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 |
|---|---|---|---|---|
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_dime... | 188 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __magic_name__ :
'''simple docstring'''
def __init__( self, lowercase_ ) -> List[str]:
"""simple docstring"""
a__ =data
a__ =[0X67452301, 0Xefcda... | 188 | 1 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase ( _SCREA... | 110 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_UpperCAmelCase : Union[str, Any] = get_tests_dir("fixtures/test_sentencepiece_w... | 110 | 1 |
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE )... | 195 |
from manim import *
class A_ ( __lowerCamelCase ):
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( self ):
lowercase = Rectangle(height=0.5 , width=0.5 )
lowercase = Rectangle(height=0.25 , width=0.25 )
lowercase = R... | 195 | 1 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load... | 331 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : int = logging.get_logger(__name__)
UpperCAmelCase : Union[str, Any] = {
'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/reso... | 331 | 1 |
"""simple docstring"""
from manim import *
class UpperCamelCase_ (__A ):
def _SCREAMING_SNAKE_CASE ( self : List[str] ) -> List[str]:
UpperCAmelCase_ : Any = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase_ : List[Any] ... | 268 |
"""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/config.json''',
'''RWKV... | 268 | 1 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_g... | 364 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class lowerCamelCase ( unittest.TestCase ):
def UpperCAmelCase(self : Tuple ) -> ... | 137 | 0 |
def UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise ValueError('''Length must be a positive.''' )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def UpperCame... | 101 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import require_elasticsearch, require... | 101 | 1 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_UpperCAmelCase = {
'iou_pre... | 232 |
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
_UpperCAmelCase = '\\n@inproceedings{snover-etal-2006-study,\n title = "A Study of Translation Edit Rate with Targeted Human Annotation",\n author = "Snover, Matthew and\n Dorr, Bonnie ... | 232 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
... | 212 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=__magic_name__ )
class A__ ( __magic_name__ ):
lowercase = field(default='audio-cl... | 212 | 1 |
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def snake_case_ ():
'''simple docstring'''
raise RuntimeError('''CUDA out of memory.''' ... | 363 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, t... | 179 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase : int = {"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOnnxConfig"""]}
try:
if not is_torch_av... | 13 |
import unittest
import numpy as np
from transformers import DistilBertConfig, 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 jax.numpy as j... | 131 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from .... | 352 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__( _UpperCamelCase : int | float | str , _UpperCamelCase : int | float | str ) -> list[str]:
'''simple docstring'''
if nth_term == "":
return [""]
... | 31 | 0 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def UpperCAmelCase__ ( UpperCAmelCase_ : list , UpperCAmelCase_ : list , UpperCAmelCas... | 185 |
'''simple docstring'''
import unittest
from knapsack import knapsack as k
class UpperCAmelCase_ (unittest.TestCase ):
"""simple docstring"""
def lowercase_ ( self ) -> Optional[Any]:
__lowerCamelCase : int = 0
__lowerCamelCase : Uni... | 185 | 1 |
'''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class _UpperCamelCase (... | 48 |
'''simple docstring'''
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data im... | 48 | 1 |
"""simple docstring"""
import warnings
warnings.warn(
'''memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '''
'''`from accelerate import find_executable_batch_size` to avoid this warning.''',
FutureWarning,
)
| 54 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE_ )
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
... | 317 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enab... | 16 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_... | 16 | 1 |
"""simple docstring"""
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_... | 268 |
"""simple docstring"""
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class a ( a_ ):
def __init__( self , _lowerCamelCase , _lowerCamelCase ):
super()... | 220 | 0 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( lowerCamelCase_ : int ):
