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 |
|---|---|---|---|---|
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCAmelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''Search: ''')))
print('''Go... | 5 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from transfor... | 5 | 1 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 5 |
import requests
from bsa import BeautifulSoup
def UpperCAmelCase_ ( __snake_case = "https://www.worldometers.info/coronavirus" ) -> dict:
"""simple docstring"""
_lowercase =BeautifulSoup(requests.get(__snake_case ).text , '''html.parser''' )
_lowerc... | 5 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class lowe... | 5 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
UpperCAmelCase__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''convert''... | 5 | 1 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
fro... | 5 |
def UpperCAmelCase_ ( __snake_case ) -> str:
"""simple docstring"""
_lowercase =0
# if input_string is "aba" than new_input_string become "a|b|a"
_lowercase =''''''
_lowercase =''''''
# append each character + "|" in new_string for range(0... | 5 | 1 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_s... | 5 |
from math import isqrt
def UpperCAmelCase_ ( __snake_case ) -> list[int]:
"""simple docstring"""
_lowercase =[True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , __snake_case , ... | 5 | 1 |
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from fla... | 5 |
UpperCAmelCase__ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',... | 5 | 1 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError('''To use the rich extension, install rich with `pip install rich`''')
| 5 |
from typing import Any
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> list:
"""simple docstring"""
_validation(
__snake_case , __snake_case , __snake_case , ... | 5 | 1 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowerCamelCase__ ( nn.Module):
def __init__(self , UpperCAmelCase = 1_6 , UpperCAmelCase = 8_8 , UpperCAmelCase = None , UpperCAmelCase ... | 5 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
# TODO Update this
UpperCAmelCase__ = {
'''facebook/esm-1b''': '''https://huggingface.co/fac... | 5 | 1 |
from typing import Any
import numpy as np
def UpperCAmelCase_ ( __snake_case ) -> bool:
"""simple docstring"""
return np.array_equal(__snake_case , matrix.conjugate().T )
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Any:
... | 5 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from t... | 5 | 1 |
from collections import defaultdict
from math import ceil, sqrt
def UpperCAmelCase_ ( __snake_case = 1000000 , __snake_case = 10 ) -> int:
"""simple docstring"""
_lowercase =defaultdict(__snake_case )
for outer_width in range(3 , (t_limit // 4)... | 5 |
UpperCAmelCase__ = 8.31_44_62 # Unit - J mol-1 K-1
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case ) -> float:
"""simple docstring"""
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter positive value.'... | 5 | 1 |
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def UpperCAmelCase_ ( ) -> Optional[... | 5 |
from __future__ import annotations
from collections.abc import Callable
UpperCAmelCase__ = list[list[float | int]]
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Matrix:
"""simple docstring"""
_lowercase =len(__snake_case )
_lowercase ... | 5 | 1 |
# flake8: noqa
# Lint as: python3
UpperCAmelCase__ = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disable_progress_ba... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase__ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['''XLMToke... | 5 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_utils... | 5 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 5 | 1 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case ) -> List[str]:
"""simple docstring"""
_lowercase =('''dense.weight... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if not is_torch_available():
raise Opti... | 5 | 1 |
import logging
from transformers import PretrainedConfig
UpperCAmelCase__ = logging.getLogger(__name__)
UpperCAmelCase__ = {
'''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json''',
}
clas... | 5 |
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> List[Any]:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__snake_case , int(b / 2 ) ) * actual_power(__snake_case , int(b / 2 ) )
else:
r... | 5 | 1 |
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ... | 5 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowerCamelCase__ ( nn.Module):
def __init__(self , UpperCAmelCase = 1_6 , UpperCAmelCase = 8_8 , UpperCAmelCase = None , UpperCAmelCase ... | 5 | 1 |
from typing import Any
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> list:
"""simple docstring"""
_validation(
__snake_case , __snake_case , __snake_case , ... | 5 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase ) -> Any:
_lowercase =str(id_ )
_lowercase =None
_lowercase =None
_lowercase ... | 5 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase__ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['''XLMToke... | 5 |
# flake8: noqa
# Lint as: python3
UpperCAmelCase__ = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disable_progress_ba... | 5 | 1 |
# Copyright 2022 The HuggingFace Team and The OpenBMB 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
#
# Unle... | 5 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json''',
... | 5 | 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,
)
UpperCAmelCase__ = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ['''paws''', ... | 5 |
