code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
snake_case__ : List[Any] = logging.get_logger(__name__)
class snake_case_( a__ ):
def __init__( self : Dict , *UpperCamelCase_ : List[st... | 60 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : Dict = 3
_UpperCamelCase : Any = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 1_5 == 0:
result -= a
... | 83 | 0 |
"""simple docstring"""
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transfo... | 61 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,... | 83 | 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
_A = logging.get_logger(__name__)
_A = {
'hustvl/yolos-small': 'https://huggi... | 62 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
Au... | 83 | 0 |
'''simple docstring'''
from ....utils import logging
lowerCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
def __init__( self : Tuple , __a : int , ... | 63 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class lowercase__ :
lowercase__ = field(
metadata={"""help""": """... | 83 | 0 |
"""simple docstring"""
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class lowercase:
'''simple docstring'''
def __init__( self: List[Any], a_: List[str] ):
'''simple docstring'''
... | 64 |
'''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_ : Dict = logging.get_logger(__... | 83 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase__ = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
'tokenization_biogpt': ['BioGptTokenizer']... | 65 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class lowercase__ :
def __init__( self : List[Any] ,lowerCamelCase__ : int ,lowerCamelCase__ : MutableSequence[float] ):
'''simple docstring'''
if len(l... | 83 | 0 |
"""simple docstring"""
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def A_ ( _lowercase, _lowercase, _lowercase ):
'''simple docstring'''
snake_case_ :str... | 66 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowercase__ ( lowercase ):
@require_torch
def UpperCamelCase_ ( self : Dict ):
... | 83 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ) ->... | 67 |
'''simple docstring'''
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 j... | 83 | 0 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> None:
... | 68 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
snake_case_ : ... | 83 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase = logging.get_logger(__name__)
__UpperCamelCase = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.jso... | 69 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import S... | 83 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class UpperCAmelCase :
_lowercas... | 70 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1 , UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : int = 1
_UpperCamelCase : Union[str, Any] = 0
for divide_by_number in range(UpperCAmelCase_ , digit + 1 ):
_UpperCamelCase : list[int... | 83 | 0 |
def A ( a_ = 1_000 ) -> int:
return sum(e for e in range(3 ,a_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f"{solution() = }")
| 71 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
if num < 0:
return False
_UpperCamelCase : int = num
_UpperCamelCase : int = 0
while num > 0:
_UpperCamelCase : str = rev_num * 1_0 + (num % 1_0)
num //= 1_0... | 83 | 0 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class ... | 72 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
_UpperCamelCase : List[str] = abs(UpperCAmelCase_ )
_UpperCamelCase : int = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def A__ ( UpperCAmelCase_ ):
... | 83 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_xl... | 73 |
'''simple docstring'''
from math import pi
def A__ ( UpperCAmelCase_ , UpperCAmelCase_ ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 83 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/re... | 74 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : int = logging.get_logger(__name__)
snake_case_ : Optional[Any] = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}
c... | 83 | 0 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def a_ ( __snake_case : dict , __snake_case : str , __snake_case : set , __snake_case : set , __snake_case : dict , ... | 75 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 83 | 0 |
import random
from typing import Any
def lowerCamelCase__ ( _a):
for _ in range(len(_a)):
SCREAMING_SNAKE_CASE : Tuple = random.randint(0 , len(_a) - 1)
SCREAMING_SNAKE_CASE : Union[str, Any] = random.randint(0 , len(_a) - 1)
SCREAMING_SNAKE_CASE ,SC... | 76 |
'''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logg... | 83 | 0 |
"""simple docstring"""
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 a_ ( ):
'''simple docstring'''
raise RuntimeError('CUDA out of memory.' ... | 77 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .to... | 83 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_=28123 ):
UpperCAmelCase = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1 ):
... | 78 |
'''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 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'... | 79 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
snake_case_ : Any = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def A__ ( ):
... | 83 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
a__ : Optional[int] = logging.get_logger(__name__)
class lowercase_ ( a__ ):
def __init__( self , *a , **a ):
warnings.war... | 80 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowercase )... | 83 | 0 |
