code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> str:
'''simple docstring'''
stooge(SCREAMING_SNAKE_CASE_ , 0 , len(SCREAMING_SNAKE_CASE_ ) - 1 )
return arr
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_C... | 68 |
import warnings
from functools import wraps
from typing import Callable
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Callable ) -> Callable:
'''simple docstring'''
@wraps(SCREAMING_SNAKE_CASE_ )
def _inner_fn(*SCREAMING_SNAKE_CASE_: int , **SCREAMING_SNA... | 68 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 68 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
ge... | 68 | 1 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class a__ ( nn.Module ):
"""simple docstring"""
__lowerCamelCase = 42
__lowerCamelCase = jnp.floataa
def UpperCamelCase ( self ) -> Any:
'''simple docstring'''
A__ ... | 68 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTest... | 68 | 1 |
from ..utils import DummyObject, requires_backends
class a__ ( metaclass=snake_case ):
"""simple docstring"""
__lowerCamelCase = ['note_seq']
def __init__( self , *lowercase , **lowercase ) -> List[str]:
'''simple docstring'''
requi... | 68 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENA... | 68 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase__ = {
"""configuration_roc_bert""": ["""ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RoCBertConfig"""],
"""tokenization_roc_bert""": ["... | 68 |
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_CACHE,
WEIGHTS_NAME,
cached_file,
get_file... | 68 | 1 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple ) -> Union[str, Any]:
'''simple docstring'''
A__ = SwinConfig(im... | 68 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.test... | 68 | 1 |
from ..utils import DummyObject, requires_backends
class a__ ( metaclass=snake_case ):
"""simple docstring"""
__lowerCamelCase = ['transformers', 'torch', 'note_seq']
def __init__( self , *lowercase , **lowercase ) -> Any:
'''simple docstring'''... | 68 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
lowerCAmelCase__ = logging.getLogger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self ... | 68 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@require_torch
class a__ ... | 68 |
import random
class a__ :
"""simple docstring"""
@staticmethod
def UpperCamelCase ( lowercase ) -> tuple[list[int], list[int]]:
'''simple docstring'''
A__ = [ord(lowercase ) for i in text]
A__ = []
A__ = []
for i in pla... | 68 | 1 |
import unittest
import numpy as np
from datasets import load_dataset
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, prepare_image_inputs
if is_t... | 68 |
def lowerCAmelCase__ ( ) -> Any:
'''simple docstring'''
for n in range(1 , 1_0_0_0_0_0_0 ):
yield n * (n + 1) // 2
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple ) -> Any:
'''simple docstring'''
A__ = 1
A__ ... | 68 | 1 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> None:
... | 68 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowerCAmelCase__ = get_tests_dir(... | 68 | 1 |
lowerCAmelCase__ = 0 # The first color of the flag.
lowerCAmelCase__ = 1 # The second color of the flag.
lowerCAmelCase__ = 2 # The third color of the flag.
lowerCAmelCase__ = (red, white, blue)
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: li... | 68 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> list:
'''simple docstring'''
A__ = int(SCREAMING_SNAKE_CASE_ )
if n_element < 1:
A__ = ValueError("a should be a positive number" )
raise my_error
A__ = [1]
A__ , A__ ... | 68 | 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,
blenderbot,
blenderbo... | 68 |
import copy
import random
from transformers import CLIPTokenizer
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> Union[str, Any]:
'''simple docstring'''
super().__init__(*lowercase , **lowe... | 68 | 1 |
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = """\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.06268... | 68 |
from collections import deque
from math import floor
from random import random
from time import time
class a__ :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
A__ = {}
def UpperCamelCase ( self , lowercase ,... | 68 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class a__ ( unittest.TestCase ):
"""simple docstring"""
def Upp... | 68 |
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = """\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.06268... | 68 | 1 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
... | 68 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ... | 68 | 1 |
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTokenizer, HfArgumentParser, s... | 68 |
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,
blenderbot,
blenderbo... | 68 | 1 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeli... | 68 |
import string
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> None:
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
A__ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 68 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list[int] ) -> int:
'''simple docstring'''
if not numbers:
return 0
if not isinstance(SCREAMING_SNAKE_CASE_ , (list, tuple) ) or not all(
isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ... | 68 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_common import To... | 68 | 1 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class a__ ( unittest.TestCase ):
"""simple docstring"""
__lowerCamelCase = JukeboxTokenizer
__lowerCamelCase = {
'artist': 'Zac Brown Band',
... | 68 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ) -> List[str]:
'''simple docstring'''
A__ =... | 68 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowerCAmelCase__ = {"""tokenization_wav2vec2_phoneme""": ["""Wav2Vec2PhonemeCTCTokenizer"""]}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
lowerCAmelCase__ = ... | 68 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ... | 68 | 1 |
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_CACHE,
WEIGHTS_NAME,
cached_file,
get_file... | 68 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnxCon... | 68 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json... | 68 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""abeja/gpt-neox-japanese-2.7b""": """https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json""",
}
class a_... | 68 | 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__ = [
"""Prosecutor: \"No videos were used in the crash investigation\" German papers say they saw a cell phone video of the... | 68 |
import warnings
from functools import wraps
from typing import Callable
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Callable ) -> Callable:
'''simple docstring'''
@wraps(SCREAMING_SNAKE_CASE_ )
def _inner_fn(*SCREAMING_SNAKE_CASE_: int , **SCREAMING_SNA... | 68 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}
class a__ (... | 68 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
ge... | 68 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 68 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTest... | 68 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: Any , SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: Any , SCREAMING_SNAKE_CASE_: Any , SCREAMING_SNAKE_CASE_: str ) -> int:
'''simple docstring'''
... | 68 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENA... | 68 | 1 |
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
lowerCAmelCase__ = datasets.logging.get_logger(__name__)
lowerCAmelCase__ = """\
@inproceedings{bleurt,
title={BLEURT: Learning Robust Metrics for Text Generation},
author=... | 68 |
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_CACHE,
WEIGHTS_NAME,
cached_file,
get_file... | 68 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple , SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_: List[str] , SCREAMING_SNAKE_CASE_: List[str] ) -> Dict:
'''simple docstring'''
A__ = [False] * len(SCREAMING_SNAKE_CASE_ )
... | 68 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.test... | 68 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json""",... | 68 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
lowerCAmelCase__ = logging.getLogger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self ... | 68 | 1 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
lowerCAmelCase__... | 68 |
import random
class a__ :
"""simple docstring"""
@staticmethod
def UpperCamelCase ( lowercase ) -> tuple[list[int], list[int]]:
'''simple docstring'''
A__ = [ord(lowercase ) for i in text]
A__ = []
A__ = []
for i in pla... | 68 | 1 |
from __future__ import annotations
lowerCAmelCase__ = 1.6_021e-19 # units = C
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: float , SCREAMING_SNAKE_CASE_: float , SCREAMING_SNAKE_CASE_: float , ) -> tuple[str, float]:
'''simple docstring'''
... | 68 |
def lowerCAmelCase__ ( ) -> Any:
'''simple docstring'''
for n in range(1 , 1_0_0_0_0_0_0 ):
yield n * (n + 1) // 2
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple ) -> Any:
'''simple docstring'''
A__ = 1
A__ ... | 68 | 1 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMix... | 68 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowerCAmelCase__ = get_tests_dir(... | 68 | 1 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Option... | 68 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> list:
'''simple docstring'''
A__ = int(SCREAMING_SNAKE_CASE_ )
if n_element < 1:
A__ = ValueError("a should be a positive number" )
raise my_error
A__ = [1]
A__ , A__ ... | 68 | 1 |
def lowerCAmelCase__ ( ) -> List[str]:
'''simple docstring'''
A__ = [3_1, 2_8, 3_1, 3_0, 3_1, 3_0, 3_1, 3_1, 3_0, 3_1, 3_0, 3_1]
A__ = 6
A__ = 1
A__ = 1_9_0_1
A__ = 0
while year < 2_0_0_1:
day += 7
if (year % 4 == 0 and y... | 68 |
import copy
import random
from transformers import CLIPTokenizer
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> Union[str, Any]:
'''simple docstring'''
super().__init__(*lowercase , **lowe... | 68 | 1 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Dataset , SCREAMING_SNAKE_CASE_: Dict[str, str] ) -> ... | 68 |
from collections import deque
from math import floor
from random import random
from time import time
class a__ :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
A__ = {}
def UpperCamelCase ( self , lowercase ,... | 68 | 1 |
from __future__ import annotations
lowerCAmelCase__ = list[list[int]]
# assigning initial values to the grid
lowerCAmelCase__ = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, 0,... | 68 |
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = """\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.06268... | 68 | 1 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
lowerCAmelCase__ = """__DUMMY_TRANSFORMERS_USER__"""
lowerCAmelCase__ = """Dummy User"""
lowerCAmelCase__ = """hf_hZEmno... | 68 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ... | 68 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""facebook/timesformer""": """https://huggingface.co/facebook/timesformer/resolve/main/config.json""",
}
class a__ ( snake_ca... | 68 |
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,
blenderbot,
blenderbo... | 68 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""facebook/wav2vec2-base-960h""": """https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main... | 68 |