__lowercase = [True] * limit
__lowercase = False
__lowercase = False
__lowercase = True
for i in range(3 ... | 217 |
'''simple docstring'''
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class __... | 217 | 1 |
"""simple docstring"""
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def UpperCAmelCase__ (snake_case__ : str , snake_case__ : str , **snake_case__ : Tuple ):
"""simple docstring"""
_snake_case ... | 64 |
'''simple docstring'''
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
__A : Any ... | 120 | 0 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def _a ( SCREAMING_SNAKE_CASE__ : Union[str, Any] ) -> Tuple... | 364 |
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
_lowerCamelCase : Tuple = collections.namedtuple('''_D... | 191 | 0 |
import comet # From: unbabel-comet
import torch
import datasets
UpperCAmelCase__ = datasets.logging.get_logger(__name__)
UpperCAmelCase__ = '''\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},
title = {Unbabel\... | 5 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowerCamelCase__ ( nn.Module):
def __init__(self , UpperCAmelCase = 1_6 , UpperCAmelCase = 8_8 , UpperCAmelCase = None , UpperCAmelCase ... | 5 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
"configuration_clap": [
"CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
"ClapAudioConfig",
"ClapConfig",
"ClapT... | 368 |
'''simple docstring'''
import functools
def UpperCamelCase ( a , a ) -> int:
'''simple docstring'''
__magic_name__ = len(a )
__magic_name__ = len(a )
@functools.cache
def min_distance(a , a ) -> int:
# i... | 98 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : Union[tf.Tensor, np.ndarray] ):
... | 46 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE__ = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
t... | 150 | 0 |
'''simple docstring'''
from __future__ import annotations
lowerCamelCase__ = [True] * 1_000_001
lowerCamelCase__ = 2
while i * i <= 1_000_000:
if seive[i]:
for j in range(i * i, 1_000_001, i):
lowerCamelCase__ = False
i... | 322 |
'''simple docstring'''
def __lowerCAmelCase (__lowerCAmelCase ):
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 322 | 1 |
'''simple docstring'''
_snake_case = 8.3_1_4_4_5_9_8
def _A ( snake_case , snake_case ) -> float:
if temperature < 0:
raise Exception("Temperature cannot be less than 0 K" )
if molar_mass <= 0:
raise Exception("Molar mass cannot be less than or equal to 0 kg/... | 250 |
'''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def a ( __a ) -> int:
'''simple docstring'''
for param in module.parameters():
UpperCamelCase__ :Dict = False
def a ( ) -> Union[str, Any]:
... | 97 | 0 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.robert... | 369 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 0 |
"""simple docstring"""
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
__A = datasets.logging.get_logger(__name__)
__A = "\\n@inproceedings{bleurt,\n title={BLEURT: Learning Robust Metrics for Text Generation},\n... | 217 |
"""simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
... | 217 | 1 |
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
... | 358 |
import json
import sys
def SCREAMING_SNAKE_CASE_ ( __A : Optional[Any] , __A : List[str] ) -> Tuple:
"""simple docstring"""
with open(__A , encoding='utf-8' ) as f:
a_ : Union[str, Any] = json.load(__A )
... | 120 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'distilbert-base-uncased': 'https://huggingface.c... | 12 |
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
lowercase : Tup... | 99 | 0 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import Model... | 371 |
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,
)
__A : List[Any] = {
'''configuration_xlm_roberta'''... | 323 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''google/realm-cc-news-pretrained-embedder''': (
'''https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json''... | 43 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class snake_case :
'''simple docstring'''
def __init__( self : Optional[int], _lowerCamelCase : Optional[int]=2, _lowerCa... | 266 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"google/bit-50": "https:/... | 350 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _snake_case( SCREAMING_SNAKE_CASE__... | 282 | 0 |
def A ( lowercase , lowercase ) -> List[Any]:
'''simple docstring'''
UpperCamelCase = 0
UpperCamelCase = len(lowercase ) - 1
while left <= right:
# avoid divided by 0 during interpolation
if sorted_collection[left] == sorted_collection[right]:
if sorted_col... | 222 |
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require_torch_gpu
class lowerc... | 222 | 1 |
"""simple docstring"""
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
__UpperCamelCase : Tuple = (
'''This metric will... | 74 |
"""simple docstring"""