"""simple docstring"""
def _A ( lowercase , lowercase ):
"""simple docstring"""
return "\n".join(
f'''{number} * {i} = {number * i}''' for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplicat... | 81 |
'''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Optional[Any] = logging.get_logger(__name__)
snake_case_ : int = {
'microsoft/xprophetnet-large-wiki100-cased': (
'http... | 83 | 0 |
# 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 be considered
# since ... | 82 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : Dict = 3
_UpperCamelCase : Any = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 1_5 == 0:
result -= a
... | 83 | 0 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
__UpperCAmelCase = get_logger(__name__)
__UpperCAmelCase = R'\n Args:\n input_ids (`jnp... | 84 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,... | 83 | 0 |
'''simple docstring'''
from collections import namedtuple
_SCREAMING_SNAKE_CASE : Optional[Any] = namedtuple("from_to", "from_ to")
_SCREAMING_SNAKE_CASE : Dict = {
"cubicmeter": from_to(1, 1),
"litre": from_to(0.0_0_1, 1000),
"kilolitre": from_to(1, 1),
"gallon... | 85 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
Au... | 83 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"""Salesforce/blip-vqa-base""": """https://huggingface.co/Salesforce... | 86 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class lowercase__ :
lowercase__ = field(
metadata={"""help""": """... | 83 | 0 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class snake_case_ ( unittest.TestCase ):
def __UpperCamelCase ( self : Union[str, Any] ) -> int:
... | 87 |
'''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_ : Dict = logging.get_logger(__... | 83 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCAmelCase : int = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
... | 88 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class lowercase__ :
def __init__( self : List[Any] ,lowerCamelCase__ : int ,lowerCamelCase__ : MutableSequence[float] ):
'''simple docstring'''
if len(l... | 83 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_... | 89 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowercase__ ( lowercase ):
@require_torch
def UpperCamelCase_ ( self : Dict ):
... | 83 | 0 |
from itertools import permutations
def lowerCamelCase_ ( UpperCamelCase__ : tuple ) -> bool:
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if n... | 90 |
'''simple docstring'''
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 j... | 83 | 0 |
"""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()
UpperCAmelCase_ : List[str] = [
... | 91 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
snake_case_ : ... | 83 | 0 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = OrderedDict(
[
... | 92 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import S... | 83 | 0 |
'''simple docstring'''
import os
import string
import sys
_lowercase : str = 1 << 8
_lowercase : Tuple = {
"tab": ord("\t"),
"newline": ord("\r"),
"esc": 2_7,
"up": 6_5 + ARROW_KEY_FLAG,
"down": 6_6 + ARROW_KEY_FLAG,
"right": 6_7... | 93 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1 , UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : int = 1
_UpperCamelCase : Union[str, Any] = 0
for divide_by_number in range(UpperCAmelCase_ , digit + 1 ):
_UpperCamelCase : list[int... | 83 | 0 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
snake_case : int = (3, 9, -11, 0, 7, 5, 1, -1)
snake_case : Optional[Any] = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class _snake_case :
SCREAMING_SNAK... | 94 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
if num < 0:
return False
_UpperCamelCase : int = num
_UpperCamelCase : int = 0
while num > 0:
_UpperCamelCase : str = rev_num * 1_0 + (num % 1_0)
num //= 1_0... | 83 | 0 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
UpperCAmelCase : in... | 95 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
_UpperCamelCase : List[str] = abs(UpperCAmelCase_ )
_UpperCamelCase : int = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def A__ ( UpperCAmelCase_ ):
... | 83 | 0 |
"""simple docstring"""
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_... | 96 |
'''simple docstring'''
from math import pi
def A__ ( UpperCAmelCase_ , UpperCAmelCase_ ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 83 | 0 |
'''simple docstring'''
class lowercase :
"""simple docstring"""
def __init__( self , UpperCamelCase_ ):
'''simple docstring'''
UpperCamelCase__ :Optional[int] = len(UpperCamelCase_ )
UpperCamelCase__ :str = [0] * len_array
if len_ar... | 97 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : int = logging.get_logger(__name__)
snake_case_ : Optional[Any] = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}
c... | 83 | 0 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultiste... | 98 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 83 | 0 |
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__UpperCAmelCase ):
"""simple docstring"""
__A : int = ['''sentencepiece''']
def __init__( self , *lowercase , **lowercase) -> List[str]:
'''simple docstring... | 99 |
'''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logg... | 83 | 0 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 100 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .to... | 83 | 0 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_INPAIN... | 101 |
