or len(b[... | 305 | 0 |
"""simple docstring"""
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@datac... | 357 |
def lowerCamelCase_ ( _UpperCamelCase ) -> int:
"""simple docstring"""
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise ValueError('''multiplicative_persistence() only accepts integral values''' )
if num < 0:
raise ValueError('''multipl... | 279 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case = {
"configuration_swinv2": ["SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Swinv2Config"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvaila... | 26 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-... | 108 | 0 |
'''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
de... | 237 | '''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-2.0
... | 237 | 1 |
import warnings
from ..trainer import Trainer
from ..utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
class _snake_case ( snake_case ):
def __init__( self , _a=None , **_a ):
warnings.warn(
"`SageMakerTrainer... | 281 |
def lowerCAmelCase_ ( _snake_case : str , _snake_case : str ) -> bool:
'''simple docstring'''
__magic_name__ : Union[str, Any] = len(_snake_case ) + 1
__magic_name__ : List[str] = len(_snake_case ) + 1
# dp is a 2d matrix where dp[i][j] denotes wh... | 281 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.te... | 241 |
"""simple docstring"""
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .m... | 241 | 1 |
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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
UpperCamelCa... | 92 |
'''simple docstring'''
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor... | 125 | 0 |
"""simple docstring"""
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqd... | 353 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __magic_name__ (__lowercase ):
lowerCamelCase__ = ['''image_processor''', '''tokenizer''']
lowerCamelCase__ = '''ViTImageProcessor'''
lowerCamel... | 22 | 0 |
import unittest
import numpy as np
def a ( snake_case__: Optional[Any] , snake_case__: List[str] , snake_case__: List[Any] , snake_case__: Any = None , ):
'''simple docstring'''
lowercase_ = np.shape(_UpperCamelCase )
... | 30 |
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
lowerCAmelCase_ = {
'''linear''': PIL.Image.Resampling.BILINEAR,
'''bilinear''': PIL.Image.Resampling.BILINEAR,
... | 279 | 0 |
'''simple docstring'''
from numpy import exp, pi, sqrt
def __a ( _UpperCamelCase: Union[str, Any] , _UpperCamelCase: float = 0.0 , _UpperCamelCase: float = 1.0 ) -> int:
"""simple docstring"""
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) **... | 357 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _a ( __lowerCAmelCase ... | 142 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Tuple =logging.get_logger(__name__)
__lowerCAmelCase : Any ={
"microsoft/unispeech-sat-base-100h-libri-ft": (
"https://huggin... | 237 |
'''simple docstring'''
def UpperCamelCase ( _lowerCamelCase : int | float | str ):
try:
A__ = float(_lowerCamelCase )
except ValueError:
raise ValueError("Please enter a valid number" )
A__ = decimal - int(_lowerCamelCase )
... | 237 | 1 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
__UpperCamelCase : Any = '''
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-valu... | 363 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( A_ ):
if not isinstance(A_ , A_ ):
lowerCAmelCase__ : int = f'Input value of [number={number}] must be an integer'
raise TypeError(A_ )
if number < 0:
return False
lowerCAmelCase__ : List[Any] = ... | 74 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Token... | 241 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
# TODO Update this
lowercase__ = {
"""facebook/esm-1b""": """https://... | 241 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
A__ : Tuple ={'''processing_wav2vec2_with_lm''': ['''Wav2Vec2ProcessorWithLM''']}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM... | 367 |
'''simple docstring'''
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
A__ : str =5_00_00
A__ : Optional[int] =50_00
A__ , A__ : Optional[int] ... | 220 | 0 |
"""simple docstring"""
def _lowercase ( __snake_case ) -> str:
if isinstance(__lowercase ,__lowercase ):
raise TypeError("'float' object cannot be interpreted as an integer" )
if isinstance(__lowercase ,__lowercase ):
raise TypeError("'str' object c... | 269 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
__SCREAMING_SNAKE_CASE :str = [
'''good first issue''',
'''feature request''',
'''wip''',
]
def UpperCAmelCase_ ( ) -> Optional[Any]:
'''simple docstring'''
... | 22 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase : Dict = {
"configuration_distilbert": [
... | 351 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : list[int | float] , snake_case : int , snake_case : int ) -> int | float:
"""simple docstring"""
if len(snake_case ) =... | 345 | 0 |
"""simple docstring"""
def _A ( lowercase ):
"""simple docstring"""