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__UpperCamelCase : int = '''%20'''.join(argv[1:]) if len(argv) > 1 else quot... | 74 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__Up... | 146 |
import cmath
import math
def _a ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float ):
"""simple docstring"""
UpperCamelCase__ : Union[str, Any] = math.radians(SCREAMING_SNAKE_CA... | 146 | 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
... | 350 |
'''simple docstring'''
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassifi... | 9 | 0 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : Union[str, Any] ):
__UpperCamelCase =FileLock(str(tmpdir / 'foo.lock' ) )
__UpperCamelCase =FileLock(str(tmpdir / 'foo.lo... | 62 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTok... | 53 | 0 |
def lowercase__ ( __snake_case : Tuple ):
'''simple docstring'''
UpperCAmelCase_ : int = [], []
while len(A__ ) > 1:
UpperCAmelCase_ : List[str] = min(A__ ), max(A__ )
start.append(A__ )
end.a... | 351 |
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,
nested... | 145 | 0 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
_snake_case : str = [8, 5, 9, 7]
_snake_case : List[Any] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_snake_case : Union[str, Any] ... | 292 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't b... | 316 | 0 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> str:
"""simple docstring"""
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 360 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> list:
"""simple docstring"""
if len(SCREAMING_SNAKE_CASE_ ) <= 1:
return lst
UpperCamelCase_ = 1
while i < len(SCREAMING_SNAKE_CASE_ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
... | 60 | 0 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
import s... | 178 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def __UpperCAmelCase ( a_ , a_ , a_ , a_ , a_):
snake_case_ = np.array([[... | 178 | 1 |
'''simple docstring'''
import math
def A_( A : list , A : int = 0 , A : int = 0):
UpperCamelCase = end or len(A)
for i in range(A , A):
UpperCamelCase = i
UpperCamelCase = array[i... | 251 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise O... | 251 | 1 |
def a_ ( _A , _A , _A , _A , _A , _A ) -> Optional[Any]:
"""simple docstring"""
if index == r:
for j in range(_A ):
print(data[j] , end=' ' )
print(' ' )
... | 307 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 258 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
A = {'''tokenization_byt5''': ['''ByT5Tokenizer''']}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
A = _LazyModule(__name__, glob... | 363 |
"""simple docstring"""
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig... | 188 | 0 |
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:
# - tqdm must be checked before tokenizers
lower... | 11 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : List[Any] = {
'''configuration_distilbert''': [
... | 264 | 0 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vision_available
f... | 159 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
_lowerCamelCase : Dict = namedtuple("covid_data", "cases deaths recovered")
def _UpperCAmelCase (UpperCamelCase_ : str = "https://www.worldometers.info/coronavirus/" ):
'''simple docstring'''
... | 159 | 1 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
UpperCAmelCase_ = Path(__file__).resolve().parents[3] / 'src'
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io # noqa
import i... | 12 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@require_torc... | 12 | 1 |
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
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_configur... | 267 |
import os
def __lowerCAmelCase ()-> List[Any]:
"""simple docstring"""
snake_case_ = os.path.join(os.path.dirname(SCREAMING_SNAKE_CASE ) , '''num.txt''' )
with open(SCREAMING_SNAKE_CASE ) as file_hand:
return str(sum(int(SCREAMING_SNAKE_CASE ) for line in file_hand ) )[... | 267 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : int = logging.get_logger(__name__)
snake_case_ : str = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
# See all GLPN m... | 83 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
A : Dict = logging.get_logger(__name__)
def __lowerCamelCase ( __a :int=None , __a ... | 274 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_A : str = logging.get_logg... | 265 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : Any = logging.get_logger(__name__)
_A : int = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase... | 265 | 1 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class __SCREAMING_SNAKE_CASE( unittest.TestCase ):
_UpperCAmelCas... | 307 |
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.war... | 307 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : Dict = {