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from fla... | 5 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyNotAvailable()
excep... | 5 |
import comet # From: unbabel-comet
import torch
import datasets
UpperCAmelCase__ = datasets.logging.get_logger(__name__)
UpperCAmelCase__ = '''\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},
title = {Unbabel\... | 5 | 1 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
UpperCAmelCase__ = ... | 5 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class lowe... | 5 | 1 |
def UpperCAmelCase_ ( __snake_case ) -> str:
"""simple docstring"""
_lowercase =0
# if input_string is "aba" than new_input_string become "a|b|a"
_lowercase =''''''
_lowercase =''''''
# append each character + "|" in new_string for range(0... | 5 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from transfor... | 5 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 5 |
import requests
from bsa import BeautifulSoup
def UpperCAmelCase_ ( __snake_case = "https://www.worldometers.info/coronavirus" ) -> dict:
"""simple docstring"""
_lowercase =BeautifulSoup(requests.get(__snake_case ).text , '''html.parser''' )
_lowerc... | 5 | 1 |
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
MusicgenProcessor,
... | 5 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
UpperCAmelCase__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''convert''... | 5 | 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
UpperCAmelCase__ = logging.get_logger(__name__)
class ... | 5 |
def UpperCAmelCase_ ( __snake_case ) -> str:
"""simple docstring"""
_lowercase =0
# if input_string is "aba" than new_input_string become "a|b|a"
_lowercase =''''''
_lowercase =''''''
# append each character + "|" in new_string for range(0... | 5 | 1 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''post_extract_proj''': '''feature_projection.... | 5 |
from math import isqrt
def UpperCAmelCase_ ( __snake_case ) -> list[int]:
"""simple docstring"""
_lowercase =[True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , __snake_case , ... | 5 | 1 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
UpperCAmelCase__ = TypeVar('''T''')
UpperCAmelCase__ = Union[List[T], Tuple[T, ...]]
UpperCAmelCase__ = Union[T, List[T], Dict[str, T]]
UpperCAmelCase__ = Union[str, bytes, os.PathLike]
| 5 |
UpperCAmelCase__ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',... | 5 | 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_softmax
if is_torch_a... | 5 |
from typing import Any
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> list:
"""simple docstring"""
_validation(
__snake_case , __snake_case , __snake_case , ... | 5 | 1 |
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
UpperCAmelCase__ = logging.ge... | 5 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
# TODO Update this
UpperCAmelCase__ = {
'''facebook/esm-1b''': '''https://huggingface.co/fac... | 5 | 1 |
def UpperCAmelCase_ ( ) -> Any:
"""simple docstring"""
_lowercase =0
for i in range(1 , 1001 ):
total += i**i
return str(__snake_case )[-10:]
if __name__ == "__main__":
print(solution())
| 5 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from t... | 5 | 1 |
UpperCAmelCase__ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',... | 5 |
UpperCAmelCase__ = 8.31_44_62 # Unit - J mol-1 K-1
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case ) -> float:
"""simple docstring"""
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter positive value.'... | 5 | 1 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json''',
#... | 5 |
from __future__ import annotations
from collections.abc import Callable
UpperCAmelCase__ = list[list[float | int]]
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Matrix:
"""simple docstring"""
_lowercase =len(__snake_case )
_lowercase ... | 5 | 1 |
from collections import deque
def UpperCAmelCase_ ( __snake_case ) -> List[Any]:
"""simple docstring"""
_lowercase =len(__snake_case )
_lowercase =deque()
_lowercase =[False for _ in range(__snake_case )]
_lowercase =[-1... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase__ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['''XLMToke... | 5 | 1 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
... | 5 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 5 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}
class lowerCa... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if not is_torch_available():
raise Opti... | 5 | 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 import UNCONDITIO... | 5 |
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> List[Any]:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__snake_case , int(b / 2 ) ) * actual_power(__snake_case , int(b / 2 ) )
else:
r... | 5 | 1 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class lowerCamelCase__ :
def __A (self , UpperCAmelCase ) -> Dict:
raise NotImplementedError()
def __A (self ... | 5 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowerCamelCase__ ( nn.Module):
def __init__(self , UpperCAmelCase = 1_6 , UpperCAmelCase = 8_8 , UpperCAmelCase = None , UpperCAmelCase ... | 5 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''microsoft/focalnet-tiny''': '''https://... | 5 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase ) -> Any:
_lowercase =str(id_ )
_lowercase =None
_lowercase =None
_lowercase ... | 5 | 1 |
UpperCAmelCase__ = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_0000)]
def UpperCAmelCase_ ( __snake_case ) -> int:
"""simple docstring"""
_lowercase =0
while number:
# Increased Speed Slightly by checking every 5 digits together.
sum_of_d... | 5 |
# flake8: noqa
# Lint as: python3
UpperCAmelCase__ = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disable_progress_ba... | 5 | 1 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
UpperCAmelCase__ = Mapping[str, np.ndarray]
UpperCAmelCase__ = Mapping[str, Any] # Is a nested dict.
UpperCAmelCase__ ... | 5 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json''',
... | 5 | 1 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
UpperCAmelCase__ = logging.get_logger(__name__)
class lowerCamelCase__ ( lowerCAmelCase):
def __init__(self , *UpperCAmelCase , **UpperCAmelCase ) ... | 5 |
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from fla... | 5 | 1 |
from collections.abc import Generator
from math import sin
def UpperCAmelCase_ ( __snake_case ) -> bytes:
"""simple docstring"""
if len(__snake_case ) != 32:
raise ValueError('''Input must be of length 32''' )
_lowercase =b''''''
for i in [3, 2, 1, 0]:
... | 5 |
import comet # From: unbabel-comet
import torch
import datasets
UpperCAmelCase__ = datasets.logging.get_logger(__name__)
UpperCAmelCase__ = '''\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},
title = {Unbabel\... | 5 | 1 |
from __future__ import annotations
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> None:
"""simple docstring"""
_lowercase =len(__snake_case )
# If row is equal to the ... | 5 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class lowe... | 5 | 1 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase ) -> Any:
_lowercase =str(id_ )
_lowercase =None
_lowercase =None
_lowercase ... | 5 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from transfor... | 5 | 1 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case ) -> List[str]:
... | 5 |
import requests
from bsa import BeautifulSoup
def UpperCAmelCase_ ( __snake_case = "https://www.worldometers.info/coronavirus" ) -> dict:
"""simple docstring"""
_lowercase =BeautifulSoup(requests.get(__snake_case ).text , '''html.parser''' )
_lowerc... | 5 | 1 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
import sql... | 5 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
UpperCAmelCase__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''convert''... | 5 | 1 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_... | 5 |
def UpperCAmelCase_ ( __snake_case ) -> str:
"""simple docstring"""
_lowercase =0
# if input_string is "aba" than new_input_string become "a|b|a"
_lowercase =''''''
_lowercase =''''''
# append each character + "|" in new_string for range(0... | 5 | 1 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Prop... | 5 |
from math import isqrt
def UpperCAmelCase_ ( __snake_case ) -> list[int]:
"""simple docstring"""
_lowercase =[True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , __snake_case , ... | 5 | 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 applic... | 5 |
UpperCAmelCase__ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',... | 5 | 1 |
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requ... | 5 |
from typing import Any
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> list:
"""simple docstring"""
_validation(
__snake_case , __snake_case , __snake_case , ... | 5 | 1 |
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__snake_case ) , __snake_case )
return number - int(__snake_case )
if __name__ == "__main__":
print(decimal_i... | 5 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
# TODO Update this
UpperCAmelCase__ = {
'''facebook/esm-1b''': '''https://huggingface.co/fac... | 5 | 1 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTester... | 5 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from t... | 5 | 1 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCAmelCase__ = '''src/... | 5 |
UpperCAmelCase__ = 8.31_44_62 # Unit - J mol-1 K-1
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case ) -> float:
"""simple docstring"""
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter positive value.'... | 5 | 1 |
def UpperCAmelCase_ ( __snake_case ) -> int:
"""simple docstring"""
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - ... | 5 |
from __future__ import annotations
from collections.abc import Callable
UpperCAmelCase__ = list[list[float | int]]
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Matrix:
"""simple docstring"""
_lowercase =len(__snake_case )
_lowercase ... | 5 | 1 |
import argparse
import struct
import unittest
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase ) -> None:
_lowercase =data
# Initialize hash values
_lowercase =[
0X6_a_0_9_e_6_6_7,
