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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case : Dict = {
'''configuration_xlm_roberta''': [
... | 657 |
def __lowercase ( __lowerCAmelCase : int ):
if length <= 0 or not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowerCAmelCase )]
if _... | 657 | 1 |
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
snake_case : int = parse(importlib.metadata.version('''torch'''))
def __lowercase ( __lowerCAmelCase : Union[str, Version] ... | 657 |
def __lowercase ( __lowerCAmelCase : list , __lowerCAmelCase : list , __lowerCAmelCase : int ):
if len(__lowerCAmelCase ) != len(__lowerCAmelCase ):
raise ValueError('The length of profit and weight must be same.' ... | 657 | 1 |
from sklearn.metrics import fa_score
import datasets
snake_case : Optional[int] = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case : List[Any] = '''
Args:
pre... | 657 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : Optional[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if ... | 657 | 1 |
def __lowercase ( __lowerCAmelCase : int = 1_0 , __lowerCAmelCase : int = 1_0_0_0 , __lowerCAmelCase : bool = True ):
assert (
isinstance(__lowerCAmelCase , __lowerCAmelCase )
and isinstance(__lowerCAmel... | 657 |
import gc
import unittest
from transformers import CTRLConfig, 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 ModelTester... | 657 | 1 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import Token... | 657 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class snake_case_ (lowerCamelCase_ , lowerCamelCase_ ):
UpperCAmelCase__ ... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
snake_case : int = {
'''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
'''tokenization_roc_bert''': [... | 657 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case : Any = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConf... | 657 | 1 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClassification,
Auto... | 657 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
snake_case : Dict = logging.get_logger(__name__)
snake_case : Any = {name: getattr(transformers, name + '''Fast''') for na... | 657 | 1 |
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
snake_case : int = logging.getLogger(__name__)
@dataclass
c... | 657 |
from math import ceil, sqrt
def __lowercase ( __lowerCAmelCase : int = 1_0_0_0_0_0_0 ):
a__ = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
a__ = max(ceil(sqrt(outer_width**2 - l... | 657 | 1 |
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
snake_case : Dict = logging.getLogger()
def __lowercase ( __lowerC... | 657 |
from sklearn.metrics import fa_score
import datasets
snake_case : Optional[int] = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case : List[Any] = '''
Args:
pre... | 657 | 1 |
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
snake_case : Any = get_tests_dir('''fixture... | 657 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 657 | 1 |
import operator as op
def __lowercase ( __lowerCAmelCase : int ):
a__ = []
a__ = lambda __lowerCAmelCase , __lowerCAmelCase : int(x / y ) # noqa: E731 integer division operation
a__ = {
'^': op.pow,
'*': op.m... | 657 |
# 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 a... | 657 | 1 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def __lowercase ( __lowerCAmelCase : ... | 657 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowercase ( __lowerCAmelCase : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('Undefined for non-integers' )
elif precision... | 657 | 1 |
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__lowerCAmelCase , int(b / 2 ) ) * actual_power(__lowerCAmelCase , int(b... | 657 |
def __lowercase ( __lowerCAmelCase : int = 2_0_0 ):
a__ = [1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
a__ = [0] * (pence + 1)
a__ = 1 # base case: 1 way to make 0 pence
for coin in coins:
for i in range(__lowerCAmelCase , pence... | 657 | 1 |
from math import factorial
snake_case : List[Any] = {str(d): factorial(d) for d in range(10)}
def __lowercase ( __lowerCAmelCase : int ):
return sum(DIGIT_FACTORIAL[d] for d in str(__lowerCAmelCase ) )
def __lowercase ( ):
a_... | 657 |
from manim import *
class snake_case_ (lowerCamelCase_ ):
def lowerCamelCase__( self :Optional[Any] ) -> Optional[int]:
a__ = Rectangle(height=0.5 ,width=0.5 )
a__ = Rectangle(height=0.46 ,width=0.46 ).set_stroke(width=0 )
... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case : List[str] = {
'''configuration_electra''': ['''ELECTRA_PRETRAINED_CONFIG_ARC... | 657 |
from math import pi
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 657 | 1 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
snake_case : Dict = logging.get_logger(__name__)
snake_case : Any = {name: getattr(transformers, name + '''Fast''') for na... | 657 |
from math import sqrt
def __lowercase ( __lowerCAmelCase : int ):
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 ... | 657 | 1 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 657 |
import unittest
from knapsack import greedy_knapsack as kp
class snake_case_ (unittest.TestCase ):