'''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 |
"""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 _UpperCAmelCase ( __snake_case )... | 102 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
snake_case_ : Any = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def A__ ( ):
... | 83 | 0 |
# 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]' when switching between checko... | 103 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowercase )... | 83 | 0 |
'''simple docstring'''
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transforme... | 104 |
'''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Optional[Any] = logging.get_logger(__name__)
snake_case_ : int = {
'microsoft/xprophetnet-large-wiki100-cased': (
'http... | 83 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenizati... | 105 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : Dict = 3
_UpperCamelCase : Any = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 1_5 == 0:
result -= a
... | 83 | 0 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( A_ , A_ ):
while b:
lowerCAmelCase__ ,lowerCAmelCase__ : Optional[int] = b, a % b
return a
def __SCREAMING_SNAKE_CASE ( A_ , A_ ):
return a if b == 0 else euclidean_gcd_recursive(A_ , a % b )
def ... | 106 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,... | 83 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
__lowerCAmelCase : int = {
'facebook/d... | 107 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
Au... | 83 | 0 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
... | 108 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class lowercase__ :
lowercase__ = field(
metadata={"""help""": """... | 83 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy ... | 109 |
'''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_ : Dict = logging.get_logger(__... | 83 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
'https://huggingface.co/CarlCochet/trajectory-transformer-... | 110 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class lowercase__ :
def __init__( self : List[Any] ,lowerCamelCase__ : int ,lowerCamelCase__ : MutableSequence[float] ):
'''simple docstring'''
if len(l... | 83 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
lowerCAmelCase__ = 1.0_5_4_5_7_1_8_1_7E-3_4 # unit of ℏ : J * s
lowerCAmelCase__ = 3E8 # unit of c : m * s^-1
... | 72 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowercase__ ( lowercase ):
@require_torch
def UpperCamelCase_ ( self : Dict ):
... | 83 | 0 |
import requests
lowerCamelCase = '' # <-- Put your OpenWeatherMap appid here!
lowerCamelCase = 'https://api.openweathermap.org/data/2.5/'
def a_ ( SCREAMING_SNAKE_CASE__ : Union[str, Any] = "Chicago" , SCREAMING_SNAKE_CASE__ : Optional[Any] = APPID ... | 199 |
'''simple docstring'''
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 j... | 83 | 0 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
'google/efficientnet-b7': 'ht... | 82 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
snake_case_ : ... | 83 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( _lowercase):
@staticmethod
@abstractmethod
def _UpperCamelCase ( __UpperCamelCase : ArgumentParser ) -> int:
ra... | 256 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import S... | 83 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowerCamelCase : str = logging.get_logger(__name__)
_lowerCamelCase : int = {
'Visual-Attention-Network/van-base': (
'https://huggingface.co/Visual... | 167 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1 , UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : int = 1
_UpperCamelCase : Union[str, Any] = 0
for divide_by_number in range(UpperCAmelCase_ , digit + 1 ):
_UpperCamelCase : list[int... | 83 | 0 |
'''simple docstring'''
def lowercase__ ( __lowercase : Union[str, Any] ) -> Optional[int]:
"""simple docstring"""
__UpperCamelCase = abs(UpperCAmelCase_ )
__UpperCamelCase = 0
while n > 0:
res += n % 10
n //=... | 53 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
if num < 0:
return False
_UpperCamelCase : int = num
_UpperCamelCase : int = 0
while num > 0:
_UpperCamelCase : str = rev_num * 1_0 + (num % 1_0)
num //= 1_0... | 83 | 0 |
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 jnp
from tran... | 128 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
_UpperCamelCase : List[str] = abs(UpperCAmelCase_ )
_UpperCamelCase : int = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def A__ ( UpperCAmelCase_ ):
... | 83 | 0 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logging.INFO
)
lowercase__ :s... | 101 |
'''simple docstring'''
from math import pi
def A__ ( UpperCAmelCase_ , UpperCAmelCase_ ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 83 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCamelCase_ = {'tokenization_byt5': ['ByT5Tokenizer']}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
UpperCamelCase_ = ... | 251 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : int = logging.get_logger(__name__)
snake_case_ : Optional[Any] = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}
c... | 83 | 0 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
"""simple docstring"""
def ... | 108 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 83 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__A : str = '\\n\n'
__A : str = '\nPerplexity (... | 120 |
'''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logg... | 83 | 0 |
"""simple docstring"""
def snake_case_ ( A_ : Optional[Any] ):