0Xb_b_6_7_a_e_8_5,
... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase__ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['''XLMToke... | 5 | 1 |
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mod... | 5 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 5 | 1 |
UpperCAmelCase__ = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
UpperCAmelCase__ = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case ) -> list[int]:
"""simple docstring"""
_low... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if not is_torch_available():
raise Opti... | 5 | 1 |
# Lint as: python3
import itertools
import os
import re
UpperCAmelCase__ = re.compile(R'''([A-Z]+)([A-Z][a-z])''')
UpperCAmelCase__ = re.compile(R'''([a-z\d])([A-Z])''')
UpperCAmelCase__ = re.compile(R'''(?<!_)_(?!_)''')
UpperCAmelCase__ = re.compile(R'''(_{2,})''')
UpperCAmel... | 5 |
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> List[Any]:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__snake_case , int(b / 2 ) ) * actual_power(__snake_case , int(b / 2 ) )
else:
r... | 5 | 1 |
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
UpperCAmelCase__ = '''src/transformers'''
UpperCAmelCase... | 5 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowerCamelCase__ ( nn.Module):
def __init__(self , UpperCAmelCase = 1_6 , UpperCAmelCase = 8_8 , UpperCAmelCase = None , UpperCAmelCase ... | 5 | 1 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
f... | 5 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase ) -> Any:
_lowercase =str(id_ )
_lowercase =None
_lowercase =None
_lowercase ... | 5 | 1 |
from __future__ import annotations
from collections.abc import Callable
UpperCAmelCase__ = list[list[float | int]]
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Matrix:
"""simple docstring"""
_lowercase =len(__snake_case )
_lowercase ... | 5 |
# flake8: noqa
# Lint as: python3
UpperCAmelCase__ = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disable_progress_ba... | 5 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if not is_torch_available():
raise Opti... | 5 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json''',
... | 5 | 1 |
import os
def UpperCAmelCase_ ( ) -> Union[str, Any]:
"""simple docstring"""
_lowercase =os.path.dirname(os.path.realpath(__snake_case ) )
_lowercase =os.path.join(__snake_case , '''triangle.txt''' )
with open(__snake_case ) as f:... | 5 |
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from fla... | 5 | 1 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
UpperCAmelCase__ = logging.get_logger(__name__)
class lowerCamelCase__ ( lowerCAmelCase):
def __init__(self , *UpperCAmelCase , **UpperCAmelCase ) -> Non... | 5 |
import comet # From: unbabel-comet
import torch
import datasets
UpperCAmelCase__ = datasets.logging.get_logger(__name__)
UpperCAmelCase__ = '''\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},
title = {Unbabel\... | 5 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase__ = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
'''Chi... | 5 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class lowe... | 5 | 1 |
from __future__ import annotations
UpperCAmelCase__ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> t... | 5 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from transfor... | 5 | 1 |
import qiskit
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> qiskit.result.counts.Counts:
"""simple docstring"""
_lowercase =qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
_lowercase ... | 5 |
import requests
from bsa import BeautifulSoup
def UpperCAmelCase_ ( __snake_case = "https://www.worldometers.info/coronavirus" ) -> dict:
"""simple docstring"""
_lowercase =BeautifulSoup(requests.get(__snake_case ).text , '''html.parser''' )
_lowerc... | 5 | 1 |
import os
# Precomputes a list of the 100 first triangular numbers
UpperCAmelCase__ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def UpperCAmelCase_ ( ) -> Tuple:
"""simple docstring"""
_lowercase =os.path.dirname(os.path.realpath(__snake_case ) )
... | 5 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
UpperCAmelCase__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''convert''... | 5 | 1 |
from ..utils import DummyObject, requires_backends
class lowerCamelCase__ ( metaclass=lowerCAmelCase):
SCREAMING_SNAKE_CASE__ = ['''flax''', '''transformers''']
def __init__(self , *UpperCAmelCase , **UpperCAmelCase ) -> int:
requires_backends... | 5 |
def UpperCAmelCase_ ( __snake_case ) -> str:
"""simple docstring"""
_lowercase =0
# if input_string is "aba" than new_input_string become "a|b|a"
_lowercase =''''''
