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 __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 )
... | 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 functools
def __lowercase ( __lowerCAmelCase : str , __lowerCAmelCase : str ):
a__ = len(__lowerCAmelCase )
a__ = len(__lowerCAmelCase )
@functools.cache
def min_distance(__lowerCAmelCase : int ... | 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 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
snake_case : Any = logging.get_logger(__name__)
snake_case : int = {
'''post_extract_proj''': '''feature_pro... | 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 copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import c... | 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 |
# 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... | 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 |
def __lowercase ( __lowerCAmelCase : Union[str, Any] , __lowerCAmelCase : int ):
print('\nThe shortest path matrix using Floyd Warshall algorithm\n' )
for i in range(__lowerCAmelCase ):
for j in range(__lowerCAmelCase ):
... | 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 ..utils import DummyObject, requires_backends
class snake_case_ (metaclass=lowerCamelCase_ ):
UpperCAmelCase__ : Optional[Any] = ['''torch''', '''torchsde''']
def __init__( self :Optional[int] ,*__snake_case :Optional[int] ,**__snake_case :Optional[... | 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 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def __lowercase ( __lowerCAmelCase : str , __lowerCAmelCase : Union[str, Any] , __lowerC... | 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 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
snake_case : str = ['''small''', '''medium''', '''large''']
snake_case : Tuple = '''lm_head.decoder.weight'''
snake_case : Dict = '''lm_head.weight'''
def A ( __lowerCAme... | 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 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
fr... | 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 |
'''simple docstring'''
def __lowercase ( __lowerCAmelCase : str ):
return " ".join(
''.join(word[::-1] ) if len(__lowerCAmelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
... | 712 |
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 | 0 |
class snake_case_ :
def __init__( self :List[Any] ,__snake_case :str = "" ,__snake_case :bool = False ) -> None:
# Mapping from the first character of the prefix of the node
a__ = {}
# A node will be a leaf if the tree contains its wor... | 713 |
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 | 0 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class snake_cas... | 714 |
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 | 0 |
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... | 715 |
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 | 0 |
# 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... | 716 |
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 | 0 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
snake_case : str = logging.get_logger(__name__)
def __lowercase ( __lowerCAmelCase : List[Any]=None , ... | 717 |
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 | 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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
snake_ca... | 718 |
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 | 0 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_E... | 719 |
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 | 0 |
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
... | 720 |
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 | 0 |
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
snake_case : Dict = [
# tf -> hf
('''/''', '''.'''),
('''layer_''', '''layers.'''),
('''kernel''', ... | 721 |
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 | 0 |
# 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... | 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'''
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()
cl... | 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 |
import os
def __lowercase ( __lowerCAmelCase : Optional[int] ):
a__ = len(grid[0] )
a__ = len(__lowerCAmelCase )
a__ = 0
a__ = 0
a__ = 0
# Check vertically, horizontally, diagonally at the same time (only work... | 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 json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.set_verbosi... | 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 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... | 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 |
from ..utils import DummyObject, requires_backends
class snake_case_ (metaclass=lowerCamelCase_ ):
UpperCAmelCase__ : List[str] = ['''speech''']
def __init__( self :Any ,*__snake_case :Dict ,**__snake_case :List[str] ) -> Dict:
re... | 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
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
... | 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 argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
snake_case = logging.get_logger(__name__)
snake_case = {name: getattr(transformers, name + '''Fast''') for name in SLOW_TO_FAST_CONVER... | 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 |
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... | 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 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case : Optional[int] = logging.get_logger(__name__)
snake_case : Any = '''▁'''... | 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 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
... | 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 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy ... | 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 |
'''simple docstring'''
from statistics import mean
import numpy as np
def __lowercase ( __lowerCAmelCase : list , __lowerCAmelCase : list , __lowerCAmelCase : list , __lowerCAmelCase : int ):
a__ = 0
... | 712 |
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 | 0 |
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 ,' ... | 713 |
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 | 0 |
import cva
import numpy as np
class snake_case_ :
def __init__( self :Tuple ,__snake_case :float ,__snake_case :int ) -> List[str]:
if k in (0.04, 0.06):
a__ = k
a__ = window_size
else:
... | 714 |
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 | 0 |
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 ... | 715 |
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 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.tes... | 716 |
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 | 0 |
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... | 717 |
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 | 0 |
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
snake_case : Dict = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplification},
authors={Xu, ... | 718 |
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 | 0 |
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... | 719 |
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 | 0 |
def __lowercase ( __lowerCAmelCase : int | float | str ):
try:
a__ = float(__lowerCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
a__ = decimal - int(__lowerCAmelCase )
if fractio... | 720 |
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 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
from t... | 721 |
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 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
snake_case : Any = {
'''configuration_altclip''': [
'''ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''AltCLIPConfig''',
'''AltCLIPTe... | 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'''
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] = {
'''voca... | 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 |
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 ( ... | 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 |
# 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... | 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 ...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... | 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 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : List[str] = logging.get_logger(__name__)
snake_case : Union[str, Any] = {
'''google/fnet-base''': '''https://huggingface.co/google/fnet-base/resolve/main/config.json''',
