code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : List[str] = logging.get_logger(__name__)
_lowercase : Optional[int] = {
"facebook/wav2vec2-base-960h": "https://huggingface.co/faceboo... | 30 | '''simple docstring'''
import argparse
_lowercase : Optional[int] = "docs/source/_static/js/custom.js"
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Dict:
with open(UpperCAmelCase__ , encoding="""utf-8""" , newline="""\n""" ) as f:
lower... | 30 | 1 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
_lowercase : Optional[int] = [
# tf -> hf
("/", "."),
("layer_", "layers."),
... | 30 | '''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
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 BackboneTest... | 30 | 1 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : Callable , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> np.array:
... | 30 | '''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase : Optional[Any] = [
"Prosecutor: \"No videos were used in the crash investigation\" German papers say th... | 30 | 1 |
'''simple docstring'''
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
... | 30 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"facebook/s2t-small-librispeech-asr": (
"https://huggingface.co/facebook/s2t-small... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( ) -> Any:
lowercase_ : Dict = 0
for i in range(1 , 1001 ):
total += i**i
return str(UpperCAmelCase__ )[-10:]
if __name__ == "__main__":
print(solution())
| 30 | '''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ... | 30 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
_lowercase : str = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}
try:... | 30 | '''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docst... | 30 | 1 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> str:
lowercase_ : int = [
"""encoder.version""",
... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 30 | 1 |
'''simple docstring'''
import math
def lowerCamelCase ( UpperCAmelCase__ : int ) -> bool:
assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and... | 30 | '''simple docstring'''
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("""dataset_size""" , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize("""input_in_memory_max_size""" , ["""default""", 0, 100 * 2**20, 900 * 2**20] ... | 30 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_lowercase : Optional[Any] = logging.get_logger(__name__)
class __magic_name__ ( _UpperCAmelCase):
def __init__( self : Any , *low... | 30 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer,... | 30 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
_lowercase : st... | 30 | '''simple docstring'''
from collections.abc import Callable
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : Callable , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> np.array:
... | 30 | 1 |
'''simple docstring'''
from __future__ import annotations
_lowercase : str = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
_lowercase : List[Any] = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def lowerCamelCase ( UpperCAmelCase__ : list[float... | 30 | '''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : float = 1 / sqrt(2 ) ) -> IIRFilter:
lowercase_ : str ... | 30 | 1 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (
... | 30 | '''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import ... | 30 | 1 |
'''simple docstring'''
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : Dict , UpperCAmelCase__ : Optional[Any] , UpperCAmelCase__ : str... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowercase : Dict = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
try:
... | 30 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Dict = logging.get_logger(__name__)
_lowercase : Tuple = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class __magic_name__ ( ... | 30 | '''simple docstring'''
_lowercase : int = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def lowerCamelCase ( ) -> None:
lowercase_ : List[Any] = input("""Enter message: """ )
lowercase_ : str = input("""Enter key [alphanumeric]: """ )
lowerca... | 30 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __magic_name__ ( _UpperCAmelCase):
@staticmethod
@abstractmethod
def SCREAMING_SNAKE_CASE_ ( lowercase_ : ArgumentParser ):
raise NotImplementedError()
... | 30 | '''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __magic_name__ ( unittest.TestCase):
def SCREAMING_SNA... | 30 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
_lowercase : List[str] = logging.get_logger(__name__)
class __magic_name__ ( _UpperCAmelCase):
def __init__( self : int , *lowercase... | 30 | '''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__ = fiel... | 30 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import pow, sqrt
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> dict[str, float]:
if (resistance, reactance, impedance).count(0 ) != ... | 30 | '''simple docstring'''
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def lowerCamelCase ( UpperCAmelCase__ : Union[str, Any] , UpperCAmelCase__ : in... | 30 | 1 |
'''simple docstring'''
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def lowerCamelCase ( UpperCAmelCase__ : str ) -> str:
return "".join(sorted(UpperCAmelCase__ ) )
def lowerCamelCase ( UpperCAmelCase__ : s... | 30 | '''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : list , UpperCAmelCase__ : int | None = None , UpperCAmelCase__ : int | None = None ) -> None:
