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 |
|---|---|---|---|---|
def __snake_case ( _lowerCAmelCase : list ) -> Optional[int]:
if len(_snake_case ) <= 1:
return lst
A_ : Any = 1
while i < len(_snake_case ):
if lst[i - 1] <= lst[i]:
i += 1
else:
A_ : Tuple = lst[i], lst[i - 1]
... | 300 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def _snake_case ( _snake_case : list[list[float]] ):
lowerCAmelCase : str = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implement... | 60 | 0 |
"""simple docstring"""
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError("""To use the rich extension, install rich with `pip install rich`""")
| 355 |
"""simple docstring"""
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ ... | 161 | 0 |
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
A__ = collections.namedtuple("""_Datasets""", ["""train""", """validati... | 82 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
A__ = TypeVar("""T""")
A__ = TypeVar("""U""")
class __lowerCAmelCase ( Generic[T, U] ):
def __init__( self , _snake_case , _snake_ca... | 82 | 1 |
'''simple docstring'''
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvisio... | 366 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
__lowercase : Optional[Any] = True
except (ImportError, ModuleNotFoundError):
__lowercase : Dict = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', quiet=True)
... | 294 | 0 |
"""simple docstring"""
import os
from collections.abc import Iterator
def lowercase__ ( snake_case_ :str = "." ):
for dir_path, dir_names, filenames in os.walk(snake_case_ ):
__UpperCAmelCase = [d for d in dir_names if d != '''scripts''' and d[0] not in '''._''']
f... | 332 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class _UpperCAmelCase :
def __init__( self : Union[str, Any] , _lowercase : Optional[Any] ):
__UpperCAmelCase = str(id_ )
__UpperCAmelCase = None
... | 332 | 1 |
"""simple docstring"""
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCAmelCase__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0... | 362 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def _UpperCAmelCase ( __lowerCamelCase : str , __lowerCamelCase : dict ) -> str:
_snake_case = BeautifulSoup(requests.get(__lowerCamelCase , params=__lowerCamelCase ).content , '''html.parser''' )
_... | 40 | 0 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = R"""
Args:
... | 191 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase_ : List[str] = {
... | 81 | 0 |
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> Any:
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
lowercase_ = mf_knapsack(i - 1... | 361 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def _SCREAMING_SNAKE_CASE () -> Generator[int, None, None]:
'''simple docstring'''
lowercase_ = {}
lowercase_ = 2
while True:
lowercase_ = facto... | 313 | 0 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 324 |
'''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_avai... | 324 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__snake_case =logging.ge... | 55 |
'''simple docstring'''
import math
def a_ ( lowerCamelCase : int ):
lowerCAmelCase = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(lowerCamelCase )
def a_ ( lowerCamelCase : float = 1 ... | 55 | 1 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
f... | 5 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase ) -> Any:
_lowercase =str(id_ )
_lowercase =None
_lowercase =None
_lowercase ... | 5 | 1 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...te... | 277 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
__A = '''\
@misc{wu2016googles,
title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author={Yonghui Wu and Mike Schu... | 277 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
__SCREAMING_SNAKE_CASE : Dict = TypeVar('T')
class __A (Generic[T]):
'''simple docstring'''
def __init__( self : Optional[Any] , UpperCAmelCase_ : T... | 347 |
"""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... | 347 | 1 |
'''simple docstring'''
from bisect import bisect
from itertools import accumulate
def __lowerCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ) -> str:
__lowerCamelCase = sorted(zip(UpperCamelCase__ , UpperCamelCase__ ) ,... | 364 | '''simple docstring'''
from __future__ import annotations
def __lowerCAmelCase ( UpperCamelCase__ , UpperCamelCase__ ) -> list[list[int]]:
__lowerCamelCase = []
create_all_state(1 , UpperCamelCase__ , UpperCamelCase__ , [] , UpperCamelCase__ )
retu... | 237 | 0 |
"""simple docstring"""
import copy
import re
class snake_case__ :
_snake_case : Dict = """hp"""
_snake_case : List[str] = {}
_snake_case : int = None
@classmethod
def a__ ( cls , lowerCamelCase , lowerCamelCase ):
__a = prefix
... | 261 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__:int = logging.get_logger(__name__)
class snake_case__ ( snake_case_ ):
