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 gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params impo... | 101 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'microsoft/git-base': 'https://huggingface.co/mi... | 101 | 1 |
import re
from filelock import FileLock
try:
import nltk
lowerCAmelCase__ : List[str] =True
except (ImportError, ModuleNotFoundError):
lowerCAmelCase__ : Union[str, Any] =False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('... | 101 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 101 | 1 |
from itertools import count
def a__ ( A__ = 5_0 ):
SCREAMING_SNAKE_CASE_ : str = [1] * min_block_length
for n in count(A__ ):
fill_count_functions.append(1 )
for block_length in range(A__, n + 1 ):
for block_start in range(n... | 101 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 101 | 1 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class __lowercase (u... | 101 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAM... | 101 | 1 |
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__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 101 | 1 |
from __future__ import annotations
import typing
from collections import Counter
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : typing.Counter[int] = Counter()
for base in range(1, max_perimeter + 1 ):
for perpendicular in range(A__, max_perimeter ... | 101 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 | 1 |
from __future__ import annotations
class __lowercase :
"""simple docstring"""
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ , ... | 101 |
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """WhisperFeatureExtractor"""
_UpperCAmelCase = """WhisperTokenizer"""
de... | 101 | 1 |
lowerCAmelCase__ : Union[str, Any] =range(2, 20 + 1)
lowerCAmelCase__ : Optional[Any] =[10**k for k in range(ks[-1] + 1)]
lowerCAmelCase__ : dict[int, dict[int, list[list[int]]]] ={}
def a__ ( A__, A__, A__, A__ ):
SCREAMING... | 101 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 1 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, reca... | 101 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase (__SCREAMING_SNAKE_CASE ):
... | 101 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension... | 101 |
# 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 re... | 101 | 1 |
from __future__ import annotations
from collections import namedtuple
def a__ ( A__, A__, A__ ):
SCREAMING_SNAKE_CASE_ : Tuple = namedtuple('result', 'name value' )
if (voltage, current, power).count(0 ) != 1:
raise ValueError('Only on... | 101 |
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__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 | 1 |
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTe... | 101 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import ... | 101 | 1 |
from math import sqrt
def a__ ( A__ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes ... | 101 |
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = ''
for i in table:
res += inp[i - 1]
return res
def a__ ( A__ ):
return data[1:] + data[0]
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_... | 101 | 1 |
from __future__ import annotations
def a__ ( A__, A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = list(range(len(A__ ) ) )
SCREAMING_SNAKE_CASE_ : int = [v / w for v, w in zip(A__, A__ )]
index.sort(key=lambda A__ :... | 101 |
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_available, is_... | 101 | 1 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class __lowercase :
"""simple docstring"""
_UpperCAmelCase = 42
... | 101 |
from __future__ import annotations
def a__ ( A__, A__ = None, A__ = None ):
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(A__ ) - 1
if start >= end:... | 101 | 1 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowerCAmelCase__ : Dict =(3, 9, -11, 0, 7, 5, 1, -1)
lowerCAmelCase__ : Optional[int] =(4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __lowercase ... | 101 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 101 | 1 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """Speech2TextFeatureExtractor"""
_UpperCAmel... | 101 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import ... | 101 | 1 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_r... | 101 |
def a__ ( A__ = 5_0_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set()
SCREAMING_SNAKE_CASE_ : Optional[int] = int((limit - 2_4) ** (1 / 2) )
SCREAMING_SNAKE_CASE_ : Dict = set(range(3, prime_square_limit + 1, 2 ) )
... | 101 | 1 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available():... | 101 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Any = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 101 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Union[str, Any] =logging.get_logger(__name__)
lowerCAmelCase__ : List[Any] ={
'BAAI/AltCLIP': 'https://huggingface.co/BA... | 101 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__ : Optional[int] =0B1011_0011_1110_1100_1001_0000_0111_... | 101 | 1 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = FileLock(str(tmpdir / 'foo.lock' ) )