if start is None:
lowercase_ : Any = 0
... | 30 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : list , UpperCAmelCase__ : int | None = None , UpperCAmelCase__ : int | None = None ) -> None:
if start is None:
lowercase_ : Any = 0
... | 30 | '''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_lowercase : Optional[Any] = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : bool = False ) -> bool:
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n % 10 not in (1, 3, 7, 9): # can quickly check l... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Optional[Any] = {
"configuration_swiftformer": [
"SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SwiftFormerConf... | 30 | 1 |
'''simple docstring'''
from torch import nn
class __magic_name__ ( nn.Module):
def __init__( self : List[Any] , lowercase_ : Tuple , lowercase_ : Optional[int] ):
super().__init__()
lowercase_ : Optional[An... | 30 | '''simple docstring'''
import unittest
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray | None = None , ) -> np.ndarray:
lowercase_ ... | 30 | 1 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_avail... | 30 | '''simple docstring'''
_lowercase : int = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def lowerCamelCase ( UpperCAmelCase__ : bytes ) -> bytes:
# Make sure the supplied data is a bytes-like object
if not isinstance(UpperCAmelCase__ , U... | 30 | 1 |
'''simple docstring'''
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallba... | 30 | '''simple docstring'''
import argparse
_lowercase : Optional[int] = "docs/source/_static/js/custom.js"
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Dict:
with open(UpperCAmelCase__ , encoding="""utf-8""" , newline="""\n""" ) as f:
lower... | 30 | 1 |
'''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def lowerCamelCase ( UpperCAmelCase__ : Any ) -> Optional[Any]:
for param in module.parameters():
lowercase_ : Optional[Any] = False
def lowe... | 30 | '''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
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 BackboneTest... | 30 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 30 | '''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase : Optional[Any] = [
"Prosecutor: \"No videos were used in the crash investigation\" German papers say th... | 30 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__ = fiel... | 30 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"facebook/s2t-small-librispeech-asr": (
"https://huggingface.co/facebook/s2t-small... | 30 | 1 |
'''simple docstring'''
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class __magic_name__ ( _Upp... | 30 | '''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ... | 30 | 1 |
'''simple docstring'''
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase : Optional[int] = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < ve... | 30 | '''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docst... | 30 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Union[str, Any] = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"vinvino02/glpn-kitti": "https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 30 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def lowerCamelCase ( UpperCAmelCase__ : Any , UpperCAmelCase__ : Union[str, Any] , UpperCAmelCase__ : Tuple , UpperCAmelCase__ : Option... | 30 | '''simple docstring'''
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("""dataset_size""" , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize("""input_in_memory_max_size""" , ["""default""", 0, 100 * 2**20, 900 * 2**20] ... | 30 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase ( UpperCAmelCase__ : List[str] , UpperCAmelCase__ : Tuple , ... | 30 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer,... | 30 | 1 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
_lowercase : Optional[Any] = datasets.logging.get_logger(__name__)
_lowercase : Union[str, Any] = "\\n@inproceedings{bleurt,\n title={BLEURT: Learning R... | 30 | '''simple docstring'''
from collections.abc import Callable
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : Callable , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> np.array:
... | 30 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified... | 30 | '''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : float = 1 / sqrt(2 ) ) -> IIRFilter:
lowercase_ : str ... | 30 | 1 |
'''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase : Optional[Any] = [
"Prosecutor: \"No videos were used in the crash investigation\" German papers say th... | 30 | '''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import ... | 30 | 1 |
'''simple docstring'''
import math
import random
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : bool = False ) -> float:
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
_lowercase : ... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowercase : Dict = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
try:
... | 30 | 1 |
'''simple docstring'''
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
_lowercase : Tuple = "scheduler_config.json"
class __magic_name__ ( _UpperCAmelCase):
... | 30 | '''simple docstring'''
_lowercase : int = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def lowerCamelCase ( ) -> None:
lowercase_ : List[Any] = input("""Enter message: """ )
lowercase_ : str = input("""Enter key [alphanumeric]: """ )