_snake_case : O... | 261 | 1 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def __SCREAMING_SNAKE_CASE ( __UpperCamelCase : Tuple , __UpperCamelCase : Any , __UpperCamelCase : List[str] ) -> Tuple:
"""simple docstring"""
... | 351 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase : Optional[int] = {
'''configuration_whisper''': ['''W... | 204 | 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 : Optional[int] = logging.get_logger(__name__)
a : Optional[int] = {
'andreasmad... | 56 |
'''simple docstring'''
import re
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
snake_case_ = re.compile(
r'''^(?:0|94|\+94|0{2}94)''' r'''7(0|1|2|4|5|6|7|8)''' r'''(-| |)''' r'''\d{7}$''' )
return bool(re.search(__UpperCAmelCase, __U... | 56 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _lowercase ) -> list:
if any(not isinstance(_lowercase , _lowercase ) or x < 0 for x in sequence ):
raise TypeError("""Sequence must be list of non-negative integers""" )
for _ in range(len(_lowercase ) ):
... | 338 |
'''simple docstring'''
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
"""split_dict""" , [
SplitDict(),
SplitDict({"""train""": SplitInfo(name="""train""" , num_bytes=1_3_3_7 , num_e... | 338 | 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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices... | 283 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokenization_commo... | 13 | 0 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...m... | 358 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__snake_case = {
"""configuration_conditional_detr""": [
"""CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""C... | 112 | 0 |
'''simple docstring'''
def __lowercase ( __lowercase = 5000_0000 ) -> int:
'''simple docstring'''
_A = set()
_A = int((limit - 24) ** (1 / 2) )
_A = set(range(3 , prime_square_limit + 1 , 2 ) )
primes.... | 79 |
'''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 ... | 161 | 0 |
'''simple docstring'''
from statistics import mean, stdev
def lowerCamelCase ( lowerCAmelCase : list , lowerCAmelCase : int = 3 ):
"""simple docstring"""
__magic_name__ : Any = min(lowerCAmelCase )
__magic_name__ : Any = max(lowerCAmelCas... | 275 |
'''simple docstring'''
def lowerCamelCase ( lowerCAmelCase : int ):
"""simple docstring"""
__magic_name__ : Optional[int] = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCamelCase ( lowerCAmelCase : int ):
"""simple ... | 275 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_ava... | 168 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
fro... | 168 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType
SCR... | 124 |
from math import log
from scipy.constants import Boltzmann, physical_constants
SCREAMING_SNAKE_CASE :Dict = 300 # TEMPERATURE (unit = K)
def UpperCAmelCase ( a_ , a_ , a_ , ) -> float:
"""simple docstring"""
if donor_conc <= 0:
r... | 124 | 1 |
"""simple docstring"""
def _A ( ):
"""simple docstring"""
for n in range(1 , 1_00_00_00 ):
yield n * (n + 1) // 2
def _A ( lowercase ):
"""simple docstring"""
a =1
a =2
while i * i <= n:
... | 81 |
"""simple docstring"""
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm... | 81 | 1 |
"""simple docstring"""
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCamelCase ( a__ ):
'''simple docstring'''
A_ : Any = (DDPMParallelScheduler,)
def _UpperCAmelCase ( self , ... | 153 |
"""simple docstring"""
class __lowerCamelCase :
'''simple docstring'''
def __init__( self , __UpperCAmelCase , __UpperCAmelCase ) -> Optional[Any]:
_a = name
_a = val
def __str__( self ) -> List[Any]... | 153 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : List[str] ):
"""simple docstring"""
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a P... | 64 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def __lowercase ( a__ ) -> Tuple:
__SCREAMING_SNAKE_CASE = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 257 | 0 |
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
__lowercase = logging.get_logger(__name__)
__lowercase = {
"""microsoft/bei... | 358 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepa... | 226 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __lowerCAmelCase ( un... | 45 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for te... | 301 | 0 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class SCREAMING_SNAKE_CASE__ ( nn.Module ):
"""simple docstring"""
a : int
... | 133 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class SCREAMING_SNAKE_CASE__ ( lowercase ... | 133 | 1 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipeline_test... | 127 |
"""simple docstring"""
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class _UpperCAmelCase :
UpperCamelCase = None
def lowerCamelCase ( self :List[Any] ):
A = self.feature_extraction_... | 292 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case = {
