code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import os
import numpy
import onnx
def a_ ( lowerCamelCase , lowerCamelCase ):
UpperCAmelCase__ = a.name
UpperCAmelCase__ = b.name
UpperCAmelCase__ = ''
UpperCAmelCase__ = ''
... | 98 |
a__ = '''0.18.2'''
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_librosa_available,
is_n... | 235 | 0 |
"""simple docstring"""
import math
from collections.abc import Callable
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = xa
__SCREAMING_SNAKE_CASE = xa
... | 361 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
return " ".join(
"".join(word[::-1] ) if len(lowerCAmelCase_ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.te... | 195 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A ={"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvaila... | 226 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase_ )
class __lowercase ( UpperCAmelCase_ ):
"""simple docstring"""
_UpperCAmelCase : str ... | 13 | 0 |
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, prepare_image_inpu... | 351 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 134 | 0 |
'''simple docstring'''
from PIL import Image
def a ( __a , __a ) -> Image:
'''simple docstring'''
def brightness(__a ) -> float:
return 128 + level + (c - 128)
if not -2_5_5.0 <= level <= 2_5_5.0:
raise ValueError('''level must be between -255.0 (blac... | 97 | '''simple docstring'''
import math
import flax.linen as nn
import jax.numpy as jnp
def snake_case__ ( _A: jnp.ndarray , _A: int , _A: float = 1 , _A: float = 1 , _A: float = 1.0e4 , _A: bool = False , _A: float = 1.0 , )... | 272 | 0 |
"""simple docstring"""
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCrite... | 298 |
"""simple docstring"""
import numpy as np
import datasets
_lowerCAmelCase : Optional[int] = """
Compute the Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of the... | 298 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase : List[Any] = logging.get_logger(__name__)
_lowerCamelCase : str ... | 14 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE ):
if len(_SCREAMING_SNAKE_CASE ) == 0:
return []
_snake_case, _snake_case = min(_SCREAMING_SNAKE_CASE ), max(_SCREAMING_SNAKE_CASE )
... | 341 | 0 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
_SCREAMING_SNAKE_CASE = datasets.logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = "\\n@inproceedings{bleurt,\n title={BLEURT: Learning Robust Metrics for... | 357 |
'''simple docstring'''
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX... | 217 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Any = logging.get_logger(__name__)
lowercase : int = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'tiiu... | 3 |
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def UpperCAmelCase ( a_ ) -> List[str]:
"""simple docstring"""
return sum(param.float().sum... | 15 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, t... | 349 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowercase :
"""simple docstring"""
UpperCAmelCase = 42
UpperCAmelCase = 42
class ... | 349 | 1 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNet... | 144 |
"""simple docstring"""
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
... | 144 | 1 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_availabl... | 238 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
... | 238 | 1 |
"""simple docstring"""
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import h... | 108 | """simple docstring"""
import math
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 SchedulerMixin, SchedulerOutput
class _A ( lowerCAmelCase , ... | 197 | 0 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __A ( A_ ):
'''simpl... | 351 |
"""simple docstring"""
import argparse
import os
# New Code #
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_sched... | 302 | 0 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def A () -> Dict:
"""simple docstring"""
with offline(OfflineSim... | 51 |
import pprint
import requests
UpperCAmelCase = '''https://zenquotes.io/api'''
def UpperCAmelCase_ ( ):
return requests.get(API_ENDPOINT_URL + '/today' ).json()
def UpperCAmelCase_ ( ):
return requests.get(API_ENDPOINT_URL + '/random' ).json()
if __name__ ... | 195 | 0 |
"""simple docstring"""
from typing import Any
def a__ ( __lowercase ) -> list[Any]:
if not input_list:
return []
_A = [input_list.count(__lowercase ) for value in input_list]
_A = max(__lowercase ) # Gets the maximum count in the... | 163 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
"configuration_x_clip": [
"XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"XCLIPConfig",
"XCLIPTextConfig",
... | 163 | 1 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def SCREAMING_SNAKE_CASE__ ( __a ):