lowerca... | 30 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=_UpperCAmelCase):
UpperCamelCase__ = ['''flax''', '''transformers''']
def __init__( self : Optional[Any] , *lowercase_ : int , **lowe... | 30 | '''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __magic_name__ ( unittest.TestCase):
def SCREAMING_SNA... | 30 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int ) -> tuple[int, int]:
if b == 0:
return (1, 0)
((lowercase_) , (lowercase_)) : str = extended_euclid(Upper... | 30 | '''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__ = fiel... | 30 | 1 |
'''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def lowerCamelCase ( UpperCAmelCase__ : int ) -> str:
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise TypeError("""Undefined for non-integers""" ... | 30 | '''simple docstring'''
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def lowerCamelCase ( UpperCAmelCase__ : Union[str, Any] , UpperCAmelCase__ : in... | 30 | 1 |
'''simple docstring'''
class __magic_name__ :
def __init__( self : List[str] ):
lowercase_ : Optional[Any] = {}
def SCREAMING_SNAKE_CASE_ ( self : Optional[Any] ):
print(self.vertex )
for i in self.vert... | 30 | '''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : list , UpperCAmelCase__ : int | None = None , UpperCAmelCase__ : int | None = None ) -> None:
if start is None:
lowercase_ : Any = 0
... | 30 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Optional[int] = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mask2Former... | 30 | '''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_lowercase : Optional[Any] = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add... | 30 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
_lowercase : Dict = logging.... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Optional[Any] = {
"configuration_swiftformer": [
"SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SwiftFormerConf... | 30 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : list[int] ) -> bool:
return len(set(UpperCAmelCase__ ) ) == len(UpperCAmelCase__ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 30 | '''simple docstring'''
import unittest
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray | None = None , ) -> np.ndarray:
lowercase_ ... | 30 | 1 |
'''simple docstring'''
import math
import qiskit
def lowerCamelCase ( UpperCAmelCase__ : int = 1 , UpperCAmelCase__ : int = 1 , UpperCAmelCase__ : int = 1 ) -> qiskit.result.counts.Counts:
if (
isinstance(UpperCAmelCase__ , UpperCAmelCase__ )
... | 30 | '''simple docstring'''
_lowercase : int = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def lowerCamelCase ( UpperCAmelCase__ : bytes ) -> bytes:
# Make sure the supplied data is a bytes-like object
if not isinstance(UpperCAmelCase__ , U... | 30 | 1 |
'''simple docstring'''
from ... import PretrainedConfig
_lowercase : Union[str, Any] = {
"sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__ = NEZHA_PRETRAINED_CONFIG_A... | 30 | '''simple docstring'''
import argparse
_lowercase : Optional[int] = "docs/source/_static/js/custom.js"
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Dict:
with open(UpperCAmelCase__ , encoding="""utf-8""" , newline="""\n""" ) as f:
lower... | 30 | 1 |
'''simple docstring'''
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 impor... | 30 | '''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
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 BackboneTest... | 30 | 1 |
'''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __magic_name__ :
pass
| 30 | '''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase : Optional[Any] = [
"Prosecutor: \"No videos were used in the crash investigation\" German papers say th... | 30 | 1 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowercase : List[Any] = loggin... | 30 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"facebook/s2t-small-librispeech-asr": (
"https://huggingface.co/facebook/s2t-small... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int ) -> str:
return "\n".join(
F'''{number} * {i} = {number * i}''' for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication... | 30 | '''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ... | 30 | 1 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
_lowercase : Optional[Any] = parse(importlib.metadata.version("torch"))
def lowerCamelCase ( UpperCAmelCase__ : Unio... | 30 | '''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docst... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
assert (
isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) and number_of_steps > 0
), F'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
if number... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 30 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
_lowercase : int = argparse.ArgumentParser(
description=(
"Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadMode... | 30 | '''simple docstring'''
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("""dataset_size""" , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize("""input_in_memory_max_size""" , ["""default""", 0, 100 * 2**20, 900 * 2**20] ... | 30 | 1 |
'''simple docstring'''
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert i... | 30 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer,... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : list[int] , UpperCAmelCase__ : list[int] , UpperCAmelCase__ : int ) -> bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(UpperCAmelC... | 30 | '''simple docstring'''
