code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'Salesforce/blip-vqa-base': 'https://huggingface.co/Salesforce/blip-vqa-base/resolve... | 61 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 | 0 |
snake_case = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
snake_case = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def lowerCamelCase__ ( lowercase , lowercase , lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[Any] ... | 62 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 | 0 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowerCamelCase__ ( __lowerCamelCase : int , __lowerCamelCase : Any , __lowerC... | 63 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tup... | 8 | 0 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
lowercase_ : int = logging.get_logger(__name__)
def A__ ( snake_case_ : Any , snake_case_ : Lis... | 64 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
l... | 8 | 0 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
__UpperCAmelCase = pd.read_csv('sample_data.csv', header... | 65 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingf... | 8 | 0 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCamelCase = "%20".join(argv[1:]) if len(argv) > 1 else quote(str(input("Search: ")))
print("G... | 66 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __snake_case : int ) -> int:
if number != int(__snake_case ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueE... | 8 | 0 |
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 = {
"""configuration_al... | 67 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 | 0 |
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from transformers import A... | 68 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( _UpperCAmelCase : int ) -> Tuple:
__snake_case = 1
__snake_case = 2
while i * i <= n:
__snake_case = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
... | 69 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int , __snake_case : int , __snake_case : int ) -> float:
__A : Dict = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of s... | 8 | 0 |
from collections import Counter
from timeit import timeit
def _SCREAMING_SNAKE_CASE ( lowercase : str = "" , ):
'''simple docstring'''
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values() ) < 2
def _SCREAMING_S... | 70 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 | 0 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_copie... | 71 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __magic_name__ ( __SCREAMING_SNAKE_CASE ):
@staticmethod
@abstractmethod
def _A( snake_case_ ):
raise NotImplementedError()
@abstractmethod
def _A( self ... | 72 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
a_ : Optional[Any] = logging.get_logger(__name__)
a_ : Tuple = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve/main/config.json',... | 73 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ ... | 8 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json""",
}
class __UpperCamelCase ( lowerC... | 74 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 | 0 |
'''simple docstring'''
def a__ ( lowerCAmelCase__ = 1_00_00_00 ) -> int:
UpperCAmelCase__ : str = 1
UpperCAmelCase__ : int = 1
UpperCAmelCase__ : int = {1: 1}
for inputa in range(2 , lowerCAmelCase__ ):
... | 75 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configura... | 8 | 0 |
"""simple docstring"""
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licen... | 76 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 8 | 0 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import g... | 77 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS... | 8 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int = 10_00 ) -> int:
'''simple docstring'''
return sum(e for e in range(3 , snake_case_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f"{solution() = }")
| 78 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .toke... | 79 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
__UpperCamelCase : Union[str, Any] = logging.get_logger(__... | 80 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 0 |
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
_snake_case : Optional[int] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Any , ... | 81 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Optional[Any] ) -> Optional[Any]: # noqa: E741
__A : Tuple = len(__snake_case )
__A : Optional[int] = 0
__A : str = [0] * n
__A : int = [Fals... | 8 | 0 |
"""simple docstring"""
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
... | 82 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase__ = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCH... | 83 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 | 0 |
import copy
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 ..auto import CONFIG_MAPPING
UpperCAmelCase = logging.get_logger(__name__)
UpperCA... | 84 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ : Optional[int] = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
... | 85 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tup... | 8 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def __snake_case ( __UpperCamelCase : Optional[int] ):
"""simple docstring"""
if "img_encoder.pos_embed" in name:
A_ ... | 86 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
l... | 8 | 0 |
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since... | 87 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingf... | 8 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class lowercase__ ( unittest.TestCase ):
__Up... | 88 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __snake_case : int ) -> int:
if number != int(__snake_case ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueE... | 8 | 0 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_... | 89 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCAmelCase = {
'''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''],
... | 90 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 | 0 |
"""simple docstring"""
from queue import PriorityQueue
from typing import Any
import numpy as np
def _snake_case ( snake_case__ : dict , snake_case__ : str , snake_case__ : set , snake_case__ : set , snake_case__ : dict , snake_case__ : dict , snake_case... | 91 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int , __snake_case : int , __snake_case : int ) -> float:
__A : Dict = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of s... | 8 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( __magic_name__ : float , __magic_name__ : float ) -> float:
if mass < 0:
raise ValueError('''The mass of a body cannot be negative''' )
return 0.5 * mass * abs(__magic_name__ ) * abs(__magic_name__... | 92 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _lowerCAmelCase ( unittest.T... | 93 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 0 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowercase_ ( __A : dict , __A : str , __A : set , __A : set , __A : dict , __A : dict , __A : ... | 94 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 0 |
"""simple docstring"""
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_avai... | 95 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ ... | 8 | 0 |
"""simple docstring"""