import string
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> None:
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
A__ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 68 | 1 |
from ...processing_utils import ProcessorMixin
class a__ ( snake_case ):
"""simple docstring"""
__lowerCamelCase = 'WhisperFeatureExtractor'
__lowerCamelCase = 'WhisperTokenizer'
def __init__( self , lowercase , lowercase ) -> Dict:
... | 68 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_common import To... | 68 | 1 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert ... | 68 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ) -> List[str]:
'''simple docstring'''
A__ =... | 68 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, t... | 68 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ... | 68 | 1 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 68 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnxCon... | 68 | 1 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_common import To... | 68 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""abeja/gpt-neox-japanese-2.7b""": """https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json""",
}
class a_... | 68 | 1 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: bool = True , *SCREAMING_SNAKE_CASE_: Any , **SCREAMING_SNAKE_CASE_: Any ) -> int:
... | 68 |
import warnings
from functools import wraps
from typing import Callable
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Callable ) -> Callable:
'''simple docstring'''
@wraps(SCREAMING_SNAKE_CASE_ )
def _inner_fn(*SCREAMING_SNAKE_CASE_: int , **SCREAMING_SNA... | 68 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 68 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
ge... | 68 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list[list[int]] ) -> int:
'''simple docstring'''
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in r... | 68 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTest... | 68 | 1 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokeni... | 68 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENA... | 68 | 1 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
lowerCAmelCase__ = logging.getLogger(__name_... | 68 |
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_CACHE,
WEIGHTS_NAME,
cached_file,
get_file... | 68 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
# See all GLPN models at ht... | 68 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.test... | 68 | 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 ConfigTester
from ..... | 68 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
lowerCAmelCase__ = logging.getLogger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self ... | 68 | 1 |
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class a__ ( snake_case , unittest.TestCase ):
"""simple docstring"""
__lowerCamelCase ... | 68 |
import random
class a__ :
"""simple docstring"""
@staticmethod
def UpperCamelCase ( lowercase ) -> tuple[list[int], list[int]]:
'''simple docstring'''
A__ = [ord(lowercase ) for i in text]
A__ = []
A__ = []
for i in pla... | 68 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 68 |
def lowerCAmelCase__ ( ) -> Any:
'''simple docstring'''
for n in range(1 , 1_0_0_0_0_0_0 ):
yield n * (n + 1) // 2
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple ) -> Any:
'''simple docstring'''
A__ = 1
A__ ... | 68 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: int ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(1 ) != 0 )
def lowerCAmelCase__ ( ) -> None:
'''simple docstring'''
assert ... | 68 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowerCAmelCase__ = get_tests_dir(... | 68 | 1 |
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin ... | 68 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> list:
'''simple docstring'''
A__ = int(SCREAMING_SNAKE_CASE_ )
if n_element < 1:
A__ = ValueError("a should be a positive number" )
raise my_error
A__ = [1]
A__ , A__ ... | 68 | 1 |
import copy
import random
from transformers import CLIPTokenizer
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> Union[str, Any]:
'''simple docstring'''
super().__init__(*lowercase , **lowe... | 68 |
import copy
import random
from transformers import CLIPTokenizer
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> Union[str, Any]:
'''simple docstring'''
super().__init__(*lowercase , **lowe... | 68 | 1 |
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy as np
from .import_utils impo... | 68 |
from collections import deque
from math import floor
from random import random
from time import time
class a__ :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
A__ = {}
def UpperCamelCase ( self , lowercase ,... | 68 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""andreasmadsen/efficient_mlm_m0.40""":... | 68 |
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = """\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.06268... | 68 | 1 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowerCAmelCase__ = get_tests_dir(... | 68 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ... | 68 | 1 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowerCAmelCase__ = None
try:
import msvcrt
except ImportError:
lowerCAmelCase__ = None
try:
import fcntl
except ImportError:
lowerCAmelCase__ = None
# Backward compatibilit... | 68 |
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,
blenderbot,
blenderbo... | 68 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ... | 68 |
import string
