code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A : List[str] = {
'''configuration_blip''': [
'''BLIP_PRETRAINED_CONFIG_A... | 353 |
"""simple docstring"""
import argparse
import os
import re
__A : Dict = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
__A : Union[str, Any] = re.compile(R'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
__A : Dict ... | 27 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : List[str] = logging.get_logger(__name__)
__A : List[str] = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-ha... | 354 |
"""simple docstring"""
def A_ ( snake_case_ : list[int] ):
'''simple docstring'''
if not numbers:
return 0
if not isinstance(snake_case_ ,(list, tuple) ) or not all(
isinstance(snake_case_ ,snake_case_ ) for number in numbers ):
... | 27 | 0 |
"""simple docstring"""
import argparse
import gc
import json
import os
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
fr... | 355 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline... | 27 | 0 |
"""simple docstring"""
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load... | 356 |
"""simple docstring"""
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def A_ ( snake_case_ : Dataset ,snake_case_ : Dict[str, str] ):
... | 27 | 0 |
import re
import subprocess
import sys
__A : str = subprocess.check_output('''git merge-base main HEAD'''.split()).decode('''utf-8''')
__A : Union[str, Any] = subprocess.check_output(F'''git diff --name-only {fork_point_sha}'''.split()).decode('''utf-8''').split()
__A : Di... | 357 |
"""simple docstring"""
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCamelCase ( _UpperCAmelCase ):
lowercase : Union[str, Any] = 'EncodecFeatureExtractor'
lowercase : Lis... | 27 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A : Union[str, Any] = {
'''configuration_data2vec_audio''': ['''DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Data2VecAud... | 358 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def A_ ( snake_case_ : str = "https://www.worldometers.info/coronavirus" ):
'''simple docstring'''
UpperCamelCase : Any = BeautifulSoup(requests.get(snake_case_ ).text ,"""html.... | 27 | 0 |
import qiskit
def A_ ( snake_case_ : int ,snake_case_ : int ):
'''simple docstring'''
UpperCamelCase : str = qiskit.Aer.get_backend("""aer_simulator""" )
UpperCamelCase : Any = qiskit.QuantumCircuit(4 ,2 )
# ... | 359 |
"""simple docstring"""
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 M... | 27 | 0 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowerCamelCase ( nn.Module ):
def __init__( self , SCREAMING_SNAKE_CASE_ = 16 , SCREAMING_SNAKE_CASE_ = 88 , SCR... | 360 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowerCamelCase ( nn.Module ):
def __init__( self , SCREAMING_SNAKE_CASE_ = 16 , SCREAMING_SNAKE_CASE_ = 88 , SCRE... | 27 | 0 |
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTensor
from accelerate import Acce... | 361 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Optional[int] = logging.get_logger(__name__)
__A : Optional[int] = {
'''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/co... | 27 | 0 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A : Tuple = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplificat... | 362 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acce... | 27 | 0 |
"""simple docstring"""
def A_ ( snake_case_ : list[list[int]] ,snake_case_ : int ,snake_case_ : int ,snake_case_ : set ):
'''simple docstring'''
UpperCamelCase : int = len(snake_case_ ), len(grid[0] )
if (
... | 363 |
"""simple docstring"""
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__A : Any = logging.get_logger(__name__)
__A : Dict = {'''vocab_fi... | 27 | 0 |
"""simple docstring"""
import os
import re
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
__A : str = logging.get_logger(__name__)
__... | 364 |
"""simple docstring"""
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, Auto... | 27 | 0 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def A_ ( snake_case_ : Any ):... | 365 |
"""simple docstring"""