def lowerCamelCase__( self :Optional[Any] ) -> Union[str, Any]:
a__ = [10, 20, 30, 40, 50, 60]
a__ = [2, 4, 6, 8, 10, 12]
a__ = 1... | 657 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
snake_case : Any = logging.get_logger(__name__)
snake_case : int = '''▁''... | 657 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,... | 657 | 1 |
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class snake_case_ (lowerC... | 657 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : list[int] ): # This function is recursive
a__ = len(__lowerCAmelCase )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if ar... | 657 | 1 |
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils import is_torch_available
... | 657 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,
get_image_s... | 657 | 1 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def __lowercase ( ):
a__ = HfArgumentParser(__lowerCAmelCase )
a__ = parser.parse_args_into_dataclasses()[0]
a__ = TensorFlowBenchmark(args=__lowerCAmelCase )
... | 657 |
def __lowercase ( __lowerCAmelCase : int ):
a__ = generate_pascal_triangle(__lowerCAmelCase )
for row_idx in range(__lowerCAmelCase ):
# Print left spaces
for _ in range(num_rows - row_idx - 1 ):
print(end=' ... | 657 | 1 |
def __lowercase ( __lowerCAmelCase : Tuple ): # noqa: E741
a__ = len(__lowerCAmelCase )
a__ = 0
a__ = [0] * n
a__ = [False] * n
a__ = [False] * n
def dfs(__lowerCAmelCase : Optional[int] , __lowerCA... | 657 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
snake_case : str = (
'''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''',
''... | 657 | 1 |
from __future__ import annotations
from collections.abc import Callable
snake_case : Optional[Any] = list[list[float | int]]
def __lowercase ( __lowerCAmelCase : Matrix , __lowerCAmelCase : Matrix ):
a__ = len(__lowerCAmelCase )
... | 657 |
def __lowercase ( __lowerCAmelCase : int ):
if length <= 0 or not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowerCAmelCase )]
if _... | 657 | 1 |
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : Dict , __lowerCAmelCase : Optional[Any] ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(__lowerCAmelCase , n ... | 657 |
def __lowercase ( __lowerCAmelCase : list , __lowerCAmelCase : list , __lowerCAmelCase : int ):
if len(__lowerCAmelCase ) != len(__lowerCAmelCase ):
raise ValueError('The length of profit and weight must be same.' ... | 657 | 1 |
class snake_case_ :
def __init__( self :Union[str, Any] ) -> Union[str, Any]:
a__ = {}
def lowerCamelCase__( self :List[str] ) -> None:
print(self.vertex )
for i in self.vertex:
print(__snake_case ,' ... | 657 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : Optional[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if ... | 657 | 1 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class snake_case_ (lowerCamelCase_ ):
@staticmethod
@abstractmethod
def lowerCamelCase__( __snake_case :ArgumentParser ) -> str:
raise NotImplementedError()
@abstractmethod
... | 657 |
import gc
import unittest
from transformers import CTRLConfig, 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 ModelTester... | 657 | 1 |
from functools import lru_cache
def __lowercase ( __lowerCAmelCase : int ):
a__ = 2
a__ = set()
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.add(__lo... | 657 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class snake_case_ (lowerCamelCase_ , lowerCamelCase_ ):
UpperCAmelCase__ ... | 657 | 1 |
from math import factorial
def __lowercase ( __lowerCAmelCase : int = 1_0_0 ):
return sum(int(__lowerCAmelCase ) for x in str(factorial(__lowerCAmelCase ) ) )
if __name__ == "__main__":
print(solution(int(input('''Enter the Number: ''').strip())))
... | 657 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case : Any = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConf... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case : Any = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConf... | 657 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
snake_case : Dict = logging.get_logger(__name__)
snake_case : Any = {name: getattr(transformers, name + '''Fast''') for na... | 657 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
snake_ca... | 657 |
from math import ceil, sqrt
def __lowercase ( __lowerCAmelCase : int = 1_0_0_0_0_0_0 ):
a__ = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
a__ = max(ceil(sqrt(outer_width**2 - l... | 657 | 1 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
snake_case : Any = Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io # noqa
... | 657 |
from sklearn.metrics import fa_score
import datasets
snake_case : Optional[int] = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case : List[Any] = '''
Args:
pre... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
snake_case : Dict = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['''XL... | 657 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 657 | 1 |
import gc
import unittest
from transformers import CTRLConfig, 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 ModelTester... | 657 |