_lowercase =''''''
# append each character + "|" in new_string for range(0... | 5 | 1 |
class lowerCamelCase__ :
def __init__(self ) -> Tuple:
_lowercase =''''''
_lowercase =''''''
_lowercase =[]
def __A (self , UpperCAmelCase , UpperCAmelCase ) -> int:
if m == -1:
r... | 5 |
from math import isqrt
def UpperCAmelCase_ ( __snake_case ) -> list[int]:
"""simple docstring"""
_lowercase =[True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , __snake_case , ... | 5 | 1 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = OrderedDict(
[
... | 5 |
UpperCAmelCase__ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',... | 5 | 1 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ... | 5 |
from typing import Any
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> list:
"""simple docstring"""
_validation(
__snake_case , __snake_case , __snake_case , ... | 5 | 1 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
UpperCAmelCase__ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf(), gbellmf(),... | 5 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
# TODO Update this
UpperCAmelCase__ = {
'''facebook/esm-1b''': '''https://huggingface.co/fac... | 5 | 1 |
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Any:
"""simple docstring"""
assert x is not None
assert y is not None
_lowercase =len(__snake_case )
_lowercase =len(__snake_case )
# declaring the array for storing the dp valu... | 5 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from t... | 5 | 1 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case ) -> Dict:
"""simple docstring"""
_lowercase =0
if start < end:
_lowercase =randint(__sna... | 5 |
UpperCAmelCase__ = 8.31_44_62 # Unit - J mol-1 K-1
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case ) -> float:
"""simple docstring"""
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter positive value.'... | 5 | 1 |
from torch import nn
def UpperCAmelCase_ ( __snake_case ) -> Any:
"""simple docstring"""
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(F"Unsupported activation func... | 5 |
from __future__ import annotations
from collections.abc import Callable
UpperCAmelCase__ = list[list[float | int]]
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Matrix:
"""simple docstring"""
_lowercase =len(__snake_case )
_lowercase ... | 5 | 1 |
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
'''The converted tokenizer will b... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase__ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['''XLMToke... | 5 | 1 |
import inspect
import unittest
from transformers import ViTMSNConfig
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_configuration_common import ConfigTester
from ...test_mo... | 5 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 5 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase__ = {
'''configuration_bert''': ['''BERT_PRE... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if not is_torch_available():
raise Opti... | 5 | 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, Optio... | 5 |
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> List[Any]:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__snake_case , int(b / 2 ) ) * actual_power(__snake_case , int(b / 2 ) )
else:
r... | 5 | 1 |
from __future__ import annotations
def UpperCAmelCase_ ( __snake_case ) -> list[int]:
"""simple docstring"""
if len(__snake_case ) == 0:
return array
_lowercase , _lowercase =min(__snake_case ), max(__snake_case )
# Compute the variables
_... | 5 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class lowerCamelCase__ ( nn.Module):
def __init__(self , UpperCAmelCase = 1_6 , UpperCAmelCase = 8_8 , UpperCAmelCase = None , UpperCAmelCase ... | 5 | 1 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
UpperCAmelCase__ = logging.get_logger(__name__)
class lowerCamelCase__ ( lowerCAmelCase):
def __init__(self , *UpperCAmelCase , **UpperCAmelCase ) -> N... | 5 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase ) -> Any:
_lowercase =str(id_ )
_lowercase =None
_lowercase =None
_lowercase ... | 5 | 1 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from t... | 5 |
# flake8: noqa
# Lint as: python3
UpperCAmelCase__ = [
'''VerificationMode''',
'''Version''',
'''disable_progress_bar''',
'''enable_progress_bar''',
'''is_progress_bar_enabled''',
'''experimental''',
]
from .info_utils import VerificationMode
from .logging import disable_progress_ba... | 5 | 1 |
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
UpperCAmelCase__ = 0b1_0_1_1_0_0_1_1_1_1_1_0_1_1_0_0_1_0_0_1_0_0_0_0_0_1_1_1_1_0_1_1_... | 5 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json''',