'''configuration_convnext''': ['''CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_M... | 355 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow... | 319 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class... | 237 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testi... | 237 | 1 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcessor, ResNetCon... | 353 | """simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCamelCase ( metaclass=lowerCAmelCase__ ):
SCREAMING_SNAKE_CASE_ = ["keras_nlp"]
def __init__( self, *lowerCAmelCase__, **lowerCAmelCase__) -> int:
requires... | 312 | 0 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE__ )
class snake_case ( SCREAMING_SNAKE_CASE__ ):
"""simple doc... | 98 |
"""simple docstring"""
def lowercase__ ( ) -> str:
'''simple docstring'''
lowercase : List[str] = 0
for i in range(1 , 10_01 ):
total += i**i
return str(_UpperCAmelCase )[-10:]
if __name__ == "__main__":
pr... | 255 | 0 |
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, AttnProcessor
from .modeling_u... | 363 |
from PIL import Image
def __magic_name__ ( __a : Image ):
'''simple docstring'''
UpperCamelCase__ , UpperCamelCase__ = image.size
UpperCamelCase__ = 0
UpperCamelCase__ = image.load()
for i in range(__a ):
for j in range(__a ... | 178 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : list[int] , lowercase : str ) -> list[int]:
_a = int(_UpperCAmelCase )
# Initialize Result
_a = []
# Traverse through all denomination
for denomination in reversed(_UpperC... | 63 |
from __future__ import annotations
def A ( _UpperCAmelCase : list[int] ) -> bool:
'''simple docstring'''
return len(set(_UpperCAmelCase ) ) == len(_UpperCAmelCase )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 339 | 0 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( __snake_case : Dict , __snake_case : Dict , __snake_c... | 145 |
from collections import defaultdict
from math import ceil, sqrt
def lowercase__ ( __snake_case : int = 1_000_000 , __snake_case : int = 10 ):
'''simple docstring'''
UpperCAmelCase_ : defaultdict = defaultdict(__snake_case )
... | 145 | 1 |
'''simple docstring'''
from collections.abc import Callable
def __lowerCamelCase ( __snake_case : Callable[[float], float], __snake_case : float, __snake_case : float ) -> float:
"""simple docstring"""
A__ : float =a
A__ :... | 134 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case : Union[str, Any] = logging.get_logger(__name__)
__snake_case : int = {
... | 134 | 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
from ...onnx import OnnxConfigWith... | 153 |
"""simple docstring"""
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 Nes... | 153 | 1 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def _lowerCamelCase( lowercase__ = True , *lowercase__ , **lowercase__ ) -> Optional[int]:
'''simple docstring'''
if not is_tqdm_available():
... | 295 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase = '''▁'''
lowerCAmelCase = {'''vocab_file''': '''spiece.model'''}
lowerCA... | 295 | 1 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
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
from ..models.auto.modeling_tf_auto imp... | 288 |
from collections import deque
from math import floor
from random import random
from time import time
class __a :
def __init__( self ) -> Dict:
'''simple docstring'''
lowercase__: Dict = {}
def SCREAMING_SNAKE_CASE__ ( s... | 288 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_... | 267 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unitt... | 267 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__snake_case = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConfig''', '''... | 367 | import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __snake_case ( lowerCamelCase__ ):
@require_torch
def UpperCAmelCase__ ( self ) -> List[str]:
'... | 78 | 0 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
UpperCAmelCase__ = logging.get_logger(__name__)
class lowercase_ ( lowercase ):
'''simple docstring'''
def __init__( self ... | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_availabl... | 181 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class snake_case_ :
__A : int
__A : int
class snake_case_ :
def __init__( self : str , lowercase... | 333 | import argparse
import datetime
def lowercase_ ( _lowerCamelCase : str):
lowercase__ : Optional[Any] = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturda... | 333 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json... | 68 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.... | 27 | 0 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def snake_case_() -> Any:
"""simple docstring"""
with offline(OfflineSimulationMode.CONNECTION_TIM... | 278 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__A = logging.get_logger(__name__)
__A = {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.t... | 278 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__SCREAMING_SNAKE_CASE :Optional[int] = {'''tokenization_byt5''': ['''ByT5Tokenizer''']}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
__SCREAMING_SNAKE_CASE ... | 22 |
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