SCREAMING_SNAKE_CASE_ : List[str] = FileLock(str(tmpdi... | 101 |
def a__ ( A__, A__ ):
def get_matched_characters(A__, A__ ) -> str:
SCREAMING_SNAKE_CASE_ : Dict = []
SCREAMING_SNAKE_CASE_ : Any = min(len(_stra ), len(_stra ) ) // 2
for i, l in enumerate(_stra ):
SCREAMIN... | 101 | 1 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils impor... | 101 |
from __future__ import annotations
lowerCAmelCase__ : Union[str, Any] =[
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( A__, A__, A__, A__, A__, ):
SCREAMING_SNAKE_CASE_ : List[Any] = ... | 101 | 1 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : str ={'vocab_file': 'vocab.json'}
lowerCAmelCase__ : ... | 101 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'microsoft/git-base': 'https://huggingface.co/mi... | 101 | 1 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 101 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = ["""image_processor""", """tokenizer""... | 101 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 101 | 1 |
from __future__ import annotations
def a__ ( A__ ):
if len(A__ ) == 0:
return []
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Any = min(A__ ), max(A__ )
SCREAMING_SNAKE_CASE_ : Optional[Any] = int(max_value - min_value ) ... | 101 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAM... | 101 | 1 |
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 i... | 101 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 101 | 1 |
def a__ ( A__, A__ ):
return number | (1 << position)
def a__ ( A__, A__ ):
return number & ~(1 << position)
def a__ ( A__, A__ ):
return number ^ (1 << position)
def a__ ( A__, A__ ):
... | 101 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 | 1 |
# flake8: noqa
# Lint as: python3
lowerCAmelCase__ : Optional[Any] =[
'VerificationMode',
'Version',
'disable_progress_bar',
'enable_progress_bar',
'is_progress_bar_enabled',
'experimental',
]
from .info_utils import VerificationMode
from .logging import disable_... | 101 |
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """WhisperFeatureExtractor"""
_UpperCAmelCase = """WhisperTokenizer"""
de... | 101 | 1 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softm... | 101 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 1 |
def a__ ( A__ = 2_0_0 ):
SCREAMING_SNAKE_CASE_ : int = [1, 2, 5, 1_0, 2_0, 5_0, 1_0_0, 2_0_0]
SCREAMING_SNAKE_CASE_ : Optional[int] = [0] * (pence + 1)
SCREAMING_SNAKE_CASE_ : List[str] = 1 # base case: 1 way to make 0 pence
for coin in coins... | 101 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase (__SCREAMING_SNAKE_CASE ):
... | 101 | 1 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xfo... | 101 |
# 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 re... | 101 | 1 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_co... | 101 |
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__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 | 1 |
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
... | 101 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import ... | 101 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import... | 101 |
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = ''
for i in table:
res += inp[i - 1]
return res
def a__ ( A__ ):
return data[1:] + data[0]
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_... | 101 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"... | 101 |
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_available, is_... | 101 | 1 |
from __future__ import annotations
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Tuple = [True] * limit
SCREAMING_SNAKE_CASE_ : List[str] = False
SCREAMING_SNAKE_CASE_ : Optional[Any] = False
SCREAMING_SNAKE_CASE_ : str = Tr... | 101 |
from __future__ import annotations
def a__ ( A__, A__ = None, A__ = None ):
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(A__ ) - 1
if start >= end:... | 101 | 1 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase__ : List[Any] =get_tests_dir('fixtu... | 101 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 101 | 1 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_... | 101 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import ... | 101 | 1 |
def a__ ( A__ ):
if length <= 0 or not isinstance(A__, A__ ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(A__ )]
if __name__ == "__main__":
print(hexagonal_numbers(length=5))
print(hexagonal_numbers(leng... | 101 |
def a__ ( A__ = 5_0_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set()
SCREAMING_SNAKE_CASE_ : Optional[int] = int((limit - 2_4) ** (1 / 2) )
SCREAMING_SNAKE_CASE_ : Dict = set(range(3, prime_square_limit + 1, 2 ) )
... | 101 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Any = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 101 | 1 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowerCAmelCase__ : int =pytest.mark.integration
@pytest.mark.paramet... | 101 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__ : Optional[int] =0B1011_0011_1110_1100_1001_0000_0111_... | 101 | 1 |