snake_case_ : Union[str, Any] = analyze_text(__snake_case )
snake_case_ : int = list(' ' + ascii_lower... | 327 |
'''simple docstring'''
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 ( unit... | 134 | 0 |
'''simple docstring'''
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_ut... | 353 |
'''simple docstring'''
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from ... | 227 | 0 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self : List[Any] , snake_case_ : list ) -> None:
'''simple docstring'''
A__ = set_counts
A__ = max(snake_case_ )
A__ = len(snake_case_ )
... | 247 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
SCREAMING_SNAKE_CASE = "src/diffusers"
# Matches is_xxx_available()
SCREAMING_SNAKE_CASE = re.... | 247 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=UpperCamelCase ):
"""simple docstring"""
UpperCamelCase_ : Optional[int] = ['''keras_nlp''']
def __init__( self : Tuple ... | 356 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__a = {
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Layo... | 17 | 0 |
"""simple docstring"""
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def _sna... | 60 |
"""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,
... | 217 | 0 |
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_modeling_common import Model... | 362 |
import numpy as np
def snake_case__ ( SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : Optional[int] , SCREAMING_SNAKE_CASE_ : Optional[int] , SCREAMING_SNAKE_CASE_ : Union[str, Any] , SCREAMING_SNAKE_CASE_ : List[Any] ):
'''simple docstrin... | 216 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.ut... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils impo... | 349 | 1 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class lowercase ( unittest.TestCase ):
'''simple docstring'''
def snake_case_ ... | 152 |
def _lowerCAmelCase ( A__: int = 1000 ):
'''simple docstring'''
UpperCAmelCase = 2**power
UpperCAmelCase = str(A__ )
UpperCAmelCase = list(A__ )
UpperCAmelCase = 0
for i in list_num:
sum_of_num += int(A__ ... | 152 | 1 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
_lowercase : Optional[int] = (7_2_0, 1_2_8_0) # Height, Width
_lowercase : List[Any] = (0.4, 0.6) # if height or width lower tha... | 238 |
"""simple docstring"""
def snake_case__ ( ):
"""simple docstring"""
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
_lowercase : str = generate_large_matrix()
_lowercase : str = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1... | 238 | 1 |
import math
def UpperCamelCase_( lowerCamelCase_ ) -> int:
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 numbers, all multiples of 3 are not primes
return False
# ... | 363 |
def UpperCamelCase_( lowerCamelCase_ = 1000 ) -> int:
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 84 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase__ : Union[str, Any] = logging.get_logger(... | 338 | 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 SCREAMING_SNAKE_CASE_ ( snake_case__ , snake_case__ ) -> Union... | 338 | 1 |
from math import isqrt
def UpperCamelCase ( _a ) -> bool:
'''simple docstring'''
return all(number % divisor != 0 for divisor in range(2 , isqrt(_a ) + 1 ) )
def UpperCamelCase ( _a = 1_0**6 ) -> int:
... | 252 |
# 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 re... | 252 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__A ={'configuration_vit_mae': ['VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMAEConfig']}
... | 163 |
'''simple docstring'''
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
__A =namedtuple(
'_TestCommandArgs',
[... | 163 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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
f... | 354 | '''simple docstring'''
def __UpperCAmelCase ( a_: int, a_: int ):
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive" )
_UpperCAmelCase : List[str] = str(bin(a_ ) )[2:] # remove the leading "0b"
_UpperCAmelCase... | 17 | 0 |
'''simple docstring'''
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCAmelCase_ ( __lowerCamelCase : str ):
lowercase_ :Optional[int] = args.pruning_method
lowe... | 223 |
'''simple docstring'''
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
lowerCAmelCase : ... | 223 | 1 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
_UpperCAmelCase : Dict = """__DUMMY_TRANSFORMERS_USER__"""
_UpperCAmelCase : str = """D... | 356 |
'''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.generation import DisjunctiveConstraint
@require_torch
class a__ ( unittest.TestCase ):
... | 9 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
fr... | 71 |
"""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... | 17 | 0 |