lowercase__ =True
except ImportE... | 216 | 0 |
"""simple docstring"""
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... | 64 | """simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_r... | 64 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailabl... | 7 |
'''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_t... | 163 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase = {"""configuration_vit""": ["""VIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViT... | 35 | 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,
)
lowercase = {
"""configuration_xlm_roberta""... | 35 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 331 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def lowerCamelCase ( lowerCAmelCase : int = 200_0000 ):
"""simple docstring"""
__magic_name__ : list[int] = [0]
__magic_name__ : int
for idx in range(1 , ceil(sqrt... | 331 | 1 |
def _UpperCamelCase ( UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int ) -> int:
"""simple docstring"""
def count_of_possible_combinations(UpperCamelCase_ : int ) -> int:
if target < 0:
... | 365 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_co... | 122 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE :Any = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE :str = {
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json''',
... | 15 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __magic_name__ ( lowerCamelCase__ ):
"""simple docstring"""
__UpperCamelCase = (DDPMScheduler,)
def SCREAMING_SNAKE_CASE ( self :Union[s... | 300 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ :int = logging.get_logger(__name__)
A_ :Dict = {
'''BAAI/AltCLIP''': '''https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json''... | 245 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ :int = logging.get_logger(__name__)
A_ :List[str] = {
'''facebook/xlm-roberta-xl''': ''... | 245 | 1 |
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import jit
from transformers ... | 340 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'''configuration_convbert''': ['''CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ConvBertConfig''', '''Conv... | 340 | 1 |
'''simple docstring'''
from typing import Any
def UpperCAmelCase ( a_ , a_ , a_ , a_ , a_ , ) -> list:
"""simple docstring"""
_validation(
a_ , a_ , a_ , a_ , a_ , ... | 353 |
'''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 _lowerCAmelCa... | 164 | 0 |
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, AutoTokenizer, HfArgumentParser... | 12 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class lowercase__ ( lowercase ):
def __init__( self : Any ,lowerCamelCase__ : str ,lowerCamelCase__ : Tuple ,lowerCame... | 83 | 0 |
# using dfs for finding eulerian path traversal
def lowerCAmelCase_ ( UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_=None ) -> List[Any]:
UpperCamelCase_ = (path or []) + [u]
for v in graph[u]:
if visited_... | 328 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class _UpperCamelCase :
def __init__( self: str ) -> Any:
"""simple docstring"""
UpperCamelCase_ = ""
UpperCamelCase_ = "... | 328 | 1 |
"""simple docstring"""
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, ... | 25 |
"""simple docstring"""
import mpmath # for roots of unity
import numpy as np
class lowerCAmelCase_ :
"""simple docstring"""
def __init__(self , SCREAMING_SNAKE_CASE__=None , SCREAMING_SNAKE_CASE__=None ) -> Dict:
"""simple docstring... | 25 | 1 |
from __future__ import annotations
from math import pi, sqrt
def _a ( lowerCamelCase: float , lowerCamelCase: float ) -> tuple:
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be ... | 250 |
import math
def _a ( lowerCamelCase: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negativ... | 250 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerT... | 74 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowercase = {'''configuration_deit''': ['''DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeiTConfig''... | 74 | 1 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Opt... | 364 |
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import... | 158 | 0 |
"""simple docstring"""
A_ = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
A_ = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def UpperCAmelCase__ (snake_case__ : dict[int, list[int]] , snake_case__ : int , snake_case__ : list[bo... | 64 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ (snake_case__ : list[int] , snake_case__ : int ):
"""simple docstring"""
if len(snake_case__ ) < k or k < 0:
raise ValueError("""Invalid Input""" )
_snake_case ... | 64 | 1 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDIT... | 348 |
# 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
#
# Unles... | 348 | 1 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def lowerCamelCase_ ( UpperCamelCase__ : List[Any] , UpperCamelCase__ : Optional[int] , UpperCamelCase__ : str , UpperCamelCa... | 90 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def UpperCAmelCase_ ( __UpperCAmelCase : bytes , __UpperCAmelCase : int ) -> np.array:
SCREAMING_SNAKE_CASE_ = f"{sampling_rate}"
