code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
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
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
... | 679 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
__magic_name__ = logging.get_logger(__name__)
# TODO: upload to AWS
__magic_name__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retribert-base-uncased/... | 679 | 1 |
import os
def UpperCAmelCase__( ):
__snake_case : Optional[Any] = os.path.dirname(os.path.realpath(__UpperCAmelCase ) )
__snake_case : Tuple = os.path.join(__UpperCAmelCase , 'triangle.txt' )
with open(__UpperCAmelCase ) as f:
__snake_case... | 679 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | 1 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
__magic_name__ = logging.get_logger(__name__)
def UpperCAmelCase__( __UpperCAmelCase : Any ):
__snake_case : int ... | 679 | import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | 1 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
__magic_name__ = TypeVar('''U''')
class __SCREAMING_SNAKE_CASE ( Generic[T, U]):
"""simple docstring"""
def... | 679 | def UpperCAmelCase__( __UpperCAmelCase : int | float | str ):
try:
__snake_case : int = float(__UpperCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
__snake_case : Any = decimal - int(__UpperCAmelCase )
if fract... | 679 | 1 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def UpperCAmelCase__( ):
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print('Key files generation successful.'... | 679 | 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,
AutoModelForMultipleChoice,
... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : list[int] ):
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__snake_case : Union[str, Any] = sum(__UpperCAmelCase ) / len(__UpperCAmelCase ) # Calculate the average
return sum(abs... | 679 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 1 |
from __future__ import annotations
from collections.abc import Callable
__magic_name__ = list[list[float | int]]
def UpperCAmelCase__( __UpperCAmelCase : Matrix , __UpperCAmelCase : Matrix ):
__snake_case : int = len(__UpperCAmelCase )
__snake... | 679 | def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | 1 |
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
__magic_name__ = 500_000
__magic_name__ , __magic_name__ = os.path.split(__file__)
__magic_name__ = os.path.join(RESULTS... | 679 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin... | 679 | 1 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
__magic_name__ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf(), gbellmf(),... | 679 | 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 __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | 1 |
import math
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
# Copied from diffusers.schedul... | 679 | from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | 1 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTeste... | 679 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 1 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is_tor... | 679 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 1 |
__magic_name__ = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__magic_name__ = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__magic_name__ = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''Thursday''',
5: '''Friday''',
6: ... | 679 | import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | 1 |
from random import randint, random
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : bool = False , __UpperCAmelCase : bool = False , __UpperCAmelCase : int = 5 , ):
... | 679 | from itertools import permutations
def UpperCAmelCase__( __UpperCAmelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__snake_case : Any = [7, 11, 13, 17]
for i, t... | 679 | 1 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
__UpperCAmelCase = (EulerDiscreteScheduler,)
__Upper... | 679 | # Function to print upper half of diamond (pyramid)
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
for i in range(0 , __UpperCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 679 | 1 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | from timeit import timeit
def UpperCAmelCase__( __UpperCAmelCase : int ):
if number < 0:
raise ValueError('the value of input must not be negative' )
__snake_case : Dict = 0
while number:
number &= number - 1
result += 1
return result
def ... | 679 | 1 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
__UpperCAmelCase = (CMStochasticIterativeScheduler,)
__UpperCAmelCase = 1_0
... | 679 | import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if not is_torch_av... | 679 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
... | 679 | 1 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
def UpperCAmelCase__( __UpperCAmelCase : Any , __UpperCAmelCase : Union[str, Any] ):... | 679 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | 1 |
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 1 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, id... | 679 | 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,
BertEncoder,
... | 679 | 1 |
import qiskit
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int ):
__snake_case : str = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit acting on the q register
__snake_case : Tuple = qiskit.QuantumCircuit(_... | 679 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 679 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
__magic_name__ = logging.get_logger(__name__)
# TODO: upload to AWS
__magic_name__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retribert-base-uncased/... | 679 | 1 |
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokeniza... | 679 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | 1 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {name: getattr(transformers, name + '''Fast''') for ... | 679 | import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | 1 |
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
__UpperCAmelCase = None
__UpperCAmelCase = None
__magic_nam... | 679 | def UpperCAmelCase__( __UpperCAmelCase : int | float | str ):
try:
__snake_case : int = float(__UpperCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
__snake_case : Any = decimal - int(__UpperCAmelCase )
if fract... | 679 | 1 |
from sklearn.metrics import mean_squared_error
import datasets
__magic_name__ = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel, M. and Prett... | 679 | 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,
AutoModelForMultipleChoice,
... | 679 | 1 |
from PIL import Image
def UpperCAmelCase__( __UpperCAmelCase : Image , __UpperCAmelCase : float ):
def brightness(__UpperCAmelCase : int ) -> float:
return 1_28 + level + (c - 1_28)
if not -255.0 <= level <= 255.0:
raise ValueError('level must be between -25... | 679 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 1 |
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class __SCREAMING_SNAKE_CASE ( tf.keras.optimizers.schedules.LearningRateSchedule):
... | 679 | def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | 1 |
from __future__ import annotations
import os
from typing import Any
import requests
__magic_name__ = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
__magic_name__ = BASE_URL + '''/user'''
# https://g... | 679 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin... | 679 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__magic_name__ = {
'''configuration_poolformer''': [
'''POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''PoolFormerConfig''',
'''Pool... | 679 | 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 __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | 1 |
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def UpperCAmelCase__( __UpperCAmelCase : Union[str... | 679 | from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | 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 ...te... | 679 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 1 |
import argparse
from collections import defaultdict
def UpperCAmelCase__( __UpperCAmelCase : Optional[int] , __UpperCAmelCase : Dict , __UpperCAmelCase : List[Any] , __UpperCAmelCase : Tuple , __UpperCAmelCase : Optional[int] ):
__snake_case ... | 679 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 1 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def UpperCAmelCase__( __UpperCAmelCase : Tuple ):
__snake_case : Tuple = os.path.join(args.tf_model_dir , 'parameters.json' )
__snake_c... | 679 | import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | 1 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__magic_name__ = False
class __SCREAMING_SNAKE_CASE ( unittest.TestC... | 679 | from itertools import permutations
def UpperCAmelCase__( __UpperCAmelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__snake_case : Any = [7, 11, 13, 17]
for i, t... | 679 | 1 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | 679 | # Function to print upper half of diamond (pyramid)
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
for i in range(0 , __UpperCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 679 | 1 |
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
from transformers.testing_... | 679 | from timeit import timeit
def UpperCAmelCase__( __UpperCAmelCase : int ):
if number < 0:
raise ValueError('the value of input must not be negative' )
__snake_case : Dict = 0
while number:
number &= number - 1
result += 1
return result
def ... | 679 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''go... | 679 | import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int ):
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
__snake_case : List[Any] = str(bin(__UpperCAmelCase ) )[2:] # remove the leading "0b"
__snake_c... | 679 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
... | 679 | 1 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModelForSequenceClas... | 679 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | 1 |
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
__magic_name__ = yaml.safe_load(
'''\
name: ""
allow_empty: false
allow_empty_text: true
subsections:
- name: "Dataset Card... | 679 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
__magic_name__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class __SCREAMING_SNAKE_CASE ( Upper... | 679 | 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,
BertEncoder,
... | 679 | 1 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def UpperCAmelCase__( __UpperCAmelCase : int ):
if not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise TypeError('Undefined for non-integers' )
elif precision < 1:
raise ValueError... | 679 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 1 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
smartaa_timesteps,
smart... | 679 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
__magic_name__ = logging.get_logger(__name__)
# TODO: upload to AWS
__magic_name__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retribert-base-uncased/... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : int ):
if exponent == 1:
return base
if exponent % 2 == 0:
__snake_case : Optional[Any] = _modexpt(__UpperCAmelCase , exponent // 2 , __Upp... | 679 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | 1 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
__magic_nam... | 679 | import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | 1 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import Toke... | 679 | def UpperCAmelCase__( __UpperCAmelCase : int | float | str ):
try:
__snake_case : int = float(__UpperCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
__snake_case : Any = decimal - int(__UpperCAmelCase )
if fract... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : int = 10_00 ):
__snake_case : Union[str, Any] = -1
__snake_case : Optional[Any] = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__snake_case : Di... | 679 | 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,
AutoModelForMultipleChoice,
... | 679 | 1 |
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
'''tokenization_roc_bert''': [... | 679 | def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/... | 679 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin... | 679 | 1 |
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin im... | 679 | 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 __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : list[int] ):
# 1. Validate that path exists between current and next vertices
if graph[path[curr_ind - 1]][next_ver] == 0:
ret... | 679 | from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | 1 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def UpperCAmelCase__( __UpperCAmelCase : Dict , __UpperCAmelCase : Optional[int]=None ):
__snake_case : Tuple = None
if toke... | 679 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 1 |
__magic_name__ = [
'''DownloadConfig''',
'''DownloadManager''',
'''DownloadMode''',
'''StreamingDownloadManager''',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManage... | 679 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 1 |
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils i... | 679 | import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : str , __UpperCAmelCase : Optional[int] ):
__snake_case : Any = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def UpperCAmelCase__( __UpperCAmelCase : Optional[int] ... | 679 | from itertools import permutations
def UpperCAmelCase__( __UpperCAmelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__snake_case : Any = [7, 11, 13, 17]