... | 5 | 1 |
def UpperCAmelCase_ ( __snake_case = 4000000 ) -> int:
"""simple docstring"""
_lowercase =[]
_lowercase , _lowercase =0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__snake_case )
_lowercase , _lowercase =b, a +... | 5 |
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from fla... | 5 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = '''▁'''
UpperCAmelCase__ ... | 5 |
import comet # From: unbabel-comet
import torch
import datasets
UpperCAmelCase__ = datasets.logging.get_logger(__name__)
UpperCAmelCase__ = '''\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},
title = {Unbabel\... | 5 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
'''configuration_git''': ['''GIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GitConfig''', '''GitVisionConfig'''],
'''processing_git''': ['''GitProcessor'''],
}
try... | 5 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class lowe... | 5 | 1 |
import os
def UpperCAmelCase_ ( __snake_case = "input.txt" ) -> int:
"""simple docstring"""
with open(os.path.join(os.path.dirname(__snake_case ) , __snake_case ) ) as input_file:
_lowercase =[
[int(__snake_case ) for element in lin... | 5 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from transfor... | 5 | 1 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
from ... import PreT... | 5 |
import requests
from bsa import BeautifulSoup
def UpperCAmelCase_ ( __snake_case = "https://www.worldometers.info/coronavirus" ) -> dict:
"""simple docstring"""
_lowercase =BeautifulSoup(requests.get(__snake_case ).text , '''html.parser''' )
_lowerc... | 5 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
'''facebook/data... | 5 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
UpperCAmelCase__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''convert''... | 5 | 1 |
import argparse
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, DistributedT... | 5 |
def UpperCAmelCase_ ( __snake_case ) -> str:
"""simple docstring"""
_lowercase =0
# if input_string is "aba" than new_input_string become "a|b|a"
_lowercase =''''''
_lowercase =''''''
# append each character + "|" in new_string for range(0... | 5 | 1 |
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
UpperCAm... | 5 |
from math import isqrt
def UpperCAmelCase_ ( __snake_case ) -> list[int]:
"""simple docstring"""
_lowercase =[True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , __snake_case , ... | 5 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ ... | 5 |
UpperCAmelCase__ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '''-.''',... | 5 | 1 |
from bisect import bisect
from itertools import accumulate
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case ) -> Optional[int]:
"""simple docstring"""
_lowercase =sorted(zip(__snake_case , __snake_case ... | 5 |
from typing import Any
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> list:
"""simple docstring"""
_validation(
__snake_case , __snake_case , __snake_case , ... | 5 | 1 |
from random import shuffle
import tensorflow as tf
from numpy import array
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Dict:
"""simple docstring"""
_lowercase =int(__snake_case )
assert noofclusters < len(__snake_case )
# Find out the ... | 5 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
# TODO Update this
UpperCAmelCase__ = {
'''facebook/esm-1b''': '''https://huggingface.co/fac... | 5 | 1 |
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> bool:
"""simple docstring"""
_lowercase =len(__snake_case )
_lowercase =len(__snake_case )
_lowercase =[[False for _ in range(m + 1 )] for _ in range(n + 1 )]
... | 5 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from t... | 5 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase__ = logging.get_logger(__name__)
class lowerCamelCase__ ( lowerCAmelCase , lowerC... | 5 |
UpperCAmelCase__ = 8.31_44_62 # Unit - J mol-1 K-1
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case ) -> float:
"""simple docstring"""
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter positive value.'... | 5 | 1 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import DPRConte... | 5 |
from __future__ import annotations
from collections.abc import Callable
UpperCAmelCase__ = list[list[float | int]]
def UpperCAmelCase_ ( __snake_case , __snake_case ) -> Matrix:
"""simple docstring"""
_lowercase =len(__snake_case )
_lowercase ... | 5 | 1 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase__ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['''XLMToke... | 5 | 1 |
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