SCREAMING_SN... | 225 | 0 |
"""simple docstring"""
import os
__A : Dict = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1000}
def lowercase ( _SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
_UpperCAmelCase = 0
_UpperCAmelCa... | 326 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class _a ( logging.LoggerAdapter):
"""simple docstring"""
@staticmethod
def lowercase__ ( __UpperCamelCase : Optional[Any] )->List[Any]:
_UpperCAmelCase = ... | 326 | 1 |
def _A ( SCREAMING_SNAKE_CASE : list ):
"""simple docstring"""
if any(not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) or x < 0 for x in sequence ):
raise TypeError("Sequence must be list of non-negative integers" )
... | 95 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""sail/poolformer_s12""": """https... | 82 | 0 |
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,
StableDiffusion... | 245 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common ... | 245 | 1 |
'''simple docstring'''
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
f... | 4 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__snake_case : Dict = logging.get_logger(__name__)
__snake_case : Any ... | 248 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaT... | 112 |
"""simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VAR... | 112 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase : int = {
'''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GraphormerConfig'''],
}
try:
i... | 233 |
from __future__ import annotations
def snake_case_ ( lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_of_bytes:
raise ValueError(""... | 233 | 1 |
def lowerCamelCase_ ( lowerCAmelCase: List[Any] )-> Optional[int]:
if not head:
return True
# split the list to two parts
_snake_case , _snake_case : Union[str, Any] = head.next, head
while fast and fast.next:
_snake_case : List[str] = f... | 260 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common impor... | 260 | 1 |
"""simple docstring"""
def lowercase ( _snake_case : Tuple , _snake_case : Dict ) ->bool:
"""simple docstring"""
__snake_case : Dict = len(UpperCamelCase_ ) + 1
__snake_case : Tuple = len(UpperCamelCase_ ) + 1
# dp is a 2d matr... | 102 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class lowercase__ ( nn.Module ):
A__ : int
A__ : int
A__ : float =0.0
A__ : int =... | 176 | 0 |
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
_lowerCamelCase : List[str] = """\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},
author={Wang,... | 231 |
from __future__ import annotations
from typing import Any
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> None:
"""simple docstring"""
create_state_space_tree(lowercase_ , [] , 0 )
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ ... | 231 | 1 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class _UpperCAmelCase :
'''simple docstring'''
def __init__(self , a_ ):
'''simple docstring'''
__snake_case : List[str] = list_of_points
# Degree determ... | 102 |
"""simple docstring"""
from __future__ import annotations
def __a ( __lowerCamelCase, __lowerCamelCase ):
UpperCAmelCase_ , UpperCAmelCase_ : str = set(__lowerCamelCase ), [start]
while stack:
UpperCAmelCase_ : Any = stack.pop()
explored... | 61 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(_... | 358 | from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, FlaxTi... | 119 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'microsoft/unispeech-large-1500h-cv': (
'https://huggingfa... | 84 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCAmelCase ( __UpperCamelCase ):
UpperCAmelCase__ = """M-CLIP"""
def __init__( self : Optional[Any] , UpperCAmelCase : Union[str, Any]=1024 , UpperCAmelCas... | 50 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def A_ ( _lowerCAmelCase : Sequence[float], _lowerCAmelCase : bool = False ):
"""simple docstring"""
if not arr:
return 0
_a = 0 if allow_empty_subarrays else float('''-inf''' ... | 354 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__snake_case = logging.get_logger(__name__)
class __lowerCamelCase ( a__ ):
'''simple docstring'''
def __init__( self , *__UpperCAmelC... | 153 | 0 |
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
import onnxruntime as ... | 280 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> float:
if days_between_payments <= 0:
raise ValueError('days_between_payments must be > 0' )
if daily_interest_rate < 0:
raise ValueError('daily_interest_rate must... | 280 | 1 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from transf... | 370 |
from __future__ import annotations
def __lowerCAmelCase ( a__ , a__ = None ) -> list[list[str]]:
__a = word_bank or []
# create a table
__a = len(a__ ) + 1
__a = []
for _ in range(a__ ):
table.append([] )