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> None:
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
A__ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 68 | 1 |
from __future__ import annotations
import os
from typing import Any
import requests
lowerCAmelCase__ = """https://api.github.com"""
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowerCAmelCase__ = BASE_URL + """/user"""
# https://githu... | 68 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_common import To... | 68 | 1 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 68 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ) -> List[str]:
'''simple docstring'''
A__ =... | 68 | 1 |
import qiskit
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: int ) -> qiskit.result.counts.Counts:
'''simple docstring'''
A__ = qiskit.Aer.get_backend("aer_simulator" )
# Create a Quantum Circuit acting on the q register
... | 68 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ... | 68 | 1 |
from functools import reduce
lowerCAmelCase__ = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""668... | 68 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnxCon... | 68 | 1 |
from collections import deque
from math import floor
from random import random
from time import time
class a__ :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
A__ = {}
def UpperCamelCase ( self , lowercase ,... | 68 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""abeja/gpt-neox-japanese-2.7b""": """https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json""",
}
class a_... | 68 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, Dis... | 68 |
import warnings
from functools import wraps
from typing import Callable
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Callable ) -> Callable:
'''simple docstring'''
@wraps(SCREAMING_SNAKE_CASE_ )
def _inner_fn(*SCREAMING_SNAKE_CASE_: int , **SCREAMING_SNA... | 68 | 1 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ... | 68 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
ge... | 68 | 1 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test... | 68 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTest... | 68 | 1 |
from math import log
from scipy.constants import Boltzmann, physical_constants
lowerCAmelCase__ = 3_0_0 # TEMPERATURE (unit = K)
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: float , SCREAMING_SNAKE_CASE_: float , SCREAMING_SNAKE_CASE_: float , ) -> floa... | 68 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENA... | 68 | 1 |
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
... | 68 |
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_CACHE,
WEIGHTS_NAME,
cached_file,
get_file... | 68 | 1 |
import argparse
import os
import re
import packaging.version
lowerCAmelCase__ = """examples/"""
lowerCAmelCase__ = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.compile(R"""^__vers... | 68 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.test... | 68 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: int ) -> str:
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
raise ValueError("iterations must be defined as integers" )
if ... | 68 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
lowerCAmelCase__ = logging.getLogger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self ... | 68 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[Any] ) -> Dict:
'''simple docstring'''
A__ = []
A__ = []
A__ = {
"^": 3,
"*": 2,
"/": 2,
"%": 2,
"+": 1,
"-": 1,
} # Priority of each operator
... | 68 |
import random
class a__ :
"""simple docstring"""
@staticmethod
def UpperCamelCase ( lowercase ) -> tuple[list[int], list[int]]:
'''simple docstring'''
A__ = [ord(lowercase ) for i in text]
A__ = []
A__ = []
for i in pla... | 68 | 1 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ) -> List[str]:
'''simple docstring'''
A__ =... | 68 |
def lowerCAmelCase__ ( ) -> Any:
'''simple docstring'''
for n in range(1 , 1_0_0_0_0_0_0 ):
yield n * (n + 1) // 2
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple ) -> Any:
'''simple docstring'''
A__ = 1
A__ ... | 68 | 1 |
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: int , SCREAMING_SNAKE_CASE_: float = 1 / sqrt(2 ) ) -> IIRFilter:
'''simple docstring'''
... | 68 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowerCAmelCase__ = get_tests_dir(... | 68 | 1 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
ge... | 68 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> list:
'''simple docstring'''
A__ = int(SCREAMING_SNAKE_CASE_ )
if n_element < 1:
A__ = ValueError("a should be a positive number" )
raise my_error
A__ = [1]
A__ , A__ ... | 68 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: list[int] , SCREAMING_SNAKE_CASE_: str ) -> list[int]:
'''simple docstring'''
A__ = int(SCREAMING_SNAKE_CASE_ )
# Initialize Result
A__ = []
# Traverse through all denomination
for denomin... | 68 |
import copy
import random
from transformers import CLIPTokenizer
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> Union[str, Any]:
'''simple docstring'''
super().__init__(*lowercase , **lowe... | 68 | 1 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import Config... | 68 |
from collections import deque
from math import floor
from random import random
from time import time
class a__ :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
A__ = {}
def UpperCamelCase ( self , lowercase ,... | 68 | 1 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
FlaxForcedBOSTokenLogitsPr... | 68 |
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = """\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.06268... | 68 | 1 |