from collections.abc import Callable
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : Callable , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> np.array:
... | 30 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 30 | '''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : float = 1 / sqrt(2 ) ) -> IIRFilter:
lowercase_ : str ... | 30 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
_lowercase : Union[str, Any] = "2020.9.26"
_lowercase : Any = "xcodz-dot, cclaus, dhruvmanila"
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ ... | 30 | '''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import ... | 30 | 1 |
'''simple docstring'''
import unittest
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray | None = None , ) -> np.ndarray:
lowercase_ ... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowercase : Dict = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
try:
... | 30 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 30 | '''simple docstring'''
_lowercase : int = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def lowerCamelCase ( ) -> None:
lowercase_ : List[Any] = input("""Enter message: """ )
lowercase_ : str = input("""Enter key [alphanumeric]: """ )
lowerca... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise TypeError("""only integers accepted as input""" )
else:
lowercase_ : Optional[int] ... | 30 | '''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __magic_name__ ( unittest.TestCase):
def SCREAMING_SNA... | 30 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Optional[Any] = {
"configuration_swiftformer": [
"SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SwiftFormerConf... | 30 | '''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__ = fiel... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : list ) -> list:
lowercase_ : Any = len(UpperCAmelCase__ )
for _ in range(UpperCAmelCase__ ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + ... | 30 | '''simple docstring'''
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def lowerCamelCase ( UpperCAmelCase__ : Union[str, Any] , UpperCAmelCase__ : in... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : list[int] , UpperCAmelCase__ : list[int] ) -> tuple[float, float]:
# Check if the input is valid
if not len(UpperCAmelCase__ ) == len(UpperCAmelCase__ ) == 3:
raise ValueError("""Please... | 30 | '''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : list , UpperCAmelCase__ : int | None = None , UpperCAmelCase__ : int | None = None ) -> None:
if start is None:
lowercase_ : Any = 0
... | 30 | 1 |
'''simple docstring'''
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_... | 30 | '''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_lowercase : Optional[Any] = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add... | 30 | 1 |
'''simple docstring'''
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
... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Optional[Any] = {
"configuration_swiftformer": [
"SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SwiftFormerConf... | 30 | 1 |
'''simple docstring'''
_lowercase : int = [0, 2, 4, 6, 8]
_lowercase : str = [1, 3, 5, 7, 9]
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : list[int] , UpperCAmelCase__ : int ) -> int:
if... | 30 | '''simple docstring'''
import unittest
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray | None = None , ) -> np.ndarray:
lowercase_ ... | 30 | 1 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> float:
lowercase_ : Union[str, Any] = x
lowercase_ : ... | 30 | '''simple docstring'''
_lowercase : int = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def lowerCamelCase ( UpperCAmelCase__ : bytes ) -> bytes:
# Make sure the supplied data is a bytes-like object
if not isinstance(UpperCAmelCase__ , U... | 30 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
_lowercase : Optional[int] = {
"configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"],
}
t... | 30 | '''simple docstring'''
import argparse
_lowercase : Optional[int] = "docs/source/_static/js/custom.js"
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Dict:
with open(UpperCAmelCase__ , encoding="""utf-8""" , newline="""\n""" ) as f:
lower... | 30 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : list[float] ) -> float:
lowercase_ : Union[str, Any] = 0.00
lowercase_ : Optional[int] = 0
for resistor in resistors:
if re... | 30 | '''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
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 BackboneTest... | 30 | 1 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : float = 1 / sqrt(2 ) ) -> IIRFilter:
lowercase_ : str ... | 30 | '''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase : Optional[Any] = [
"Prosecutor: \"No videos were used in the crash investigation\" German papers say th... | 30 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
_lowercas... | 30 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"facebook/s2t-small-librispeech-asr": (
"https://huggingface.co/facebook/s2t-small... | 30 | 1 |
'''simple docstring'''
# Copyright 2022 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
#
# U... | 30 | '''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ... | 30 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
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 BackboneTest... | 30 | '''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docst... | 30 | 1 |