'''google/fnet-l... | 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 inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils import patch_environ... | 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 itertools
import string
from collections.abc import Generator, Iterable
def __lowercase ( __lowerCAmelCase : Iterable[str] , __lowerCAmelCase : int ):
a__ = iter(__lowerCAmelCase )
while True:
a__ = tuple(itertool... | 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 |
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... | 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 |
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__ ... | 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 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from... | 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 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def __lowercase ( __lowerCAmelCase : Any , __lowerCAmelCase : Dict , __lowerCAmelCase : str , __lowerCAmelCase : List[str] ):
... | 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 |
'''simple docstring'''
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 ... | 712 |
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 | 0 |
import os
from distutils.util import strtobool
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : Optional[int] ):
for e in env_keys:
a__ = int(os.environ.get(__lowerCAmelCase , -1 ) )
if val >... | 713 |
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 | 0 |
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... | 714 |
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 | 0 |
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 : ... | 715 |
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 | 0 |
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 ... | 716 |
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 | 0 |
def __lowercase ( __lowerCAmelCase : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
a__ = F'Input value of [number={number}] must be an integer'
raise TypeError(__lowerCAmelCase )
if number < 0:
... | 717 |
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 | 0 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
from ... | 718 |
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 | 0 |
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class snake_case_ (lowerCamelCase_ , unittest.TestCase ):
UpperCAmelCase__ : str = ... | 719 |
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 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.testing_utils import DUMMY... | 720 |
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 | 0 |
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... | 721 |
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 | 0 |
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... | 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'''
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,
... | 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 |
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallback,
TrainingArgument... | 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 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''',
''... | 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
from typing import Dict
from ...configuration_utils import PretrainedConfig
snake_case : List[Any] = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytorch''': ... | 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 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
snake_case : Optional[Any] = {
'''configuration_layoutlmv2''': ['''LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 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 gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full... | 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 subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case_ (lowerCamelCase_ ):
@require_torch
def lowerCamelCase__( self :Union[str, Any] ) -> L... | 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 |
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... | 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 |
# 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
... | 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 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class snake_cas... | 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 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, we had to include ... | 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 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
snake_case ... | 712 |
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 | 0 |
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... | 713 |
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 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case : Optional[int] = logging.get_logger(__name__)
snake_case : Any = {'''voc... | 714 |
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 | 0 |
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... | 715 |
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 | 0 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class snake_case_ (unittest.TestCase ):
def lowerCamelCase__( self :Dict ) -> Any:
a__ = [... | 716 |
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 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : List[Any] = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritten/resolve... | 717 |
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 | 0 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 718 |
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 | 0 |
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] ... | 719 |
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 | 0 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import GenerationTes... | 720 |
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 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
snake_case : List[str] = logging.get_logger(__name__)
class snake_case_ (lowerCamelCase_ ):
UpperCAmelCase__ : Optional[Any] ... | 721 |
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 | 0 |
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 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 Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (... | 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 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDetection
from... | 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 |
from maths.prime_factors import prime_factors
def __lowercase ( __lowerCAmelCase : int ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
a__ = F'Input value of [number={number}] must be an integer'
raise TypeError(__low... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : int = logging.get_logger(__name__)
snake_case : Dict = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json''... | 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 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... | 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 math
def __lowercase ( __lowerCAmelCase : float , __lowerCAmelCase : float ):
return math.pow(__lowerCAmelCase , 2 ) - a
def __lowercase ( __lowerCAmelCase : float ):
return 2 * x
def ... | 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 |
from __future__ import annotations
import math
snake_case = '''2020.9.26'''
snake_case = '''xcodz-dot, cclaus, dhruvmanila'''
def __lowercase ( __lowerCAmelCase : float , __lowerCAmelCase : float , __lowerCAmelCase : float ... | 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 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class snake_case_ (lowerCamelCase_ , unittest.TestCase ):
UpperCA... | 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 |
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
... | 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 |
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastapi.routing import A... | 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 __future__ import annotations
import math
def __lowercase ( __lowerCAmelCase : int , __lowerCAmelCase : int , __lowerCAmelCase : bool , __lowerCAmelCase : list[int] , __lowerCAmelCase : ... | 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 |
'''simple docstring'''
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/co... | 712 |
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 | 0 |
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:
... | 713 |
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 | 0 |
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