import argparse
import os
import re
__A : Any = '''src/transformers'''
# Pattern that looks at the indentation in a line.
__A : Tuple = re.compile(R'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
__A : List[Any] ... | 27 | 0 |
"""simple docstring"""
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
__A : List[str] = lo... | 366 |
"""simple docstring"""
def A_ ( snake_case_ : int ):
'''simple docstring'''
if number < 0:
raise ValueError("""number must not be negative""" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 27 | 0 |
"""simple docstring"""
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common ... | 367 |
"""simple docstring"""
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_uti... | 27 | 0 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
__A : Any = logging.get_logger(__name__) # pylint: disable=invalid-name
class lowerCamel... | 368 |
"""simple docstring"""
from collections.abc import Callable
def A_ ( snake_case_ : Callable[[float], float] ,snake_case_ : float ,snake_case_ : float ):
'''simple docstring'''
UpperCamelCase : float = a
UpperCamelCase : flo... | 27 | 0 |
"""simple docstring"""
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTester... | 369 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_util... | 27 | 0 |
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 checkouts and running tests.
__A : Dict = abspath(join(dirname(dirname(__file__)), '''src'''))
... | 370 |
"""simple docstring"""
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def A_ ( snake_case_ : int ): # picklable for... | 27 | 0 |
"""simple docstring"""
from math import factorial
def A_ ( snake_case_ : int ,snake_case_ : int ):
'''simple docstring'''
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not pos... | 371 |
"""simple docstring"""
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common ... | 27 | 0 |
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 = _LazyModule(__name__, globals()['__file__'], _import_structur... | 28 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__UpperCAmelCase ... | 28 | 1 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from... | 28 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmelC... | 28 | 1 |
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_sentencepiece,
req... | 28 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 1 |
from typing import Any
import numpy as np
def __UpperCamelCase ( lowercase__ : np.ndarray ) -> bool:
'''simple docstring'''
return np.array_equal(lowercase__ , matrix.conjugate().T )
def __UpperCamelCase ( lowercase__ : np.ndarray , lowerc... | 28 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 | 1 |
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, ... | 28 |
from __future__ import annotations
from typing import Any
class __a :
def __init__( self : Dict , UpperCAmelCase : int = 6 ):
lowerCAmelCase_ : Node | None = None
lowerCAmelCase_ : Node | None = None
self.... | 28 | 1 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 28 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 28 | 1 |
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig... | 28 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 1 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__UpperCAmelCase = '\\n\n'
__UpperCAmelCase = '\nPerplexity (PPL) is one of the most common metrics for evaluating lan... | 28 |
from math import factorial, pi
def __UpperCamelCase ( lowercase__ : float , lowercase__ : int = 30 ) -> float:
'''simple docstring'''
if not isinstance(lowercase__ , (int, float) ):
raise ValueError("""maclaurin_sin() requires either an int or... | 28 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.ut... | 28 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 28 | 1 |
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncode... | 28 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig... | 28 | 1 |
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 ...ima... | 28 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 28 | 1 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'nielsr/canine-s': 20_48,
}
# Unicode defines 1,114,112 total “codepoints”
__UpperCA... | 28 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Optional[Any] , *... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : bytes ) -> str:
'''simple docstring'''
return "".join([hex(lowercase__ )[2:].zfill(2 ).upper() for byte in list(lowercase__ )] )
def __UpperCamelCase ( lowercase__ : str ) -> bytes:
'''simple docstr... | 28 |
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 __a ( __UpperCa... | 28 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 |
from math import ceil
def __UpperCamelCase ( lowercase__ : int = 1001 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : Optional[Any] = 2 ... | 28 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
__UpperCAmelCase = {
'configuration_speech_to_text': ['SPEECH_TO_TEXT_PRETRAINED_CONFI... | 28 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowe... | 28 | 1 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER,... | 28 |
def __UpperCamelCase ( lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase_ : Any = 0
for ch in input_str:
lowerCAmelCase_ : Any = ord(lowercase__ )
lowerCAmelCase_ : Dict = pow(2 , lowerc... | 28 | 1 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = [
['attention', 'attn'],
['encoder_attentio... | 28 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__UpperCAmelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__UpperCAmelCase... | 28 | 1 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface i... | 28 |
from datetime import datetime as dt
import os
from github import Github
__UpperCAmelCase = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def __UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : int ) -> int:
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = abs(lowercase__ )
lowerCAmelCase_ : int = 0
while n > 0:
res += n % 10
n //= 10
return res
def __UpperCame... | 28 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 28 | 1 |
import argparse
import json
import subprocess
def __UpperCamelCase ( lowercase__ : int , lowercase__ : List[str] ) -> Any:
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = []
lowerCAmelCase_ : List[str] = (
f'curl -H ... | 28 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 28 | 1 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
__UpperCAmelCase = TypeVar('T')
class __a ( Generic[T] ):
__snake_case : deque[T] # Cache store of keys
__snake_case : set[T] # References of the keys in ... | 28 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class __a ( __Upper... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : int , lowercase__ : int ) -> str:
'''simple docstring'''
return "\n".join(
f'{number} * {i} = {number * i}' for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplicatio... | 28 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for non-integers""" )
eli... | 28 | 1 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a n... | 28 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__UpperCAmelCase ... | 28 | 1 |
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 __UpperCamelCase ( lowercase__ : Any , lowercase__ : Optional[Any] , lowerc... | 28 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmelC... | 28 | 1 |
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : str ) -> list[int]:
'''simple docstring'''
return [ord(lowercase__ ) - 96 for elem in plain]
def __UpperCamelCase ( lowercase__ : list[int] ) -> str:
'''simple docstring'''
... | 28 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : float , lowercase__ : float ) -> float:
'''simple docstring'''
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 * mass * abs(lowercase__ ) * abs(lowercase__ )
if ... | 28 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 | 1 |
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, ... | 28 |
from __future__ import annotations
from typing import Any
class __a :
def __init__( self : Dict , UpperCAmelCase : int = 6 ):
lowerCAmelCase_ : Node | None = None
lowerCAmelCase_ : Node | None = None
self.... | 28 | 1 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 28 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 28 | 1 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
import... | 28 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 1 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_available()... | 28 |
from math import factorial, pi
def __UpperCamelCase ( lowercase__ : float , lowercase__ : int = 30 ) -> float:
'''simple docstring'''
if not isinstance(lowercase__ , (int, float) ):
raise ValueError("""maclaurin_sin() requires either an int or... | 28 | 1 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __a ( __UpperCamelCase ):
def A ( self : str , UpperCAmelCase : str=None , UpperCAmelCase : Union[str, Any]=None , UpperCAmelCase : str=None , **UpperCAmelCase : ... | 28 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 28 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
__UpperCAmelCase = {
'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
'albert-large-v1': 'https://huggingface.co/a... | 28 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig... | 28 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
'https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json... | 28 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 28 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvailable()
except Opt... | 28 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Optional[Any] , *... | 28 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'distilbert-base-uncased': 'https://huggingfac... | 28 |
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 __a ( __UpperCa... | 28 | 1 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
)
def __... | 28 |
from math import ceil
def __UpperCamelCase ( lowercase__ : int = 1001 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : Optional[Any] = 2 ... | 28 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__UpperCAmelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__UpperCAmelCase... | 28 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowe... | 28 | 1 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def __UpperCamelCase ( lowercase__ : Any , lowercase__ : bool = True , lowercase__ : float = math.inf , lowercase__ : float = -math.inf , lowercase__ : ... | 28 |
def __UpperCamelCase ( lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase_ : Any = 0
for ch in input_str:
lowerCAmelCase_ : Any = ord(lowercase__ )