from typing import List
import numpy as np
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: dict ) -> int:
'''simple docstring'''
A__ = {key: len(SCREAMING_SNAKE_CASE_ ) for key, value in gen_kwargs.items() if isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_C... | 68 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ... | 68 | 1 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""huggingface/autoformer-tourism-monthly""": """https://huggingface.co/huggingface/autoformer-touri... | 68 |
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,
blenderbot,
blenderbo... | 68 | 1 |
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 a__ ( snake_case ):
"""simple docstring"""
__lowe... | 68 |
import string
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> None:
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
A__ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 68 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 68 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_common import To... | 68 | 1 |
def lowerCAmelCase__ ( ) -> Any:
'''simple docstring'''
for n in range(1 , 1_0_0_0_0_0_0 ):
yield n * (n + 1) // 2
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple ) -> Any:
'''simple docstring'''
A__ = 1
A__ ... | 68 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: Optional[int] , SCREAMING_SNAKE_CASE_: int ) -> List[str]:
'''simple docstring'''
A__ =... | 68 | 1 |
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.test... | 68 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
lowerCAmelCase__ = logging.get_logger(__name__)
class a__ ... | 68 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[Any]=2_8_1_2_3 ) -> List[str]:
'''simple docstring'''
A__ = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1... | 68 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnxCon... | 68 | 1 |
lowerCAmelCase__ = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],
"""G""": ["""C"""],
}
def lowerCAmelCase__ ( SCREA... | 68 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""abeja/gpt-neox-japanese-2.7b""": """https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json""",
}
class a_... | 68 | 1 |
import inspect
import unittest
from transformers import ConvNextConfig
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_backbone_common import BackboneTesterMixin
from ...test... | 68 |
import warnings
from functools import wraps
from typing import Callable
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Callable ) -> Callable:
'''simple docstring'''
@wraps(SCREAMING_SNAKE_CASE_ )
def _inner_fn(*SCREAMING_SNAKE_CASE_: int , **SCREAMING_SNA... | 68 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: List[str] ) -> ... | 68 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
ge... | 68 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 68 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTest... | 68 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ = {
"""configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
"""tokenization_tapas""": ["""TapasTokenizer"""... | 68 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENA... | 68 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class a__ ( unittest.TestCase ):
"""simple docstring"""
... | 68 |
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_CACHE,
WEIGHTS_NAME,
cached_file,
get_file... | 68 | 1 |
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
lowerCAmelCase__ = collections.namedtuple("""_Datasets""", ["""train""",... | 68 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.test... | 68 | 1 |
import string
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> None:
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
A__ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 68 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
lowerCAmelCase__ = logging.getLogger(__name__)
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self ... | 68 | 1 |
from collections.abc import Callable
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Callable[[float], float] , SCREAMING_SNAKE_CASE_: float , SCREAMING_SNAKE_CASE_: float ) -> float:
'''simple docstring'''
A__ = a
A__ = b
if function(SC... | 68 |
import random
class a__ :
"""simple docstring"""
@staticmethod
def UpperCamelCase ( lowercase ) -> tuple[list[int], list[int]]:
'''simple docstring'''
A__ = [ord(lowercase ) for i in text]
A__ = []
A__ = []
for i in pla... | 68 | 1 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import logging
fr... | 68 |
def lowerCAmelCase__ ( ) -> Any:
'''simple docstring'''
for n in range(1 , 1_0_0_0_0_0_0 ):
yield n * (n + 1) // 2
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Tuple ) -> Any:
'''simple docstring'''
A__ = 1
A__ ... | 68 | 1 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a_... | 68 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowerCAmelCase__ = get_tests_dir(... | 68 | 1 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <host> --key_path <key_... | 68 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int ) -> list:
'''simple docstring'''
A__ = int(SCREAMING_SNAKE_CASE_ )
if n_element < 1:
A__ = ValueError("a should be a positive number" )
raise my_error
A__ = [1]
A__ , A__ ... | 68 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
@flax.struct.dataclass
class ... | 68 |
import copy
import random
from transformers import CLIPTokenizer
class a__ ( snake_case ):
"""simple docstring"""
def __init__( self , *lowercase , **lowercase ) -> Union[str, Any]:
'''simple docstring'''
super().__init__(*lowercase , **lowe... | 68 | 1 |
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