def a__ ( A__ ):
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError('The given input must be positive' )
# get the generated string sequence
SCREAMING_SNAKE_CASE_ : Optional[int] = gray_code_sequence_string(A__ )
#... | 101 |
def a__ ( A__, A__ ):
def get_matched_characters(A__, A__ ) -> str:
SCREAMING_SNAKE_CASE_ : Dict = []
SCREAMING_SNAKE_CASE_ : Any = min(len(_stra ), len(_stra ) ) // 2
for i, l in enumerate(_stra ):
SCREAMIN... | 101 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 101 |
from __future__ import annotations
lowerCAmelCase__ : Union[str, Any] =[
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( A__, A__, A__, A__, A__, ):
SCREAMING_SNAKE_CASE_ : List[Any] = ... | 101 | 1 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __lowercase (pl.LightningModule ):
"""simple docstring"""
def __init__( self , ... | 101 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'microsoft/git-base': 'https://huggingface.co/mi... | 101 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Union[str, Any] ={
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json'... | 101 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 101 | 1 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __lowercase :
"""simple docstring"""
_UpperCAmelCase = 42
_UpperCAmelCase ... | 101 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 101 | 1 |
lowerCAmelCase__ : List[Any] ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lowerCAmelCas... | 101 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAM... | 101 | 1 |
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 .tokenization_f... | 101 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 101 | 1 |
def a__ ( A__ = 5_0_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set()
SCREAMING_SNAKE_CASE_ : Optional[int] = int((limit - 2_4) ** (1 / 2) )
SCREAMING_SNAKE_CASE_ : Dict = set(range(3, prime_square_limit + 1, 2 ) )
... | 101 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 | 1 |
from collections.abc import Callable
import numpy as np
def a__ ( A__, A__, A__, A__, A__ ):
SCREAMING_SNAKE_CASE_ : Dict = int(np.ceil((x_end - xa) / step_size ) )
SCREAMING_SNAKE_CASE_ : int = np.zeros((n + 1,) )
SC... | 101 |
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """WhisperFeatureExtractor"""
_UpperCAmelCase = """WhisperTokenizer"""
de... | 101 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : List[str] =logging.get_logger(__name__)... | 101 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 1 |
import os
import pytest
from attr import dataclass
lowerCAmelCase__ : Any ='us-east-1' # defaults region
@dataclass
class __lowercase :
"""simple docstring"""
_UpperCAmelCase = 42
_UpperCAmelCase = """a... | 101 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase (__SCREAMING_SNAKE_CASE ):
... | 101 | 1 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Any = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 101 |
# 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 re... | 101 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_timesformer': ['TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TimesformerConfig'],
}
try:
if not is_torch_available():
... | 101 |
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__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 | 1 |
import unittest
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepa... | 101 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import ... | 101 | 1 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_com... | 101 |
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = ''
for i in table:
res += inp[i - 1]
return res
def a__ ( A__ ):
return data[1:] + data[0]
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_... | 101 | 1 |
from collections.abc import Iterable
from typing import Generic, TypeVar
lowerCAmelCase__ : List[Any] =TypeVar('_T')
class __lowercase (Generic[_T] ):
"""simple docstring"""
def __init__( self , lowerCAmelCase__ = None ... | 101 |
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_available, is_... | 101 | 1 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
lowerCAmelCase__ : Optional[Any] =[
'Prosecutor: "No videos were used in the crash investigation" German papers say they saw... | 101 |
from __future__ import annotations
def a__ ( A__, A__ = None, A__ = None ):
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(A__ ) - 1
if start >= end:... | 101 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrFor... | 101 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 101 | 1 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from .... | 0 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import ... | 101 | 0 |
from collections.abc import Generator
from math import sin
def _A ( _lowercase ) -> bytes:
"""simple docstring"""
if len(_lowercase ) != 32:
raise ValueError('Input must be of length 32' )
__UpperCamelCase = B''
for i in [3, 2, 1, 0]:
... | 1 |
def a__ ( A__ = 5_0_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set()