lowerCAmelCase_ : Dict = pow(2 , lowerc... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : int ) -> bool:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
lowerCAmelCase_ : Dict = f'Input value of [number={number}] must be an integer'
raise TypeError(lowercase__ ... | 28 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__UpperCAmelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__UpperCAmelCase... | 28 | 1 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
blenderbot,
blend... | 28 |
from datetime import datetime as dt
import os
from github import Github
__UpperCAmelCase = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def __UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
... | 28 | 1 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = '▁'
__UpperCAmelCase ... | 28 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 28 | 1 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import ... | 28 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 28 | 1 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( lowercase__ : Optional[Any] ) -> int:
'''simple d... | 28 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class __a ( __Upper... | 28 | 1 |
__UpperCAmelCase = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .... | 28 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for non-integers""" )
eli... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : int , lowercase__ : int ) -> str:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
lowerCAmelCase_ : str = str(bin(lowercase__ ) ... | 28 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__UpperCAmelCase ... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : int = 50 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : Union[str, Any] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):... | 28 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmelC... | 28 | 1 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def __UpperCamelCase ( lowercase__ : Tuple , lowercase__ : int=None ) -> List[Any]:
'''simple docstring'''
lowerCAmelCase_ ... | 28 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 1 |
def __UpperCamelCase ( ) -> Tuple:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 0
for i in range(1 , 1001 ):
total += i**i
return str(lowercase__ )[-10:]
if __name__ == "__main__":
print(solution())
| 28 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 | 1 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
__UpperCAmelCase = (
'4S 3H 2C 7S 5H',
'9D 8H 2C 6S 7H',
'2D 6D 9D TH 7D',
'TC 8C 2S JH 6C',
'JH 8S TH AH QH',
'TS KS 5S 9S AC',
'KD 6S 9D TH AD',
'KS 8D... | 28 |
from __future__ import annotations
from typing import Any
class __a :
def __init__( self : Dict , UpperCAmelCase : int = 6 ):
lowerCAmelCase_ : Node | None = None
lowerCAmelCase_ : Node | None = None
self.... | 28 | 1 |
import numpy as np
def __UpperCamelCase ( lowercase__ : np.array ) -> np.array:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def __UpperCamelCase ( lowercase__ : np.array ) -> np.array:
'''simple docstring'''
return vector * sigm... | 28 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 28 | 1 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for non-integers""" )
eli... | 28 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class __a ( __Upper... | 28 |
from math import factorial, pi
def __UpperCamelCase ( lowercase__ : float , lowercase__ : int = 30 ) -> float:
'''simple docstring'''
if not isinstance(lowercase__ , (int, float) ):
raise ValueError("""maclaurin_sin() requires either an int or... | 28 | 1 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
r... | 28 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 28 | 1 |
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : list[int] ) -> int:
'''simple docstring'''
if not nums:
return 0
lowerCAmelCase_ : Optional[Any] = nums[0]
lowerCAmelCase_ : List[Any] = 0
for num in nums[1:]:
... | 28 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig... | 28 | 1 |
from timeit import timeit
def __UpperCamelCase ( lowercase__ : int ) -> int:
'''simple docstring'''
if number < 0:
raise ValueError("""the value of input must not be negative""" )
lowerCAmelCase_ : Any = 0
while number:
number &= number ... | 28 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 28 | 1 |
from torch import nn
def __UpperCamelCase ( lowercase__ : Dict ) -> List[str]:
'''simple docstring'''
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
... | 28 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Optional[Any] , *... | 28 | 1 |
from timeit import timeit
__UpperCAmelCase = {
'MALAYALAM': True,
'String': False,
'rotor': True,
'level': True,
'A': True,
'BB': True,
'ABC': False,
'amanaplanacanalpanama': True, # "a man a plan a canal panama"
}
# Ensure our test data is valid
assert all((key == key[::... | 28 |
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 __a ( __UpperCa... | 28 | 1 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
W... | 28 |
from math import ceil
def __UpperCamelCase ( lowercase__ : int = 1001 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : Optional[Any] = 2 ... | 28 | 1 |
from PIL import Image
def __UpperCamelCase ( lowercase__ : Image , lowercase__ : float ) -> Image:
'''simple docstring'''
def brightness(lowercase__ : int ) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.0:
raise... | 28 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowe... | 28 | 1 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def __UpperCamelCase ( lowercase__ : dict ) -> tuple:
'''simpl... | 28 |
def __UpperCamelCase ( lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase_ : Any = 0
for ch in input_str:
lowerCAmelCase_ : Any = ord(lowercase__ )
lowerCAmelCase_ : Dict = pow(2 , lowerc... | 28 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmel... | 28 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__UpperCAmelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__UpperCAmelCase... | 28 | 1 |
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class __a ( __UpperCamelCase ,unittest.Te... | 28 |
from datetime import datetime as dt
import os
from github import Github
__UpperCAmelCase = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def __UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
... | 28 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_utils import FeatureExtra... | 28 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : int = 1000000 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : Any = 1
lowerCAmelCase_ : str = 1
lowerCAmelCase_ : List[Any] = {1: 1}
for inputa in range(2 , lowercase__ )... | 28 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 28 | 1 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowercase__ : Tuple=7 ) -> Optional[Any]:
'''simple docstring'''
lowerCAmelCase_ : int ... | 28 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class __a ( __Upper... | 28 | 1 |
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmbeddings,
BertLa... | 28 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for non-integers""" )
eli... | 28 | 1 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class __a ( nn.Module ):
... | 28 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__UpperCAmelCase ... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : Tuple ) -> Optional[int]:
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = 1
lowerCAmelCase_ : List[Any] = 2
while i * i <= n:
lowerCAmelCase_ : str = 0
while n % i == 0... | 28 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmelC... | 28 | 1 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def __UpperCamelCase ( ) -> Union[str, Any]:
'''simple docstring'''
lowerCAmelCase_ : Dict = HfArgumentParser(lowercase__ )
lowerCAmelCase_ : List[str] = parse... | 28 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 1 |
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 __a ( __UpperCamelCase ,unittest.TestCase ):
__... | 28 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
class __a ... | 28 |
from __future__ import annotations
from typing import Any
class __a :
def __init__( self : Dict , UpperCAmelCase : int = 6 ):
lowerCAmelCase_ : Node | None = None
lowerCAmelCase_ : Node | None = None
self.... | 28 | 1 |
import math
import qiskit
def __UpperCamelCase ( lowercase__ : int = 1 , lowercase__ : int = 1 , lowercase__ : int = 1 ) -> qiskit.result.counts.Counts:
'''simple docstring'''
if (
isinstance(lowercase__ , lowercase__ )
... | 28 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 28 | 1 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
__UpperCAmelCase = 5_00_00
__UpperCAmelCase = 50_00
__UpperCAmelCase , __UpperCAmelCase = os.path.split(__file__)
__UpperCAmelCase = os.path.join(RESULTS_BASEPA... | 28 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 1 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
def __UpperCamelCase ( lowercase__ : Optional[Any]=None , lowercase_... | 28 |
from math import factorial, pi
def __UpperCamelCase ( lowercase__ : float , lowercase__ : int = 30 ) -> float:
'''simple docstring'''
if not isinstance(lowercase__ , (int, float) ):
raise ValueError("""maclaurin_sin() requires either an int or... | 28 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {'configuration_ibert': ['IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'IBertConfig', 'IBertOnnxConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNo... | 28 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 28 | 1 |
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
from ... | 28 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig... | 28 | 1 |
__UpperCAmelCase = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager
| 28 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 28 | 1 |
def __UpperCamelCase ( lowercase__ : list[list[float]] ) -> list[list[float]]:
'''simple docstring'''
lowerCAmelCase_ : list[list[float]] = []
for data in source_data:
for i, el in enumerate(lowercase__ ):
if len(lowercase__ ) < i +... | 28 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Optional[Any] , *... | 28 | 1 |
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,
RobertaTokenizerFast,
XLMRo... | 28 |
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 __a ( __UpperCa... | 28 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 28 |
from math import ceil
def __UpperCamelCase ( lowercase__ : int = 1001 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : Optional[Any] = 2 ... | 28 | 1 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compressio... | 28 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowe... | 28 | 1 |
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