'''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 Perfect... | 72 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .to... | 83 | 0 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMI... | 199 |
'''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 |
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
A__ = logging.get_logger(__name__)
def _UpperCAmelCase ( snake_case ):
"""simple docstring"""
if isinstance(UpperCAmelCase_ , np.ndarray ):
re... | 82 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
snake_case_ : Any = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def A__ ( ):
... | 83 | 0 |
"""simple docstring"""
from collections.abc import Generator
def lowercase ( ) -> Dict:
_UpperCamelCase = 0, 1
while True:
_UpperCamelCase = b, a + b
yield b
def lowercase ( a__ : str = 1000 ) -> Tuple:
_Upper... | 256 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowercase )... | 83 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase : Any = {
'configuration_informer': [
'INFORMER_PRETRAINED_CONFIG_ARCHIVE_M... | 167 |
'''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Optional[Any] = logging.get_logger(__name__)
snake_case_ : int = {
'microsoft/xprophetnet-large-wiki100-cased': (
'http... | 83 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available,... | 53 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : Dict = 3
_UpperCamelCase : Any = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 1_5 == 0:
result -= a
... | 83 | 0 |
from __future__ import annotations
from statistics import mean
def _lowerCAmelCase (_lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase):
UpperCamelCase_ = [0] * no_of_processes
UpperCamelCase_ = [0] * no_of_processes
# Initialize remaining_time ... | 128 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,... | 83 | 0 |
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
lowercase__ :int = logging.get_logger(__name__)
lowercase_... | 101 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
Au... | 83 | 0 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
UpperCamelCase_ = logging.get_logger... | 251 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class lowercase__ :
lowercase__ = field(
metadata={"""help""": """... | 83 | 0 |
"""simple docstring"""
def a__ ( SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
if length <= 0 or not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(UpperCA... | 108 |
'''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_ : Dict = logging.get_logger(__... | 83 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__A : int = {
'configuration_vision_text_dual_encoder': ['Vi... | 120 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class lowercase__ :
def __init__( self : List[Any] ,lowerCamelCase__ : int ,lowerCamelCase__ : MutableSequence[float] ):
'''simple docstring'''
if len(l... | 83 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForCondi... | 72 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowercase__ ( lowercase ):
@require_torch
def UpperCamelCase_ ( self : Dict ):
... | 83 | 0 |
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowerCamelCase = numpy.array([0, 0])
lowerCamelCase = numpy.array([0.5, 0.866_0254])
lowerCamelCase = numpy.array([1, 0])
lowerCamelCa... | 199 |
'''simple docstring'''
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 j... | 83 | 0 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __lowerCAmelCase ( lowerCamelCase__ , unittest.TestCase... | 82 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
snake_case_ : ... | 83 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase = {
'configuration_groupvit': [
'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'GroupViTConfig',
'GroupViTOnnxCon... | 256 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import S... | 83 | 0 |
"""simple docstring"""
import os
def lowercase_ ( ):
"""simple docstring"""
A_ : List[str] = os.path.join(os.path.dirname(UpperCAmelCase_ ) , '''num.txt''' )
with open(UpperCAmelCase_ ) as file_hand:
return str(sum(int(UpperCAmelCase... | 167 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1 , UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : int = 1
_UpperCamelCase : Union[str, Any] = 0
for divide_by_number in range(UpperCAmelCase_ , digit + 1 ):
_UpperCamelCase : list[int... | 83 | 0 |
'''simple docstring'''
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler... | 53 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
if num < 0:
return False
_UpperCamelCase : int = num
_UpperCamelCase : int = 0
while num > 0:
_UpperCamelCase : str = rev_num * 1_0 + (num % 1_0)
num //= 1_0... | 83 | 0 |
from __future__ import annotations
from collections.abc import MutableSequence
class _lowercase :
'''simple docstring'''
def __init__( self , snake_case__ , snake_case__ ):
'''simple docstring'''
if len(lowerCamelCase__ ) != degree + 1:
... | 128 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
_UpperCamelCase : List[str] = abs(UpperCAmelCase_ )
_UpperCamelCase : int = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def A__ ( UpperCAmelCase_ ):
... | 83 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstr... | 101 |
'''simple docstring'''
from math import pi
def A__ ( UpperCAmelCase_ , UpperCAmelCase_ ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 83 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnal... | 251 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : int = logging.get_logger(__name__)