return "".join([hex(lowercase )[2:].zfill(2 ).upper() for byte in list(lowercase )] )
def _A ( lowercase ):
"""simple docstring"""
# Check data validity, fo... | 81 |
import datasets
from .evaluate import evaluate
_A : Optional[int] = '\\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},\n booktitle={EMNLP},\n year={2016... | 142 | 0 |
"""simple docstring"""
def UpperCamelCase ( _A : Optional[int] )-> str:
"""simple docstring"""
if collection == []:
return []
# get some information about the collection
A__ = len(_lowercase )
A__ = max(_lo... | 363 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def UpperCamelCase ( _A : Tuple )-> Dict:
... | 198 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForCondition... | 100 |
"""simple docstring"""
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Dict ,A_ : list[int] ) -> None:
A = len(A_ )
A = [0] * len_array
if len_array > 0:
A = array[0]
f... | 74 | 0 |
"""simple docstring"""
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_avail... | 370 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/conf... | 241 | 0 |
import math
def _lowerCAmelCase ( __lowerCAmelCase ) -> Optional[Any]:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numb... | 230 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def _SCREAMING_SNAKE_CASE ( __snake_case : str = "AAPL" ):
'''simple docstring'''
lowercase = f'https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'
lowercase = BeautifulSoup(... | 220 | 0 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __snake_case ( __lowerCAmelCase ):
a__ = ["""image_processor""", """tokenizer"""]
a__ = """AutoImageProcessor"""
a__ = """AutoTokenizer"""
def __... | 358 | """simple docstring"""
def __a ( _SCREAMING_SNAKE_CASE ) ->bool:
return credit_card_number.startswith(('34', '35', '37', '4', '5', '6') )
def __a ( _SCREAMING_SNAKE_CASE ) ->bool:
a__: Any = credit_card_number
a__: Tuple ... | 203 | 0 |
"""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/lic... | 81 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase_ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': '''htt... | 345 | 0 |
"""simple docstring"""
from timeit import timeit
def a__ ( __lowercase ) -> int:
if number < 0:
raise ValueError("the value of input must not be negative" )
_A = 0
while number:
number &= number - 1
result += 1
return res... | 163 |
"""simple docstring"""
def a__ ( __lowercase ) -> int:
assert (
isinstance(__lowercase , __lowercase ) and number_of_steps > 0
), f"""number_of_steps needs to be positive integer, your input {number_of_steps}"""
if number_of_steps == 1:
return 1
... | 163 | 1 |
'''simple docstring'''
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils im... | 75 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase ( a__ , unittest.TestCase ):
'''simple docstring''... | 198 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import _LazyModule
_UpperCAmelCase : Tuple = {"""tokenization_tapex""": ["""TapexTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
_UpperCAmelCase : ... | 9 |
'''simple docstring'''
from __future__ import annotations
import math
def __magic_name__( lowerCamelCase, lowerCamelCase):
if len(lowerCamelCase) != 2 or len(a[0]) != 2 or len(lowerCamelCase) != 2 or len(b[0]) != 2:
raise Exception('''Matrices are not 2x2''')
__lowerC... | 9 | 1 |
'''simple docstring'''
def _UpperCamelCase ( __A , __A , __A ) -> bool:
'''simple docstring'''
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__A ) )
def _UpperCamelCase ( ... | 80 |
"""simple docstring"""
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
lowercase__ = {
"""facebook/maskformer-swin-base-ade... | 241 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase_ = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowe... | 253 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
lowerCamelCase_ = '''
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
'''
lowerCamelCase_ = '''
Args... | 253 | 1 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from ... | 63 |
"""simple docstring"""
def __lowerCAmelCase ( lowercase : int ) -> bool:
"""simple docstring"""
if p < 2:
raise ValueError("p should not be less than 2!" )
elif p == 2:
return True
snake_case : Dict = 4
snake_case : str ... | 203 | 0 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transformer import Pr... | 356 | # 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 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase = 0):
UpperCAmelCase__ , UpperCAmelCase__ ... | 163 |
'''simple docstring'''
import torch
from torch import nn
class _snake_case ( nn.Module ):
def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase=1 , ... | 163 | 1 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModelForSequence... | 371 |
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class snake_case__:
"""simple docstring"""
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE : Collection[float] | None = None ):
... | 121 | 0 |
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