'configuration_instructblip': [
'INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InstructBlipConfig',
'InstructBlipQFormerConfig',
'... | 33 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : Dict = {
'configuration_instructblip': [
'INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InstructBlipConfig',
'InstructBlipQFormerConfig',
'... | 33 | 1 |
"""simple docstring"""
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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/... | 172 | """simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCL... | 172 | 1 |
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:
predictions: List of predicted texts.... | 304 |
import unittest
from transformers import XLMConfig, 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_... | 304 | 1 |
"""simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
__UpperCamelCase = '''\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author={Wang... | 69 |
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,
... | 159 | 0 |
"""simple docstring"""
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, req... | 234 |
"""simple docstring"""
import numpy as np
def _a ( _snake_case ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 234 | 1 |
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
_A = logging.get_logger(__name__)
_A = '''▁'''
_A = {'''vocab_f... | 278 |
def _A ( _lowercase ) -> list[int]:
"""simple docstring"""
if length <= 0 or not isinstance(_lowercase , _lowercase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(_lowercase )]
i... | 310 | 0 |
"""simple docstring"""
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.swit... | 353 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase__ ( snake... | 234 | 0 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 157 | from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import T... | 157 | 1 |
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 TokenizerTesterM... | 367 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase : Union[str, Any] = {
'''configuration_bigbird_pegasus''': [
'''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BigBirdPegasusC... | 191 | 0 |
"""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, RegNetYaagf, ... | 102 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 55 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a = logging.get_log... | 100 |
"""simple docstring"""
class _UpperCAmelCase:
def __init__( self , __a , __a , __a) -> List[Any]:
'''simple docstring'''
_UpperCamelCase = name
_UpperCamelCase = value
_UpperCamelCase = weight
def __r... | 100 | 1 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def __UpperCAmelCase ( __a : List[str] ,__a : List[Any] ,__a : Optional[Any] ,__a : Optional[int] ,) -> Tuple:
"""simple docstring"""
... | 235 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
A_ : List[Any] = current_set.copy()
for row_index, row in enumerate(SCREAMING_SNAKE_CASE ):
A_ : List[str] = row[0]
for column_index, column in enumerate(SCREAMING_SNAKE_CASE ):
if magnitude ... | 186 | 0 |
'''simple docstring'''
from functools import reduce
a__ : Union[str, Any] = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""1254069874... | 353 |
'''simple docstring'''
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowercase ( *__A ):
'''simple docstring'''
if not isinstance(__A ,__A ):
__UpperCamelCase = list(_... | 243 | 0 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' ... | 80 |
"""simple docstring"""
def __magic_name__ ( __snake_case : list ) -> list:
if len(__snake_case ) < 2:
return collection
def circle_sort_util(__snake_case : list , __snake_case : int , __snake_case : int ) -> bool:
... | 202 | 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 .tokenizat... | 370 | """simple docstring"""
def UpperCAmelCase ( UpperCamelCase__ , UpperCamelCase__ ):
"""simple docstring"""
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
raise ValueError('iterations must be defined as integers' )
... | 154 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
f... | 311 |
'''simple docstring'''
import argparse
import copy
def lowercase ( __magic_name__ ):
'''simple docstring'''
UpperCAmelCase : List[str] = {}
with open(__magic_name__ ) as f:
for line in f:
if line.split()[0] not in dict_... | 311 | 1 |
'''simple docstring'''
def _a( ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : List[str] =[3_1, 2_8, 3_1, 3_0, 3_1, 3_0, 3_1, 3_1, 3_0, 3_1, 3_0, 3_1]
SCREAMING_SNAKE_CASE__ : Union[str, Any] =6
SCREAMING_SN... | 350 |
'''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def _a( UpperCamelCase__ : int ):
'''simple docstring'''
if not isinstance(UpperCamelCase__, UpperCamelCase__ ):
raise TypeError(... | 222 | 0 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASET... | 82 |