snake_case_ : Optional[Any] = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}
c... | 83 | 0 |
"""simple docstring"""
def a__ ( SCREAMING_SNAKE_CASE : Optional[Any] ):
'''simple docstring'''
lowerCAmelCase : List[Any] = generate_pascal_triangle(UpperCAmelCase_ )
for row_idx in range(UpperCAmelCase_ ):
# Print left spaces
for _ in rang... | 108 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 83 | 0 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
... | 120 |
'''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logg... | 83 | 0 |
"""simple docstring"""
lowerCAmelCase__ = 9.8_0_6_6_5
def snake_case_ ( A_ : Optional[int], A_ : Union[str, Any], A_ : Dict = g ):
'''simple docstring'''
if fluid_density <= 0:
raise ValueError('''Impossible fluid densit... | 72 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .to... | 83 | 0 |
def a_ ( SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
_lowerCamelCase : Optional[int] =[False] * len(UpperCAmelCase_ )
_lowerCamelCase : List[Any] =[-1] * len(UpperCAmelCase_ )
def dfs(SCREAMING_SNAKE_CASE__ : Any , ... | 199 |
'''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 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_p... | 82 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
snake_case_ : Any = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def A__ ( ):
... | 83 | 0 |
"""simple docstring"""
import re
def lowercase ( a__ : Dict ) -> Any:
_UpperCamelCase = re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''' )
if match := re.search(UpperCAmelCase_ , UpperCAmelCase_ ):
return match.string == phone
return False
... | 256 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowercase )... | 83 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _UpperCAmelCase ):
"""simple docstring"""
A_ : Union[str, Any] = 0.00
A_ : Any = 0
for resistor in resistors:
if resistor <= 0:
A_ : Optional[... | 167 |
'''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Optional[Any] = logging.get_logger(__name__)
snake_case_ : int = {
'microsoft/xprophetnet-large-wiki100-cased': (
'http... | 83 | 0 |
'''simple docstring'''
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization imp... | 53 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : Dict = 3
_UpperCamelCase : Any = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 1_5 == 0:
result -= a
... | 83 | 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
UpperCAmelCase : int =logging.get_logger(__name__)
UpperCAmelCase : Uni... | 128 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,... | 83 | 0 |
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_remote_code
from ...image_pr... | 101 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
Au... | 83 | 0 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class _a ( unittest.TestCase ):
'''simple docstring'''
def ... | 251 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class lowercase__ :
lowercase__ = field(
metadata={"""help""": """... | 83 | 0 |
"""simple docstring"""
import os
import pytest
from transformers.dynamic_module_utils import get_imports
lowerCAmelCase__ = '\nimport os\n'
lowerCAmelCase__ = '\ndef foo():\n import os\n return False\n'
lowerCAmelCase__ = '\ndef foo():\n def bar():\n if T... | 108 |
'''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_ : Dict = logging.get_logger(__... | 83 | 0 |
'''simple docstring'''
def UpperCamelCase_ ( A__ : Union[str, Any] ):
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = []
lowerCAmelCase_ : Optional[Any] = set({"""(""", """[""", """{"""} )
lowerCAmelCase_ : Optional[in... | 120 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class lowercase__ :
def __init__( self : List[Any] ,lowerCamelCase__ : int ,lowerCamelCase__ : MutableSequence[float] ):
'''simple docstring'''
if len(l... | 83 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=_lowercase):
snake_case__ : Any = ["note_seq"]
def __init__( self : Tuple , *__lowerCAmelCase : Union[str, Any] , **__lowerCAmel... | 72 |
'''simple docstring'''
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowercase__ ( lowercase ):
@require_torch
def UpperCamelCase_ ( self : Dict ):
... | 83 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase = {
'configuration_xlm_roberta_xl': [
'XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XLMRobertaXLConfig',
'XLMRobertaXLOnnxConfig',
... | 199 |
'''simple docstring'''
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 j... | 83 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A__ = {'configuration_xlnet': ['XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLNetConfig']... | 82 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
snake_case_ : ... | 83 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'AutoformerConfig'... | 256 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import S... | 83 | 0 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerc... | 167 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ = 1 , UpperCAmelCase_ = 1_0_0_0 ):
_UpperCamelCase : int = 1
_UpperCamelCase : Union[str, Any] = 0
for divide_by_number in range(UpperCAmelCase_ , digit + 1 ):
_UpperCamelCase : list[int... | 83 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
a__ : ... | 53 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
if num < 0:
return False
_UpperCamelCase : int = num
_UpperCamelCase : int = 0
while num > 0:
_UpperCamelCase : str = rev_num * 1_0 + (num % 1_0)
num //= 1_0... | 83 | 0 |
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