# seed value... | 33 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A ( UpperCAmelCase_ ):
__UpperCAmelCase : Union[str, Any] = ['image_processor', 'tokenizer']
__UpperCAmelCase : Dict = 'CLIPImageProcessor'
... | 65 | import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowerCAmelCase_ ( __A ) -> Dict:
'''simple docstring'''
UpperCAmelCase__ = [
"encoder.version",
"dec... | 65 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _A ( __lowercase , unittest.TestCase ):
... | 13 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
Wa... | 13 | 1 |
import string
def UpperCamelCase ( __magic_name__ : str ) -> int:
"""simple docstring"""
lowercase__ = """"""
for i in sequence:
lowercase__ = ord(_A )
if 65 <= extract <= 90:
output += chr(155 - extract )
elif 97 <=... | 305 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 188 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
__lowerCAmelCase = logging.get_logger(__name__)
class __magic_name__ ( _UpperCamelCase ):
def __init__( self : List[str] ,*_Uppe... | 107 |
'''simple docstring'''
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers i... | 107 | 1 |
import importlib
import inspect
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_config_docstrings.py
lowerCAmelCase__ : List[str] = '''src/transformers'''
# This is to make sure the transformers mo... | 143 |
"""simple docstring"""
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.preproce... | 247 | 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... | 67 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def a__ ( _SCREAMING_SNAKE_CASE : str = "" , ) -> bool:
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(" " , "" ).lower() ).values() ... | 67 | 1 |
"""simple docstring"""
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
UpperCAmelCase_ : Union[str, Any] = {1: (1, 1), 2: (2, 1), 3: (3... | 91 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _SCREAMING_SNAKE_CASE ( _lowercase : np.ndarray , _lowercase : np.ndarray ) ->float:
'''simple docstring''... | 105 | 0 |
from __future__ import annotations
import pandas as pd
def __magic_name__ ( __a : list[int] , __a : list[int] , __a : int ):
'''simple docstring'''
UpperCamelCase__ = [0] * no_of_processes
UpperCamelCase__ = [0] * no_of_processes
# Copy the ... | 351 |
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
if is_torch_available():
... | 178 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Union[str, Any] = {'... | 80 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 181 | 0 |
from ..utils import DummyObject, requires_backends
class lowercase_ ( metaclass=lowercase ):
'''simple docstring'''
__snake_case = ['''note_seq''']
def __init__( self : int , *__UpperCAmelCase : Lis... | 26 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
UpperCAmelCase__ = logging.get... | 26 | 1 |
def A ( _lowerCamelCase = 1_000 ):
'''simple docstring'''
_lowerCAmelCase : Dict = -1
_lowerCAmelCase : Dict = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
... | 36 |
import unittest
from transformers import LiltConfig, 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, id... | 36 | 1 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ran... | 360 | def snake_case (__lowercase ) -> list:
'''simple docstring'''
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(__lowercase ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__('doctest').testmod() | 284 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _UpperCAm... | 33 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A : Dict ={
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if ... | 41 | 0 |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState, Parti... | 99 |
from ..utils import DummyObject, requires_backends
class __UpperCAmelCase ( metaclass=lowerCamelCase__ ):
UpperCamelCase = ["""onnx"""]
def __init__( self : int, *__A : Optional[Any], **__A : Dict ):
requires_backends(self, ['''on... | 99 | 1 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers... | 63 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
imp... | 266 | 0 |
from __future__ import annotations
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
# Checks if the entire collection has been sorted
if len(SCREAMING_SNAKE_CASE__ ) <= 1 or n <= 1:
return
insert_next(SCREAMING_SNAKE_CASE__ , n - 1 )
rec_insertion_sor... | 356 |
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 | 0 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def a ( snake_case__: Optional[int] , snake_case__: Optional[int] , snake_case__: Union[str, Any] ):
'''simple docstring'''
lowercase_ ... | 30 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(check_device=Fa... | 99 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNetC... | 296 |
"""simple docstring"""
import cva
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , snake_case : float , snake_case : int ):
'''simple docstring'''
if k in (0.04, 0.06):
... | 296 | 1 |
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