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class __lowerCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
@register_to_config
def... | 82 | 1 |
def _A ( lowerCAmelCase_ : float ):
"""simple docstring"""
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge... | 221 |
def _A ( lowerCAmelCase_ : int = 1000 ):
"""simple docstring"""
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 221 | 1 |
from __future__ import annotations
_A : Tuple = '#'
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] ) ->None:
lowerCamelCase__ : dict = {}
def __lowerCamelCase ( self : int , A :... | 142 |
from ..utils import DummyObject, requires_backends
class __SCREAMING_SNAKE_CASE ( metaclass=lowerCAmelCase_ ):
_UpperCAmelCase : int = ["transformers", "torch", "note_seq"]
def __init__( self : Union[str, Any] , *A : int , **A : Optional[int]... | 142 | 1 |
'''simple docstring'''
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def a_ ( _UpperCAmelCase : Optional[int] ) -> int:
return 1 / (1 + np.exp(-z ))
def a_ ( _UpperCAmelCase : Optional[Any] ,_Uppe... | 355 |
'''simple docstring'''
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet i... | 0 | 0 |
from __future__ import annotations
import time
import numpy as np
lowerCAmelCase__ = [8, 5, 9, 7]
lowerCAmelCase__ = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
lowerCAmelCase__ = [
[3, 2, 1, 4],
[0, 2, 5, 2],
[5, ... | 68 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class UpperCAmelCase_ ( __lowercase ):
def __lt__( self : Optional[int] , UpperCAmelCa... | 4 | 0 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
U... | 128 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` in... | 128 | 1 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase_ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
a_ ... | 208 |
'''simple docstring'''
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.tra... | 208 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from t... | 370 |
'''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class UpperCAmelCase__ ( UpperCAmelCase_):
_... | 243 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ : Any = {
"configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}
try:
if not is_torch_available():
ra... | 55 |
from __future__ import annotations
from collections.abc import Callable
def A_ ( snake_case : Callable[[int | float], int | float] , snake_case : int | float , snake_case : int | float , snake_case : int = 100 , ) ... | 328 | 0 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_util... | 357 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_lowerCamelCase)
class A__ ( _lowerCamelCase):
# `task` is not a ClassVar since we want ... | 182 | 0 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ = "src/transformers"
# Pattern that looks at the indentation in a line.
lowercase__ = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
lowercase__ = re.compile(r"^\s*\"([^... | 151 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
lowercase__ = logging.get_logger(__name__)
class A_ ( _snake_case ):
'''simple docstring'''
def __init__( se... | 151 | 1 |
'''simple docstring'''
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def a_ ( __snake_case : Optional[int] ) -> int:
"""simple docstring"""
return 1 / (1 + np.exp(-z ))
def a_ ( __sna... | 353 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
a_ : Any = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONFIG_ARCHIVE... | 6 | 0 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase=0.2 , _lowerCamelCase=0.2 ):
a :T... | 94 |
snake_case : str = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
snake_case : List[... | 94 | 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_ = logging.get_logger(__name__)
lowercase_ = {
'xlm-roberta-base': 'https://hugging... | 362 |
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import Onn... | 194 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
lowercase_ : List[Any] = [1]
lowercase_ , lowercase_ , lowercase_ : Optional[Any] = 0, 0, 0
lowercase_ : Union[str, Any]... | 239 | '''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : Tuple = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/A... | 239 | 1 |
"""simple docstring"""
import sys
from pathlib import Path
A = Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io # noqa
import itertools # noqa
import json # noqa
import os # noqa
import unitte... | 352 |
"""simple docstring"""
def __A ( a_ :int , a_ :int) -> str:
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''')
__a : Union[str, Any] = str(bin(a_))[2:] # remove the leading "0b"
__a : Union[st... | 188 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a = {
'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