"""simple docstring"""
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")
class snak... | 163 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class snake_case ( _UpperCamelCase):
__UpperCamelCase ... | 163 | 1 |
"""simple docstring"""
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available... | 194 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ ={
'configuration_roformer': ['ROFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoFormerConfi... | 216 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class _lowercase ( __UpperCAmelCase ):
lowercase_ = 'WhisperFeatureExtractor'
lowercase_ = 'WhisperTokenizer'
def __init__( self , UpperCAmelCase_ , UpperCAmelCase_ ) -> List[Any... | 205 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
class _lowercase ( __UpperCAmelCase ):
lowercase_ = 'encoder-decoder'
lowercase_ = True
def __ini... | 205 | 1 |
'''simple docstring'''
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
a_ = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership funct... | 152 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import ded... | 152 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor,... | 369 |
from __future__ import annotations
def lowerCAmelCase__ ( _a : str , _a : str ):
snake_case_ : Optional[Any] = get_failure_array(_a )
# 2) Step through text searching for pattern
snake_case_ , snake_case_ : Dict = 0, 0 # index into te... | 36 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
__magic_name__ = {
"sample_size": 32,
"in_channels": 3,
"out_channels": 3,
"layers_per_block": 2,
"num_class_em... | 100 |
"""simple docstring"""
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="""session""" )... | 84 | 0 |
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
deprecate(
'''pipelines_utils''',
'''0.22.0''',
'''Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import from diffusers.pi... | 354 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_SCREAMING_SNAKE_CASE = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Fo... | 217 | 0 |
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.utils ... | 296 |
'''simple docstring'''
def lowerCamelCase__ ( _A , _A ):
while second != 0:
a : Union[str, Any] = first & second
first ^= second
a : Tuple = c << 1
return first
if __name__ == "__main__":
import doctest
doctest.testmod(... | 297 | 0 |
def snake_case (A_ :int = 1_0 , A_ :int = 2_2 ):
'''simple docstring'''
a : List[Any] = range(1 , A_ )
a : int = range(1 , A_ )
return sum(
1 for power in powers for base in bases if len(str(base**power ... | 364 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_UpperCamelCase : List[str] = logging.get... | 186 | 0 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ...i... | 59 |
"""simple docstring"""
def _A ( UpperCamelCase_ : Any) -> List[str]:
'''simple docstring'''
__lowercase ,__lowercase = [], []
while len(UpperCamelCase_) > 1:
__lowercase ,__lowercase = min(UpperCamelCase_), max(UpperCamelCase_)
start.append(Uppe... | 17 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import LearnedClassifie... | 357 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_SCREAMING_SNAKE_CASE : str = "https://www.indeed.co.in/jobs?q=mobile+app+development&l="
def UpperCAmelCase__ (UpperCamelCase_ = "mumbai" ):
... | 213 | 0 |
"""simple docstring"""
def _UpperCAmelCase ( __lowerCamelCase : int ) -> List[str]:
_snake_case = len(lowercase__ )
for i in range(1 , lowercase__ ):
_snake_case = collection[i]
_snake_case = 0
_snake_case ... | 288 |
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
__lowerCAmelCase : List[Any] =datasets.load_iris()
__lowerCAmelCase : Tuple =np.array(data['data'])
__lowerCAmelCase : Dict =np.array(data['target'])
__lowerCAmelCase... | 9 | 0 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __SCREAMING_SNAKE_CASE ( lowerCAmelCase: dict , lowerCAmelCase: str , lowerCAmelCase: set , lowerCAmelCase: set , lowerCAmelCase: dict , lowerCAmelCase: dict , lowerCAmelCase:... | 369 |
# 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 ap... | 189 | 0 |
'''simple docstring'''
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimensi... | 163 |
'''simple docstring'''
from math import log
from scipy.constants import Boltzmann, physical_constants
__A =3_00 # TEMPERATURE (unit = K)
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , ):
if donor_conc <= ... | 163 | 1 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Generation... | 356 |
import argparse
import gc
import json
import os
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accele... | 225 | 0 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowercase_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_copies # noqa: E402