# 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 a... | 657 | 1 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : list[float] ):
a__ = 0.00
a__ = 0
for resistor in resistors:
if resistor <= 0:
a__ = F'Resistor at index {index} has a negative or zero value... | 657 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowercase ( __lowerCAmelCase : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('Undefined for non-integers' )
elif precision... | 657 | 1 |
import os
def __lowercase ( ):
with open(os.path.dirname(__lowerCAmelCase ) + '/p022_names.txt' ) as file:
a__ = str(file.readlines()[0] )
a__ = names.replace('"' , '' ).split(',' )
names.sort()
a__ = 0
... | 657 |
def __lowercase ( __lowerCAmelCase : int = 2_0_0 ):
a__ = [1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
a__ = [0] * (pence + 1)
a__ = 1 # base case: 1 way to make 0 pence
for coin in coins:
for i in range(__lowerCAmelCase , pence... | 657 | 1 |
from ...configuration_utils import PretrainedConfig
snake_case : Tuple = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-finetuned-wtq''': (
'''https://huggingface.co/go... | 657 |
from manim import *
class snake_case_ (lowerCamelCase_ ):
def lowerCamelCase__( self :Optional[Any] ) -> Optional[int]:
a__ = Rectangle(height=0.5 ,width=0.5 )
a__ = Rectangle(height=0.46 ,width=0.46 ).set_stroke(width=0 )
... | 657 | 1 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
snake_case : str = (
'''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''',
''... | 657 |
from math import pi
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 657 | 1 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class snake_case_ (lowerCamelCase_ ):
UpperCAmelCase__ : str = '''Speech2TextFeatureExtractor'''
UpperCAmelCase__ : Union[str, Any] = '''Speech2TextToken... | 657 |
from math import sqrt
def __lowercase ( __lowerCAmelCase : int ):
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 ... | 657 | 1 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tran... | 657 |
import unittest
from knapsack import greedy_knapsack as kp
class snake_case_ (unittest.TestCase ):
def lowerCamelCase__( self :Optional[Any] ) -> Union[str, Any]:
a__ = [10, 20, 30, 40, 50, 60]
a__ = [2, 4, 6, 8, 10, 12]
a__ = 1... | 657 | 1 |
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers import GradientAccumulator, cr... | 657 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,... | 657 | 1 |
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processor import AttnAddedKVP... | 657 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : list[int] ): # This function is recursive
a__ = len(__lowerCAmelCase )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if ar... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : Optional[Any] = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''InstructB... | 657 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,
get_image_s... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
snake_case : Optional[int] = {
'''configuration_speech_to_text''': ['''SPEECH_TO_TEX... | 657 |
def __lowercase ( __lowerCAmelCase : int ):
a__ = generate_pascal_triangle(__lowerCAmelCase )
for row_idx in range(__lowerCAmelCase ):
# Print left spaces
for _ in range(num_rows - row_idx - 1 ):
print(end=' ... | 657 | 1 |
def __lowercase ( __lowerCAmelCase : list , __lowerCAmelCase : list , __lowerCAmelCase : int ):
if len(__lowerCAmelCase ) != len(__lowerCAmelCase ):
raise ValueError('The length of profit and weight must be same.' ... | 657 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
snake_case : str = (
'''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''',
''... | 657 | 1 |
from __future__ import annotations
from collections.abc import Generator
def __lowercase ( ):
a__ = {}
a__ = 2
while True:
a__ = factor_map.pop(__lowerCAmelCase , __lowerCAmelCase )
if factor:
a__ =... | 657 |
def __lowercase ( __lowerCAmelCase : int ):
if length <= 0 or not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowerCAmelCase )]
if _... | 657 | 1 |
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
snake_case : List[str] = {
'''facebook/maskformer-swin-base-ade''': (
... | 657 |
def __lowercase ( __lowerCAmelCase : list , __lowerCAmelCase : list , __lowerCAmelCase : int ):
if len(__lowerCAmelCase ) != len(__lowerCAmelCase ):
raise ValueError('The length of profit and weight must be same.' ... | 657 | 1 |
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_tim... | 657 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : Optional[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if ... | 657 | 1 |
from math import pi
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 657 |
import gc
import unittest
from transformers import CTRLConfig, 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 ModelTester... | 657 | 1 |
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS
loggi... | 657 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class snake_case_ (lowerCamelCase_ , lowerCamelCase_ ):
UpperCAmelCase__ ... | 657 | 1 |
from __future__ import annotations
import requests
def __lowercase ( __lowerCAmelCase : str ):
a__ = F'https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'