import requests
__lowerCamelCase = '' # <-- Put your OpenWeatherMap appid here!
__lowerCamelCase = 'https://api.openweathermap.org/data/2.5/'
def a ( __UpperCAmelCase : str = "Chicago" , __UpperCAmelCase : str = AP... | 96 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 | 0 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def a ( snake_case__: Dict , snake_case__: Any , snake_case__: Dict ):
'''simple docstring'''
lowercase_ = AutoConfig.from_pretrained(snake_case__ )
... | 97 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configura... | 8 | 0 |
'''simple docstring'''
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowercase__ : str = 'http://w... | 98 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 8 | 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_... | 99 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS... | 8 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_ten... | 100 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 0 |
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def a__ ( A__=None... | 101 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : str = logging.get_logger(__name__)
__magic_name__ : Union[str, Any] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rw... | 102 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 0 |
"""simple docstring"""
from __future__ import annotations
import time
snake_case = list[tuple[int, int]]
snake_case = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, ... | 103 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Optional[Any] ) -> Optional[Any]: # noqa: E741
__A : Tuple = len(__snake_case )
__A : Optional[int] = 0
__A : str = [0] * n
__A : int = [Fals... | 8 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
UpperCamelCase = {"""vocab_file""": """vocab.txt"... | 104 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase__ : str = logging.get_logger(__name__)
UpperCamelCase__ : str = {
'''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json... | 105 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
fr... | 106 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 | 0 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
_UpperCAmelCase : Dict = '''
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)
'''
_UpperCAmelCase : ... | 107 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tup... | 8 | 0 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( __snake_case ) -> int:
_UpperCAmelCase = len(__snake_case ) // 2
# choose the middle 3 elements
_UpperCAmelCase = lst[m - 1 : m + 2]
# if middle element is peak
if three[1... | 108 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
l... | 8 | 0 |
'''simple docstring'''
import re
def __magic_name__ ( __UpperCAmelCase ) -> list:
'''simple docstring'''
return [char.split() for char in re.split(R"""[^ a-z A-Z 0-9 \s]""" , str_ )]
def __magic_name__ ( __UpperCAmelCase ) -> str:
'''s... | 109 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingf... | 8 | 0 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class a ( low... | 110 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __snake_case : int ) -> int:
if number != int(__snake_case ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueE... | 8 | 0 |
_lowerCamelCase : str = 0 # The first color of the flag.
_lowerCamelCase : List[Any] = 1 # The second color of the flag.
_lowerCamelCase : str = 2 # The third color of the flag.
_lowerCamelCase : List[str] = (red, white, blue)
def SCREAM... | 87 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 | 0 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase_ ( a__ , a__ ):
@register_to_config
def __init__( self , *,
__A = 4 , __A = 768 ... | 443 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 | 0 |
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,
)
UpperCamelCase_ = {'''configuration_mbart... | 625 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int , __snake_case : int , __snake_case : int ) -> float:
__A : Dict = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of s... | 8 | 0 |
'''simple docstring'''
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, p... | 334 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
import queue
class UpperCamelCase__ :
def __init__( self : str , lowerCamelCase : List[str] ):
'''simple docstring'''
a__ = data
a__ = None
a__ = None
... | 489 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Pad... | 330 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 0 |
def A ( _SCREAMING_SNAKE_CASE ) -> Optional[int]:
lowerCamelCase : List[str] = 0
lowerCamelCase : Optional[int] = len(__snake_case )
for i in range(n - 1 ):
for j in range(i + 1 ,__snake_case ):
... | 311 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ ... | 8 | 0 |
import re
from ..models.auto import AutoProcessor
from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
from ..utils import is_vision_available
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class _A ( a__ ):
_UpperCamelCase : Option... | 217 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
from functools import lru_cache
from math import ceil
snake_case_ : str = 100
snake_case_ : Tuple = set(range(3, NUM_PRIMES, 2))
primes.add(2)
snake_case_ : int
for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
if pri... | 212 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configura... | 8 | 0 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
a_ : Any = parse(importlib.metadata.version("""torch"""))
def a_ ( __snake_case : Union[str, Version] , __snake_c... | 676 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 8 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase__ ( a__):
UpperCamelCase_ = ["""image_processor""", """tokenizer"""]
UpperCamelCase_ = """CLIPImageProcessor"""
UpperCamelCase_ = ("... | 248 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS... | 8 | 0 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
_lowerCamelCase : Union[str, Any] = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE ( lowercase_=None , ... | 87 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 0 |
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : Dict , UpperCAmelCase_ : Any , UpperCAmelCase_ : Tuple=0 ) -> Any:
# Format the message.
... | 443 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 0 |
def _UpperCAmelCase ( A = 50 ):
'''simple docstring'''
UpperCAmelCase__ =[1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
... | 625 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 0 |
'''simple docstring'''
class __UpperCamelCase :
def __init__( self :List[Any] ):
snake_case_ : Union[str, Any] = {}
def a__ ( self :List[Any] ):
print(self.vertex )
for i in self.vertex:
print(_UpperCAm... | 334 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Optional[Any] ) -> Optional[Any]: # noqa: E741
__A : Tuple = len(__snake_case )
__A : Optional[int] = 0
__A : str = [0] * n
__A : int = [Fals... | 8 | 0 |
'''simple docstring'''
import sys
lowerCAmelCase_ : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295... | 489 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 0 |
'''simple docstring'''
def __lowercase ( __lowercase , __lowercase , __lowercase , __lowercase ) -> int:
'''simple docstring'''
_A = len(__snake_case ), len(grid[0] )
if (
min(__snake_case , __snake_case ) < 0
or row == row... | 330 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ : Union[str, Any] = {
'''configuration_blip_2''': [
'''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Blip2Config''',
'''Blip2... | 311 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 | 0 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
lowerCAmelCase_ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'
' Distillat... | 217 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tup... | 8 | 0 |
'''simple docstring'''
def __snake_case ( _UpperCAmelCase : Dict):
UpperCamelCase = [0] * len(__snake_case)
UpperCamelCase = []
UpperCamelCase = [1] * len(__snake_case)
for values in graph.values():
for i in values:
indegree[i] += 1
for i in rang... | 212 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
l... | 8 | 0 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'''kwargs, expected''' , [
({'''num_shards''': 0, '''max_num_jobs''': 1}, []),
({'''num_shards''': 10, '''max_nu... | 676 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingf... | 8 | 0 |
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.uti... | 248 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __snake_case : int ) -> int:
if number != int(__snake_case ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueE... | 8 | 0 |
import torch
from diffusers import DiffusionPipeline
class UpperCamelCase_ ( a__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , UpperCAmelCase__ : List[str] , UpperCAmelCase__ : int) ->str:
'''simple docstring'''
... | 87 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
raise Option... | 443 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 | 0 |
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
UpperCamelCase_ = 0
UpperCamelCase_ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
... | 625 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int , __snake_case : int , __snake_case : int ) -> float:
__A : Dict = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of s... | 8 | 0 |
'''simple docstring'''
import numpy as np
import datasets
__A : Optional[int] = '''
Compute the Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distanc... | 334 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : int = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''Mega... | 489 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase_ = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''',... | 330 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def A ( _SCREAMING_SNAKE_CASE ) -> int:
lowerCamelCase : Union[str, Any] = SwinConfig(image_size=192 )
... | 311 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ ... | 8 | 0 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
... | 217 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase__ ( a__, ... | 212 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configura... | 8 | 0 |
'''simple docstring'''
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
a_ : List[str] = object()
# For specifying empty leaf dict `{}`
a_ : str = object()
de... | 676 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 8 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase__ ( a__):
UpperCamelCase_ = ["""image_processor""", """tokenizer"""]
UpperCamelCase_ = """AutoImageProcessor"""
UpperCamelCase_ = """AutoTokenizer"""
... | 248 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS... | 8 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ = 10 ) -> str:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ) or n < 0:
raise ValueError('''Invalid input''' )
A__ = 10**n
A__ = 28_433 * (pow(2 , 7_83... | 87 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'''
... | 443 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 0 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVision... | 625 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 0 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_uti... | 334 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Optional[Any] ) -> Optional[Any]: # noqa: E741
__A : Tuple = len(__snake_case )
__A : Optional[int] = 0
__A : str = [0] * n
__A : int = [Fals... | 8 | 0 |
'''simple docstring'''
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.trans... | 489 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 0 |
'''simple docstring'''
import math
import sys
def __lowercase ( __lowercase ) -> int:
'''simple docstring'''
if number != int(__snake_case ):
raise ValueError("the value of input must be a natural number" )
if number < 0:
raise ValueError("the va... | 330 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE__ : int = {
'''configuration_m2m_100''': ['''M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''M2M100Config''', '''M2M100OnnxConfig'... | 311 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class _A ( unittest.TestCase ):
def __a ... | 217 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tup... | 8 | 0 |
'''simple docstring'''
from math import sqrt
def __snake_case ( _UpperCAmelCase : int):
assert isinstance(__snake_case, __snake_case) and (
number >= 0
), "'number' must been an int and positive"
UpperCamelCase = True
# 0 and 1 are none primes.
if nu... | 212 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
l... | 8 | 0 |
'''simple docstring'''
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
Alber... | 676 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingf... | 8 | 0 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def A ( _lowercase , _lowercase ):
SCREAMING_SNAKE_CASE : Optional[int] = list(__snake_case )
SCREAMING_SNAKE_CASE : int = list(__snak... | 248 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __snake_case : int ) -> int:
if number != int(__snake_case ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueE... | 8 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> Union[str, Any]:
"""simple docstring"""
_enforce_args(__snake_case , __snake_case )
if n == 0:
return 0
A__ = float('''-inf''' )
for i in range(1 , n +... | 87 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 | 0 |
from PIL import Image
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : Image , UpperCAmelCase_ : float ) -> Image:
def brightness(UpperCAmelCase_ : int ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if not -255.0 <= level <= 255.0:
... | 443 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 | 0 |
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
UpperCamelCase_ = logging.get_logger(__name_... | 625 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int , __snake_case : int , __snake_case : int ) -> float:
__A : Dict = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of s... | 8 | 0 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class __UpperCamelCase ( unittest.TestCase ):
def a__ ( self :int ):
snake_case_ : Dict ... | 334 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ : str = {
'''config... | 489 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepen... | 330 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 0 |
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