# This is the re... | 205 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def a ( A__ : int , A__ : int , A__ : int , A__ : int , A__ : int , A__ : int ) -> np.ndarray:
"""simple docstring"""
... | 205 | 1 |
'''simple docstring'''
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def __snake_case( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> List[str... | 43 |
'''simple docstring'''
def __snake_case( _lowerCAmelCase ) -> int:
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ):
raise TypeError("""Input value must be an 'int' type""" )
snake_case__ : List[str] = 0
while number:
positi... | 43 | 1 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def lowercase_ ( self , lowerCam... | 90 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake_... | 36 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( a_: str ):
return " ".join(
"".join(word[::-1] ) if len(a_ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words('Hey wollef ... | 17 | '''simple docstring'''
import unittest
import numpy as np
import requests
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
... | 17 | 1 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _a ( SCREAMING_SNAKE_CASE : int ) -> List[str]:
"""simple docstring"""
for param in module.parameters():
__lowerCAmelCase: str = False
def _a ( ) -... | 322 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
fro... | 277 | 0 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
_snake_case = None
try:
import msvcrt
except ImportError:
_snake_case = None
try:
import fcntl
except ImportError:
_snake_case... | 324 |
"""simple docstring"""
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
@requ... | 324 | 1 |
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tenso... | 76 |
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 import xopen
from ..table import... | 186 | 0 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def snake_case__ ( __lowerCamelCase : str , __lowerCamelCase : Optional[int] , __lowerCamelCase : List[Any] , __lowerCamelCase : Optional[Any] , ... | 359 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
_lowercase : Any = {
"configuration_trocr": ["TROCR_PRETRAINED_CONFIG_... | 272 | 0 |
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def UpperCAmelCase ( lowercase , lowercase=1 ):
"""simple docstring"""
if n_shave_prefix_segments >= 0:
return ".".join(path.split('''.''' )[n_... | 210 | """simple docstring"""
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassif... | 213 | 0 |
"""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... | 360 |
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
lowerCAmelCase__ : Optional[Any] ='src/transformers'
lowerCAmelC... | 162 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ : Any = logging.get_logger(__name__)
lowerCamelCase_ : List[str] = {
"""microsoft/unispeech-large-1500... | 81 |
import numpy as np
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase ) -> np.array:
return 1 / (1 + np.exp(-vector ))
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase ) -> np.array:
return vector * sigmoid(1.7_0_2 * vector )
if __name__ =... | 189 | 0 |
'''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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbo... | 351 | '''simple docstring'''
def __UpperCAmelCase ( a_: str ):
if not all(char in "01" for char in bin_string ):
raise ValueError("Non-binary value was passed to the function" )
if not bin_string:
raise ValueError("Empty string was passed to the function" )
_Upp... | 17 | 0 |
"""simple docstring"""
import pprint
import requests
_UpperCamelCase : Optional[Any] = 'https://zenquotes.io/api'
def _SCREAMING_SNAKE_CASE ( ):
'''simple docstring'''
return requests.get(API_ENDPOINT_URL + '/today' ).json()
def _SCREAMING_SNAKE_CASE ( ):
''... | 220 |
"""simple docstring"""
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization... | 220 | 1 |
lowercase_ = 'Input must be a string of 8 numbers plus letter'
lowercase_ = 'TRWAGMYFPDXBNJZSQVHLCKE'
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Tuple = f'Expected str... | 194 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Union[str, Any] = len(SCREAMING_SNAKE_CASE__ )
__lowerCamelCase : Any = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of ... | 194 | 1 |
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
... | 43 | def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCamelCase :Tuple = [0 for i in range(len(SCREAMING_SNAKE_CASE ) )]
# initialize interval's left pointer and right pointer
__UpperCamelCase , __UpperCamelCase :str = 0, 0
for i in range(1 ... | 43 | 1 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('3.8'):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