'configuration_mas... | 155 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common impo... | 178 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCAmelCase ( a_ ) -> List[Any]:
"""simple docstring"""
if not nums:
return 0
A_ : Any = nums[0]
A_ : Tuple = 0
for num in nums[1:]:
A... | 351 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _lowerCAmelCa... | 164 | 0 |
import re
import string
import numpy as np
import datasets
lowerCAmelCase : Dict = '\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n'
lowerCAmelCase : List[str] = '\nArgs:\n ... | 253 |
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_NAME, shard_checkpoint
lowerCAmelCase : ... | 253 | 1 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> Tuple:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def _SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_=0 ) -> str:
return sorted(A__ ... | 357 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
"Intel/dpt-large": "https://huggingface.co/Intel/dpt-large/resolve/main/confi... | 230 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( __UpperCAmelCase: int ) -> bool:
UpperCamelCase__ : Tuple = str(__UpperCAmelCase )
return len(__UpperCAmelCase ) == 9 and set(__UpperCAmelCase ) == set('''123456789''' )
... | 201 |
def lowerCAmelCase_ ( __UpperCAmelCase: int ) -> int:
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ) or number < 0:
raise ValueError('''Input must be a non-negative integer''' )
UpperCamelCase__ : Optional[Any] = 0
whil... | 201 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import gcd
def _lowerCAmelCase ( lowerCAmelCase , lowerCAmelCase = 2 , lowerCAmelCase = 1 , lowerCAmelCase = 3 , ):
'''simple docstring'''
# A value less than 2 can cause an infinite loop in the algorit... | 248 |
"""simple docstring"""
lowerCAmelCase_ : Dict = {str(digit): digit**5 for digit in range(1_0)}
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowerCAmelCase ) )
def _l... | 248 | 1 |
from math import sqrt
def lowerCamelCase_ ( UpperCamelCase__ : int ) -> bool:
"""simple docstring"""
assert isinstance(UpperCamelCase__ , UpperCamelCase__ ) and (
number >= 0
), "'number' must been an int and positi... | 90 |
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__magic_name__ ):
"""simple docstring"""
snake_case_ = ['''onnx''']
def __init__( self , *lowerCamelCase__ , **lowerCamelCase__ ) ... | 90 | 1 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class lowercase_ ( unittest.TestCase ):
@require_torch
def Upp... | 369 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__name__)
__A = ... | 278 | 0 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowerCamelCase__ ( ) -> Dict:
UpperCamelCase_ = {
"""repo_name""": ["""test_repo1""", """test_repo2""", """test_repo3"""],
... | 122 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
from ... | 122 | 1 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowercase__ ( nn.Module ):
'''simple docstring'''
def __init__( self, __magic_name__ = 16, __magic_name__ = 88, __magic_name__ = Non... | 247 |
# 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
#
# Unl... | 247 | 1 |
from __future__ import annotations
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
return [ord(SCREAMING_SNAKE_CASE ) - 96 for elem in plain]
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
return "".join(chr(elem + 96 ) for elem in encod... | 43 |
'''simple docstring'''
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules... | 53 | 0 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_... | 227 |
'''simple docstring'''
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import tor... | 227 | 1 |
from typing import Any
def lowerCAmelCase ( lowerCAmelCase_ )-> List[str]:
if not input_list:
return []
lowerCAmelCase_ : int = [input_list.count(a_ ) for value in input_list]
lowerCAmelCase_ : str = max(a_ ) # Gets the maximum cou... | 262 |
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self , a ) -> None:
snake_case_ = set_counts
snake_case_ = max(a )
snake_case_ = len(a )
snake_case_ = [1] * num_sets
snake_ca... | 178 | 0 |
"""simple docstring"""
import warnings
warnings.warn(
'''memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '''
'''`from accelerate import find_executable_batch_size` to avoid this warning.''',
FutureWarning,
)
| 363 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
a : Optional[int] = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/m... | 79 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : int = ["""image_processor""", """toke... | 317 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructu... | 317 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
A__ : str = loggi... | 351 |
'''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, run_command, slow, to... | 0 | 0 |
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