SCREAMING_SNAKE_CASE_ : Optional[int] = int((limit - 2_4) ** (1 / 2) )
SCREAMING_SNAKE_CASE_ : Dict = set(range(3, prime_square_limit + 1, 2 ) )
... | 101 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
"""configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}
try:
if not is_torch_available():
raise OptionalDe... | 2 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Any = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 101 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMi... | 3 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__ : Optional[int] =0B1011_0011_1110_1100_1001_0000_0111_... | 101 | 0 |
"""simple docstring"""
import numpy as np
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : np.ndarray , _UpperCAmelCase : np.ndarray , _UpperCAmelCase : float = 1e-12 , _UpperCAmelCase : int = 100 , ):
assert np.shape(_UpperCAmelCase )[0] == np.shape(_UpperCAmel... | 4 |
def a__ ( A__, A__ ):
def get_matched_characters(A__, A__ ) -> str:
SCREAMING_SNAKE_CASE_ : Dict = []
SCREAMING_SNAKE_CASE_ : Any = min(len(_stra ), len(_stra ) ) // 2
for i, l in enumerate(_stra ):
SCREAMIN... | 101 | 0 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
_lowercase = """\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Bl... | 5 |
from __future__ import annotations
lowerCAmelCase__ : Union[str, Any] =[
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( A__, A__, A__, A__, A__, ):
SCREAMING_SNAKE_CASE_ : List[Any] = ... | 101 | 0 |
def SCREAMING_SNAKE_CASE__ ( ):
return [list(range(1_000 - i , -1_000 - i , -1 ) ) for i in range(1_000 )]
_lowerCamelCase = generate_large_matrix()
_lowerCamelCase = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
[[3, 2], ... | 6 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'microsoft/git-base': 'https://huggingface.co/mi... | 101 | 0 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 7 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 101 | 0 |
'''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 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 101 | 0 |
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def A ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> Tuple:
A__ = s.rsplit(__UpperCamelCase , __UpperCamelCase ... | 9 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAM... | 101 | 0 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
DataCo... | 10 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 101 | 0 |
'''simple docstring'''
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __A ( unittest.TestCase ):
'''simple docstring'''
__lowerCamelCase : Tuple = JukeboxTokenizer
__lowerCamelCase : Dict = {... | 11 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 | 0 |
def UpperCamelCase ( lowercase_ ) -> bool:
'''simple docstring'''
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def UpperCamelCase ( lowercase_ ) -> bool:
'''simple docstring'''
lowercase__ ... | 12 |
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """WhisperFeatureExtractor"""
_UpperCAmelCase = """WhisperTokenizer"""
de... | 101 | 0 |
'''simple docstring'''
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,
)
if is_sentencepiece_available():
from ..ta... | 13 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 0 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__lowercase )
class UpperCAmelCase_ ( __lowercase ):
"""simple docstring"""
UpperCAmelCase__ :... | 14 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase (__SCREAMING_SNAKE_CASE ):
... | 101 | 0 |
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
A : List[str] = logging.getLogger(__name__)
if is_torch_tpu_available... | 15 |
# 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 re... | 101 | 0 |
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
@require_torch
@require_optimum
@s... | 16 |
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__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 | 0 |
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
UpperCAmelCase_ : List[str] = '''\
@inproceedings{popovic-2015-chrf,
title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",
author = "Popovi{\'c}, Maja",
booktitle = "Proc... | 17 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import ... | 101 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class lowerCAmelCase... | 18 |
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[Any] = ''
for i in table:
res += inp[i - 1]
return res
def a__ ( A__ ):
return data[1:] + data[0]
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_... | 101 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTowe... | 19 |
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_available, is_... | 101 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class lowercase_ (lowercase__ ):
def __init__( self , lowercase_ , lowercase_) -> Tuple:
a__ =params
a__ =np.array(lowercase_)
a__ ... | 20 |
from __future__ import annotations
def a__ ( A__, A__ = None, A__ = None ):
if start is None:
SCREAMING_SNAKE_CASE_ : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(A__ ) - 1