_SCREAMING_SNAKE_CAS... | 364 | from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastapi.routing impor... | 81 | 0 |
"""simple docstring"""
def _A ( UpperCamelCase_ : str) -> str:
'''simple docstring'''
return " ".join(
"".join(word[::-1]) if len(UpperCamelCase_) > 4 else word for word in sentence.split())
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_lo... | 17 |
"""simple docstring"""
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoenco... | 17 | 1 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, 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_ten... | 122 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils i... | 122 | 1 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowercase__ : List[Any] = None
try:
import msvcrt
except ImportError:
lowercase__ : List[str] = None
try:
import fcntl
except ImportError:
lo... | 324 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_a... | 324 | 1 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,
get_... | 354 | import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowercase = """\
@inproceedings{kakwani2020indicnlpsuite,
title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for I... | 35 | 0 |
import requests
def lowercase_ ( _lowerCamelCase : str , _lowerCamelCase : str):
lowercase__ : List[str] = {"Content-Type": "application/json"}
lowercase__ : List[Any] = requests.post(_lowerCamelCase , json={"text": message_body} , headers=_lower... | 87 | '''simple docstring'''
import os
import string
import sys
__lowercase = 1 << 8
__lowercase = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 2_7,
'''up''': 6_5 + ARROW_KEY_FLAG,
'''down''': 6_6 + ARROW_KEY_FLAG,
'''right''': 6_7 + ARROW_KEY_FLAG,
... | 272 | 0 |
'''simple docstring'''
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count... | 217 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE = {
'''configuration_... | 217 | 1 |
from graphs.minimum_spanning_tree_kruskal import kruskal
def lowercase__ ( ):
'''simple docstring'''
UpperCAmelCase_ : str = 9
UpperCAmelCase_ : Tuple = [
[0, 1, 4],
[0, 7, 8],
[1... | 29 |
'''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():
fr... | 162 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ :Optional[int] = {
"configuration_bigbird_pegasus": [
"BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BigBirdPegasusConfig",
"BigBirdPegasu... | 369 |
import numpy as np
import datasets
lowercase__ :Dict = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof. P. C.... | 97 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils i... | 46 |
"""simple docstring"""
from math import sqrt
def _A ( UpperCamelCase_ : int) -> int:
'''simple docstring'''
__lowercase = 0
for i in range(1, int(sqrt(UpperCamelCase_) + 1)):
if n % i == 0 and i != sqrt(UpperCamelCase_):
total += i + n // i
eli... | 17 | 0 |
'''simple docstring'''
def __lowerCamelCase ( A__ ) -> bool:
"""simple docstring"""
if p < 2:
raise ValueError('p should not be less than 2!' )
elif p == 2:
return True
UpperCamelCase = 4
UpperCamelCase = (1 << p) - 1
... | 367 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase : Tuple = {
"configuration_convnext": ["CONVNEXT_PRE... | 249 | 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 .tokenization_roform... | 194 |
"""simple docstring"""
from collections import defaultdict
class _UpperCAmelCase:
def __init__( self , __a , __a) -> Union[str, Any]:
'''simple docstring'''
_UpperCamelCase = total # total no of tasks (N)
# DP ... | 194 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils i... | 357 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase )
class SCREAMING_SNAKE_CASE (UpperCAmelCase ):
_UpperCamelCase : str = field(default='language-m... | 269 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _a ( __a ):
@staticmethod
@abstractmethod
def A ( lowercase : ArgumentParser ):
'''simple docstring'''
raise NotImplementedError()
... | 34 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def _A ( ... | 81 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def __UpperCAmelCase ( lowercase ):
"""simple docstring"""
return choice(_lowerCAmelCase )
def __UpperCAmelCase ( lowercase ,lowercase ):
"""simple docstring""... | 370 | """simple docstring"""
def __UpperCAmelCase ( lowercase = 10_00 ):
"""simple docstring"""
_UpperCAmelCase = 2**power
_UpperCAmelCase = 0
while n:
_UpperCAmelCase , _UpperCAmelCase = r + n % 10, n // 10
return r
if __name__ == "__main__":
print(solution(int(str(input... | 30 | 0 |
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 lowerCamelCase__ ( ) -> int:
UpperC... | 122 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
_A = '''\
'''
_A = '''
Perplexity (PPL) is one of the most common metrics for evaluating language models.