return requests.get(__lowerCAmelCase ).json()
def __lowercase ( ... | 657 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case : Any = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConf... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : Optional[Any] = {
'''configuration_clap''': [
'''CLAP_PRETRAINED_MODEL_ARCHIVE_LIST''',
'''ClapAudioConfig''',
'''ClapConfig''',
'''Cl... | 657 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
snake_case : Dict = logging.get_logger(__name__)
snake_case : Any = {name: getattr(transformers, name + '''Fast''') for na... | 657 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : str = logging.get_logger(__name__)
snake_case : Tuple = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json''',
'''microsoft/marku... | 657 |
from math import ceil, sqrt
def __lowercase ( __lowerCAmelCase : int = 1_0_0_0_0_0_0 ):
a__ = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
a__ = max(ceil(sqrt(outer_width**2 - l... | 657 | 1 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_co... | 657 |
from sklearn.metrics import fa_score
import datasets
snake_case : Optional[int] = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case : List[Any] = '''
Args:
pre... | 657 | 1 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepiece
@slow ... | 657 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 657 | 1 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : list[int] ): # This function is recursive
a__ = len(__lowerCAmelCase )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if ar... | 657 |
# 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 a... | 657 | 1 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case : Any = logging.get_logger(__name__)
snake_case : List[str] = {
'''vocab_file''': '''vocab.json''',... | 657 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowercase ( __lowerCAmelCase : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('Undefined for non-integers' )
elif precision... | 657 | 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 applic... | 657 |
def __lowercase ( __lowerCAmelCase : int = 2_0_0 ):
a__ = [1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
a__ = [0] * (pence + 1)
a__ = 1 # base case: 1 way to make 0 pence
for coin in coins:
for i in range(__lowerCAmelCase , pence... | 657 | 1 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def __lowercase ( __lowerCAmelCase : Any , __lowerCAmelCase : Dict , __lowerCAmelCase : str , __lowerCAmelCase : List[str] ):
a__ = ... | 657 |
from manim import *
class snake_case_ (lowerCamelCase_ ):
def lowerCamelCase__( self :Optional[Any] ) -> Optional[int]:
a__ = Rectangle(height=0.5 ,width=0.5 )
a__ = Rectangle(height=0.46 ,width=0.46 ).set_stroke(width=0 )
... | 657 | 1 |
import itertools
import string
from collections.abc import Generator, Iterable
def __lowercase ( __lowerCAmelCase : Iterable[str] , __lowerCAmelCase : int ):
a__ = iter(__lowerCAmelCase )
while True:
a__ = tuple(itertool... | 657 |
from math import pi
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 657 | 1 |
def __lowercase ( __lowerCAmelCase : int = 1_0_0_0 ):
a__ = 2**power
a__ = 0
while n:
a__ , a__ = r + n % 1_0, n // 1_0
return r
if __name__ == "__main__":
print(solution(int(str(input()).strip())))
| 657 |
from math import sqrt
def __lowercase ( __lowerCAmelCase : int ):
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 ... | 657 | 1 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
... | 657 |
import unittest
from knapsack import greedy_knapsack as kp
class snake_case_ (unittest.TestCase ):
def lowerCamelCase__( self :Optional[Any] ) -> Union[str, Any]:
a__ = [10, 20, 30, 40, 50, 60]
a__ = [2, 4, 6, 8, 10, 12]
a__ = 1... | 657 | 1 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
snake_case : Union[str, Any] ... | 657 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,... | 657 | 1 |
def __lowercase ( __lowerCAmelCase : int ):
if num <= 0:
raise ValueError('Input must be a positive integer' )
a__ = [True] * (num + 1)
a__ = 2
while p * p <= num:
if primes[p]:
for i in range(p ... | 657 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : list[int] ): # This function is recursive
a__ = len(__lowerCAmelCase )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if ar... | 657 | 1 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 657 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,
get_image_s... | 657 | 1 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_u... | 657 |
def __lowercase ( __lowerCAmelCase : int ):
a__ = generate_pascal_triangle(__lowerCAmelCase )
for row_idx in range(__lowerCAmelCase ):
# Print left spaces
for _ in range(num_rows - row_idx - 1 ):
print(end=' ... | 657 | 1 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : list[float] ):
if len(__lowerCAmelCase ) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
if any(i <= 0 for i in nums ):
... | 657 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
snake_case : str = (
'''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''',
''... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