if start >= end:... | 101 | 0 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
requ... | 21 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 101 | 0 |
'''simple docstring'''
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
_snake_case : Tuple = {
'linear': PIL.Image.Resampling.BILINEAR,
... | 22 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import ... | 101 | 0 |
import doctest
from collections import deque
import numpy as np
class _a :
"""simple docstring"""
def __init__( self ) -> None:
UpperCamelCase_ = [2, 1, 2, -1]
UpperCamelCase_ = [1, 2, 3, 4]
def _UpperCAmelCase (... | 23 |
def a__ ( A__ = 5_0_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set()
SCREAMING_SNAKE_CASE_ : Optional[int] = int((limit - 2_4) ** (1 / 2) )
SCREAMING_SNAKE_CASE_ : Dict = set(range(3, prime_square_limit + 1, 2 ) )
... | 101 | 0 |
'''simple docstring'''
UpperCAmelCase_ : 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
'''
... | 24 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : Any = [
'encoder.version',
'decoder.version',
'model.encoder.version',
... | 101 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class _UpperCamelCase ( __A )... | 25 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase__ : Optional[int] =0B1011_0011_1110_1100_1001_0000_0111_... | 101 | 0 |
'''simple docstring'''
from torch import nn
def _a ( _lowerCamelCase ) -> Tuple:
"""simple docstring"""
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
... | 26 |
def a__ ( A__, A__ ):
def get_matched_characters(A__, A__ ) -> str:
SCREAMING_SNAKE_CASE_ : Dict = []
SCREAMING_SNAKE_CASE_ : Any = min(len(_stra ), len(_stra ) ) // 2
for i, l in enumerate(_stra ):
SCREAMIN... | 101 | 0 |
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
_A = 0
# if input_string is "aba" than new_input_string become "a|b|a"
_A = ''
_A = ''
# append each character + "|" in new_string f... | 27 |
from __future__ import annotations
lowerCAmelCase__ : Union[str, Any] =[
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def a__ ( A__, A__, A__, A__, A__, ):
SCREAMING_SNAKE_CASE_ : List[Any] = ... | 101 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoMo... | 28 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'microsoft/git-base': 'https://huggingface.co/mi... | 101 | 0 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowerCamelCase ( lowerCAmelCase , unittest.TestCase ):
a__: Optional[Any] ... | 29 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 101 | 0 |
import sys
def lowerCamelCase__ ( _lowercase ):
'''simple docstring'''
UpperCAmelCase_ : List[Any] = len(_lowercase )
UpperCAmelCase_ : Tuple = [[0 for x in range(_lowercase )] for x in range(_lowercase )]
UpperCAmelCase_ : Union[str, Any] = [[... | 30 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : str ={
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 101 | 0 |
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...test_tokenization_common i... | 31 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAM... | 101 | 0 |
from __future__ import annotations
def A__ ( SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float ) -> float:
"""simple docstring"""
if days_between_payments <= 0:
raise ValueError('''days_between_pay... | 32 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 101 | 0 |
from collections.abc import Sequence
from queue import Queue
class __magic_name__ :
'''simple docstring'''
def __init__( self:str , _a:List[Any] , _a:Optional[Any] , _a:List[Any] , _a:Dict=None , _a:List[Any]=None ):
snake_case__ = s... | 33 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 101 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {'configuration_opt': ['OPT_PRETRAINED_... | 34 |
from ...processing_utils import ProcessorMixin
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """WhisperFeatureExtractor"""
_UpperCAmelCase = """WhisperTokenizer"""
de... | 101 | 0 |
def a ( A__ ) -> str:
'''simple docstring'''
return "".join([hex(A__ )[2:].zfill(2 ).upper() for byte in list(A__ )] )
def a ( A__ ) -> bytes:
'''simple docstring'''
if (len(A__ ) % 2) != 0:
raise ValueE... | 35 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 101 | 0 |
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditionalGeneration, BartTokenizer... | 36 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase (__SCREAMING_SNAKE_CASE ):
... | 101 | 0 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils import Regr... | 37 |
# 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 re... | 101 | 0 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForS... | 38 |
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__":
lowerCAmelCase__ : Optional[int] ='%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('S... | 101 | 0 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase_ = logging.getLogger(__name__)
def __SCREAMING_SNAKE_CASE ():
snake_case_ = argparse.ArgumentParser(
description='''Pre... | 39 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import ... | 101 | 0 |
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