It is defined ... | 122 | 1 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ :Any = logging.get_logger(__name__)
lowercase__ :str = {
"vocab_file": "vocab.txt",
"merges_file": "bpe.codes... | 97 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ :Any = {
"configuration_distilbert": [
"DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_... | 97 | 1 |
'''simple docstring'''
import sys
from collections import defaultdict
class UpperCAmelCase :
def __init__( self : int ) -> Optional[Any]:
_lowerCAmelCase = []
def lowercase__ ( self : List[str] ... | 70 |
'''simple docstring'''
import string
from math import logaa
def __snake_case( _lowerCAmelCase , _lowerCAmelCase ) -> int:
snake_case__ : List[str] = document.translate(
str.maketrans("""""" , """""" , string.punctuation ) ).replace("""\n""" ... | 35 | 0 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def lowerCAmelCase_ ( __lowerCamelCase ):
__snake_case : List[str] = {}
__snake_case : ... | 354 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Any = logging.get_logger(__name__)
_snake_case : Dict = {
"facebook/s2t-wav2vec2-large-en-de": (
"https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json"
... | 134 | 0 |
"""simple docstring"""
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedS... | 217 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,... | 217 | 1 |
"""simple docstring"""
import unittest
import numpy as np
def __snake_case ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ... | 202 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : Union[str, Any] = {
"configuration_roform... | 202 | 1 |
from math import factorial
class lowerCamelCase__:
def __init__( self: List[str] , UpperCamelCase_: int , UpperCamelCase_: Union[str, Any] ):
__lowerCamelCase = real
if isinstance(UpperCamelCase_ , UpperCamelCase_ ):
... | 12 |
'''simple docstring'''
__snake_case = 65521
def a ( __a ) -> int:
'''simple docstring'''
UpperCamelCase__ :Tuple = 1
UpperCamelCase__ :Any = 0
for plain_chr in plain_text:
UpperCamelCase__ :List[str] = (a + o... | 97 | 0 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMix... | 37 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
lowerCAmelCase__ : int = {
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
"g... | 37 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCAmelCase = {"""processing_wav2vec2_with_lm""": ["""Wav2Vec2ProcessorWithLM"""]}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
UpperCAmelCase = _... | 256 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
while b:
SCREAMING_SNAKE_CASE__ : int = b, a % b
return a
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
return a if b =... | 370 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import... | 56 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : Tuple = {
'''... | 105 |
"""simple docstring"""
def _lowercase ( ) -> int:
return 1
def _lowercase ( __snake_case ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def _lowercase ( __snake_case ) -> int:
return 0 if x < 0 else five_pence(x - 5 )... | 269 | 0 |
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings('''ignore''', category=UserWarning, module='''torch.optim.lr_scheduler''')
class lowercase :
""... | 362 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__A = {
'''configuration_clip''': [
'''CLIP_PRETRAINED_CO... | 277 | 0 |
'''simple docstring'''
# Copyright (c) 2021-, NVIDIA CORPORATION. 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-... | 42 |
def a ( snake_case__: int = 100 ):
'''simple docstring'''
lowercase_ = (n * (n + 1) // 2) ** 2
lowercase_ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(f"{solution() = }")
| 30 | 0 |
from functools import lru_cache
@lru_cache
def lowercase__( a__ ):
"""simple docstring"""
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
docte... | 370 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_av... | 19 | 0 |
'''simple docstring'''
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class lowercase ( A__ ):
"""simple docstring"""
_a = CustomTokenizer
pass | 97 |
'''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 = logging.get_logger(__name__)
__snake_case = {
'''camembert-base'... | 97 | 1 |
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
lowercase = logging.get_logger(__name__)
lowerca... | 368 | import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowercase = """src/transformers"""
# This is to make sure ... | 35 | 0 |
'''simple docstring'''
def __lowerCAmelCase ( UpperCamelCase__ , UpperCamelCase__ ) -> str:
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
raise ValueError('''iterations must be defined as integers''' )
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ... | 67 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __lowerCamelCase ( __snake_case : str = "." ) -> Iterator[str]:
"""simple docstring"""
for dir_path, dir_names, filenames in os.walk(__snake_case ):
A__ : Li... | 134 | 0 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCamelCase_ :
def __init__( self : Any ):
'''simple docstring'''
a = ''''''
a = ''''''
a =... | 361 |
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome is truly tiny -
# all files ~60KB. A... | 330 | 0 |
"""simple docstring"""
import math
def __UpperCAmelCase ( ):
"""simple docstring"""
_UpperCAmelCase = input("""Enter message: """ )
_UpperCAmelCase = int(input(f'''Enter key [2-{len(lowercase ) - 1}]: ''' ) )
_UpperCAmelCase = input(""... | 289 | """simple docstring"""
import argparse
import os
# New Code #
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
fro... | 289 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
... | 352 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, req... | 215 | 0 |
'''simple docstring'''
# Copyright 2022 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
... | 37 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availab... | 37 | 1 |
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 lowerCAmelCase_ ( _lowercase : List[str]) ... | 360 |
from __future__ import annotations
import requests
_lowercase : Dict =set(
"approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories crea... | 266 | 0 |
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