snake_case : Tuple = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''VisionEncoder... | 657 |
def __lowercase ( __lowerCAmelCase : int ):
if length <= 0 or not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowerCAmelCase )]
if _... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case : List[Any] = {
'''configuration_convbert''': ['''CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ConvB... | 657 |
def __lowercase ( __lowerCAmelCase : list , __lowerCAmelCase : list , __lowerCAmelCase : int ):
if len(__lowerCAmelCase ) != len(__lowerCAmelCase ):
raise ValueError('The length of profit and weight must be same.' ... | 657 | 1 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import Ar... | 657 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : Optional[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if ... | 657 | 1 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __lowercase ( __lowerCAmelCase : str , __lowerCAmelCase : complex , __lowerCAmelCase : str = "x" , __lowerCAmelCase : float = 1_0**-... | 657 |
import gc
import unittest
from transformers import CTRLConfig, 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 ModelTester... | 657 | 1 |
def __lowercase ( __lowerCAmelCase : int = 1_0_0_0 ):
a__ = -1
a__ = 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
a__ = (n * n - 2 * a * n) // (2 * n - 2 * a)... | 657 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class snake_case_ (lowerCamelCase_ , lowerCamelCase_ ):
UpperCAmelCase__ ... | 657 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : int , __lowerCAmelCase : int , __lowerCAmelCase : int ... | 657 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case : Any = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConf... | 657 | 1 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
snake_case : List[str] = logging.getLogger(__name__)
class snake_case_ (lowerCamelCase_ ):
def __init__( s... | 657 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
snake_case : Dict = logging.get_logger(__name__)
snake_case : Any = {name: getattr(transformers, name + '''Fast''') for na... | 657 | 1 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def __lowercase ( __lowerCAmelCase : str ):
return "".join(sorted(__lowerCAmelCase ) )
def __lowercase ( __lowerCAmelCase : str ):
... | 657 |
from math import ceil, sqrt
def __lowercase ( __lowerCAmelCase : int = 1_0_0_0_0_0_0 ):
a__ = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
a__ = max(ceil(sqrt(outer_width**2 - l... | 657 | 1 |
from math import ceil, sqrt
def __lowercase ( __lowerCAmelCase : int = 1_0_0_0_0_0_0 ):
a__ = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
a__ = max(ceil(sqrt(outer_width**2 - l... | 657 |
from sklearn.metrics import fa_score
import datasets
snake_case : Optional[int] = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case : List[Any] = '''
Args:
pre... | 657 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
@flax.struct.dataclass... | 657 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 657 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : List[str] = logging.get_logger(__name__)
snake_case : int = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}
class... | 657 |
# 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 a... | 657 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : Any = logging.get_logger(__name__)
snake_case : Dict = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/config.json''',
}
class snake_case_ (lowe... | 657 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowercase ( __lowerCAmelCase : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('Undefined for non-integers' )
elif precision... | 657 | 1 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl import CORPUS_NA... | 657 |
def __lowercase ( __lowerCAmelCase : int = 2_0_0 ):
a__ = [1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
a__ = [0] * (pence + 1)
a__ = 1 # base case: 1 way to make 0 pence
for coin in coins:
for i in range(__lowerCAmelCase , pence... | 657 | 1 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def __lowercase ( ... | 657 |
from manim import *
class snake_case_ (lowerCamelCase_ ):
def lowerCamelCase__( self :Optional[Any] ) -> Optional[int]:
a__ = Rectangle(height=0.5 ,width=0.5 )
a__ = Rectangle(height=0.46 ,width=0.46 ).set_stroke(width=0 )
... | 657 | 1 |
def __lowercase ( __lowerCAmelCase : float ):
return 1_0 - x * x
def __lowercase ( __lowerCAmelCase : float , __lowerCAmelCase : float ):
# Bolzano theory in order to find if there is a root between a and b
if... | 657 |
from math import pi
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 657 | 1 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_common import T... | 657 |
from math import sqrt
def __lowercase ( __lowerCAmelCase : int ):
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 ... | 657 | 1 |
from __future__ import annotations
import math
snake_case : int = '''2020.9.26'''
snake_case : List[Any] = '''xcodz-dot, cclaus, dhruvmanila'''
def __lowercase ( __lowerCAmelCase : float , __lowerCAmelCase : float , __lowerCAme... | 657 |
import unittest
from knapsack import greedy_knapsack as kp
class snake_case_ (unittest.TestCase ):