for i, t... | 679 | 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 by appl... | 679 | # Function to print upper half of diamond (pyramid)
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
for i in range(0 , __UpperCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 679 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | from timeit import timeit
def UpperCAmelCase__( __UpperCAmelCase : int ):
if number < 0:
raise ValueError('the value of input must not be negative' )
__snake_case : Dict = 0
while number:
number &= number - 1
result += 1
return result
def ... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : str , __UpperCAmelCase : str = " " ):
__snake_case : Tuple = []
__snake_case : Optional[int] = 0
for index, char in enumerate(__UpperCAmelCase ):
if char == separator:
split_words.append(string[las... | 679 | import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | 1 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
__magic_name__ = get_tests_dir('''fixtures/test_sentencepiece... | 679 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
... | 679 | 1 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from tran... | 679 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_ava... | 679 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 1 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 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,
BertEncoder,
... | 679 | 1 |
import os
def UpperCAmelCase__( ):
with open(os.path.dirname(__UpperCAmelCase ) + '/grid.txt' ) as f:
__snake_case : str = [] # noqa: E741
for _ in range(20 ):
l.append([int(__UpperCAmelCase ) for x in f.readline().split()] )
__snake_case ... | 679 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 1 |
import math
import tensorflow as tf
from packaging import version
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
__snake_case : str = tf.convert_to_tensor(__UpperCAmelCase )
__snake_case : Optional[int] = 0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0 ... | 679 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
__magic_name__ = logging.get_logger(__name__)
# TODO: upload to AWS
__magic_name__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retribert-base-uncased/... | 679 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : Tuple ):
for i in range(len(SCREAMING_SNAKE_CASE_ ) - 1 , 0 , -1 ):
__snake_case : Optional[Any] = False
for j in range(SCREAMING_SNAKE_CASE_ , 0 , -1 ):
if unsorted[j] < unsort... | 700 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | 0 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_safe imp... | 701 | import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | 0 |
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
__magic_name__ = get_logger(__name__)
__magic_name__ = R'\n Args:\n input_ids (`jnp.ndarray` of shape `(batch_size, sequen... | 702 | def UpperCAmelCase__( __UpperCAmelCase : int | float | str ):
try:
__snake_case : int = float(__UpperCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
__snake_case : Any = decimal - int(__UpperCAmelCase )
if fract... | 679 | 0 |
from __future__ import annotations
import bisect
def UpperCAmelCase__( __UpperCAmelCase : List[str] , __UpperCAmelCase : Optional[Any] , __UpperCAmelCase : str = 0 , __UpperCAmelCase : List[Any] = -1 ):
if hi < 0:
__snake_case : Tuple ... | 703 | 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,
AutoModelForMultipleChoice,
... | 679 | 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
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''mi... | 704 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 0 |
'''simple docstring'''
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def UpperCAmelCase__( __UpperCAmelCase : str ):
return x + 2
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
... | 705 | def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | 0 |
import operator
def UpperCAmelCase__( __UpperCAmelCase : Optional[int] , __UpperCAmelCase : List[str] = False , __UpperCAmelCase : Union[str, Any] = None ):
__snake_case : Union[str, Any] = operator.lt if reverse else operator.gt
__snake_case : List[... | 706 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin... | 679 | 0 |
import math
from datetime import datetime, timedelta
def UpperCAmelCase__( __UpperCAmelCase : int ):
__snake_case : str = year % 19
__snake_case : Optional[int] = year % 4
__snake_case : int = year % 7
__snake_case : int = math.floor(yea... | 707 | 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 __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | 0 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
__magic_name__ = object()
# For specifying empty leaf dict `{}`
__magic_name__ = object()
def Up... | 708 | from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | 0 |
'''simple docstring'''
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self... | 709 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 0 |
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
__snake_case : Optional[Any] = F"""Input value of [number={number}] must be an integer"""
raise TypeError(lowerCamelCase__ )
if number < 1:
... | 710 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 0 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutputWithP... | 711 | import math
import os
import sys
def UpperCAmelCase__( __UpperCAmelCase : str ):
__snake_case : Union[str, Any] = ''
try:
with open(__UpperCAmelCase , 'rb' ) as binary_file:
__snake_case : Optional[Any] = binary_file.read()
for dat i... | 679 | 0 |
def UpperCAmelCase__( __UpperCAmelCase : Union[str, Any] , __UpperCAmelCase : List[str] , __UpperCAmelCase : int , __UpperCAmelCase : Optional[int] , __UpperCAmelCase : Any , __UpperCAmelCase : str ):
if index == r:
for j in ra... | 712 | from itertools import permutations
def UpperCAmelCase__( __UpperCAmelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__snake_case : Any = [7, 11, 13, 17]
for i, t... | 679 | 0 |
'''simple docstring'''
import math
def UpperCAmelCase__( __UpperCAmelCase : Union[str, Any] ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are... | 713 | # Function to print upper half of diamond (pyramid)
def UpperCAmelCase__( __UpperCAmelCase : List[str] ):
for i in range(0 , __UpperCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 679 | 0 |
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, get_t... | 714 | from timeit import timeit
def UpperCAmelCase__( __UpperCAmelCase : int ):
if number < 0:
raise ValueError('the value of input must not be negative' )
__snake_case : Dict = 0
while number:
number &= number - 1
result += 1
return result
def ... | 679 | 0 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
__magic_name__ = False
class __SCREAMING_SNAKE_CASE ( uni... | 715 | import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
imp... | 679 | 0 |
from __future__ import annotations
import math
def UpperCAmelCase__( __UpperCAmelCase : Any ):
if num <= 0:
__snake_case : int = F"""{num}: Invalid input, please enter a positive integer."""
raise ValueError(_lowerCamelCase )
__snake_case : Optional[Any... | 716 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T]):
"""simple docstring"""
def __init__( self , _UpperCAmelCase ):
... | 679 | 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
from transformers.models... | 717 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slow
f... | 679 | 0 |
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
__magic_name__ = logging.get_logger(__name__)
@add_... | 718 | import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : Any ):
... | 679 | 0 |
'''simple docstring'''
def UpperCAmelCase__( ):
__snake_case : Optional[int] = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
__snake_case : Optional[int] = 6
__snake_case : Tuple = 1
__snake_case : List[Any] = 19_01
__snake_case : L... | 719 | 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,
BertEncoder,
... | 679 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__magic_name__ = {
"""configuration_swiftformer""": [
"""SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""SwiftFormerConfig""",
"""S... | 720 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 0 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE__):
"""simple docstring"""
__UpperCAmelCase = (KDPMaDiscreteScheduler,)
... | 721 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
__magic_name__ = logging.get_logger(__name__)
# TODO: upload to AWS
__magic_name__ = {
'''yjernite/retribert-base-uncased''': (
'''https://huggingface.co/yjernite/retribert-base-uncased/... | 679 | 0 |
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 FlaxGenerationTesterMixin
from... | 700 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioG... | 679 | 0 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
"""simple docstring"""
_... | 701 | import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 679 | 0 |
import random
def UpperCAmelCase__( __UpperCAmelCase : list , __UpperCAmelCase : List[Any] ):
__snake_case , __snake_case , __snake_case : Optional[int] = [], [], []
for element in data:
if element < pivot:
less.append(__UpperCAmelCase )
... | 702 | def UpperCAmelCase__( __UpperCAmelCase : int | float | str ):
try:
__snake_case : int = float(__UpperCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
__snake_case : Any = decimal - int(__UpperCAmelCase )
if fract... | 679 | 0 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MAX_SHARD_SIZE
from data... | 703 | 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,
AutoModelForMultipleChoice,
... | 679 | 0 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import re... | 704 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 0 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def UpperCAmelCase__( __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : int , __... | 705 | def UpperCAmelCase__( __UpperCAmelCase : list ):
__snake_case : List[Any] = len(__UpperCAmelCase )
for _ in range(__UpperCAmelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
__snake_case , __snake_... | 679 | 0 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def UpperCAmelCase__( *__UpperCAmelCase : List[Any] , __UpperCAmelCase : Optional[Union[Dict, Any]] = None , __UpperCAmelCase : str=True , __UpperCAmelCase : ... | 706 | import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin... | 679 | 0 |
import math
def UpperCAmelCase__( __UpperCAmelCase : Any ):
assert isinstance(__snake_case , __snake_case ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or not number ... | 707 | 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 __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__UpperCAmelCase = 42
... | 679 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
__magic_name__ = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}
try:
if not is_torch... | 708 | from __future__ import annotations
__magic_name__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__( __UpperCAmelCase : list[list[int]] , __UpperCAmelCase : list[int] , __UpperCAmelCase : list[int] ... | 679 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''rober... | 709 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
__magic_name__ ... | 679 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __SCREAMING_SNAKE_CASE ( UpperCAmelCase__):
... | 710 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__magic_name__ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , **_Upp... | 679 | 0 |
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