def lowerCamelCase__( self :Optional[Any] ) -> Union[str, Any]:
a__ = [10, 20, 30, 40, 50, 60]
a__ = [2, 4, 6, 8, 10, 12]
a__ = 1... | 657 | 1 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_available():
import torch
... | 657 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,... | 657 | 1 |
snake_case : Union[str, Any] = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
snake_case : ... | 657 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : list[int] ): # This function is recursive
a__ = len(__lowerCAmelCase )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if ar... | 657 | 1 |
import os
import numpy
import onnx
def __lowercase ( __lowerCAmelCase : List[Any] , __lowerCAmelCase : Optional[Any] ):
a__ = a.name
a__ = b.name
a__ = ''
a__ = ''
a__ = a == b
a__ = name_a
... | 657 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,
get_image_s... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case : List[str] = {
'''configuration_blenderbot''': [
'''BLENDERBOT_PRETRA... | 657 |
def __lowercase ( __lowerCAmelCase : int ):
a__ = generate_pascal_triangle(__lowerCAmelCase )
for row_idx in range(__lowerCAmelCase ):
# Print left spaces
for _ in range(num_rows - row_idx - 1 ):
print(end=' ... | 657 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case : Dict = {'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''OP... | 657 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
snake_case : str = (
'''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''',
''... | 657 | 1 |
snake_case : Union[str, Any] = "\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
snake_case :... | 700 |
def __lowercase ( __lowerCAmelCase : int ):
if length <= 0 or not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowerCAmelCase )]
if _... | 657 | 0 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class snake_case_ (_snake_case , _snake_case ):
@register_to_config
def __in... | 701 |
def __lowercase ( __lowerCAmelCase : list , __lowerCAmelCase : list , __lowerCAmelCase : int ):
if len(__lowerCAmelCase ) != len(__lowerCAmelCase ):
raise ValueError('The length of profit and weight must be same.' ... | 657 | 0 |
def __lowercase ( __lowerCAmelCase : Any ):
a__ = int(_SCREAMING_SNAKE_CASE )
if n_element < 1:
a__ = ValueError('a should be a positive number' )
raise my_error
a__ = [1]
a__ , a__ , a__ = (0... | 702 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : Optional[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if ... | 657 | 0 |
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers import AutoCo... | 703 |
import gc
import unittest
from transformers import CTRLConfig, 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 ModelTester... | 657 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, rando... | 704 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class snake_case_ (lowerCamelCase_ , lowerCamelCase_ ):
UpperCAmelCase__ ... | 657 | 0 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxMo... | 705 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case : Any = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConf... | 657 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
snake_case : Tuple = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
snake_case : Optional[int] = [file for ... | 706 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
snake_case : Dict = logging.get_logger(__name__)
snake_case : Any = {name: getattr(transformers, name + '''Fast''') for na... | 657 | 0 |
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
'split_dict' , [
SplitDict(),
SplitDict({'train': SplitInfo(name='train' , num_bytes=1_3_3_7 , num_examples=4_2 , dataset_... | 707 |
from math import ceil, sqrt
def __lowercase ( __lowerCAmelCase : int = 1_0_0_0_0_0_0 ):
a__ = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
a__ = max(ceil(sqrt(outer_width**2 - l... | 657 | 0 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
snake_case : Any = '''https://www.indeed.co.in/jobs?q=mobile+app+development&l='''
def __lowercase ( __lowerCAmelCase : str = "mumbai" ):
a... | 708 |
from sklearn.metrics import fa_score
import datasets
snake_case : Optional[int] = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
snake_case : List[Any] = '''
Args:
pre... | 657 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : Dict = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'AutoformerConfig',
],
}
... | 709 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 657 | 0 |
def A ( __lowerCAmelCase : Tuple = 1_0_0 ):
a__ = (n * (n + 1) // 2) ** 2
a__ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(f"""{solution() = }""")
| 710 |
# 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 a... | 657 | 0 |
from sklearn.metrics import mean_squared_error
import datasets
snake_case : Optional[Any] = '\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel, O. and B... | 711 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowercase ( __lowerCAmelCase : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('Undefined for non-integers' )
elif precision... | 657 | 0 |
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