'''simple docstring'''
# 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
#
# U... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 30 | 1 |
'''simple docstring'''
_lowercase : List[Any] = "Input must be a string of 8 numbers plus letter"
_lowercase : Any = "TRWAGMYFPDXBNJZSQVHLCKE"
def lowerCamelCase ( UpperCAmelCase__ : str ) -> bool:
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ... | 30 | '''simple docstring'''
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("""dataset_size""" , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize("""input_in_memory_max_size""" , ["""default""", 0, 100 * 2**20, 900 * 2**20] ... | 30 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase : Tuple = logging.get_logger(__name__)
_lowercase : Any = {
"distilbert-bas... | 30 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer,... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : List[str] , UpperCAmelCase__ : Dict ) -> Any:
lowercase_ : Optional[int] = [0 for i in range(r + 1 )]
# nc0 = 1
lowercase_ : Optional[Any] = 1
for i in range... | 30 | '''simple docstring'''
from collections.abc import Callable
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : Callable , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> np.array:
... | 30 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_avai... | 30 | '''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : float = 1 / sqrt(2 ) ) -> IIRFilter:
lowercase_ : str ... | 30 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"facebook/s2t-small-librispeech-asr": (
"https://huggingface.co/facebook/s2t-small... | 30 | '''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import ... | 30 | 1 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int ) -> int:
while a != 0:
lowercase_ , lowercase_ : Any = b % a, a
return b
def lowerCamelCase ( UpperCAmelCase__ : int , U... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowercase : Dict = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
try:
... | 30 | 1 |
'''simple docstring'''
import sys
def lowerCamelCase ( UpperCAmelCase__ : int ) -> Optional[int]:
lowercase_ : Tuple = len(UpperCAmelCase__ )
lowercase_ : Any = [[0 for x in range(UpperCAmelCase__ )] for x in range(UpperCAmelCase__ )... | 30 | '''simple docstring'''
_lowercase : int = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def lowerCamelCase ( ) -> None:
lowercase_ : List[Any] = input("""Enter message: """ )
lowercase_ : str = input("""Enter key [alphanumeric]: """ )
lowerca... | 30 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Any = {
"configuration_conditional_detr": [
"CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Conditional... | 30 | '''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __magic_name__ ( unittest.TestCase):
def SCREAMING_SNA... | 30 | 1 |
'''simple docstring'''
from scipy.stats import pearsonr
import datasets
_lowercase : int = "\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on t... | 30 | '''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase)
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__ = fiel... | 30 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_o... | 30 | '''simple docstring'''
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def lowerCamelCase ( UpperCAmelCase__ : Union[str, Any] , UpperCAmelCase__ : in... | 30 | 1 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def ... | 30 | '''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : list , UpperCAmelCase__ : int | None = None , UpperCAmelCase__ : int | None = None ) -> None:
if start is None:
lowercase_ : Any = 0
... | 30 | 1 |
'''simple docstring'''
from __future__ import annotations
_lowercase : Union[str, Any] = list[list[int]]
# assigning initial values to the grid
_lowercase : Matrix = [
[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, ... | 30 | '''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_lowercase : Optional[Any] = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add... | 30 | 1 |
'''simple docstring'''
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
_lowercase : Dict = object()
# For specifying empty leaf dict `{}`
_lowercase : Any = object()... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Optional[Any] = {
"configuration_swiftformer": [
"SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SwiftFormerConf... | 30 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
_lowercase : str = logging.get_logger(__name__)
class __magic_name__ ( _UpperCAmelCase):
def __init__( self : Optional[i... | 30 | '''simple docstring'''
import unittest
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray | None = None , ) -> np.ndarray:
lowercase_ ... | 30 | 1 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_lowercase : Optional[Any] = [
"good first issue",
"feature request",
"wip",
]
def lowerCamelCase ( ) -> List[str]:
lowercase_ : List[Any] = Github(os.... | 30 | '''simple docstring'''
_lowercase : int = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def lowerCamelCase ( UpperCAmelCase__ : bytes ) -> bytes:
# Make sure the supplied data is a bytes-like object
if not isinstance(UpperCAmelCase__ , U... | 30 | 1 |
'''simple docstring'''
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,
... | 30 | '''simple docstring'''
import argparse
_lowercase : Optional[int] = "docs/source/_static/js/custom.js"
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Dict:
with open(UpperCAmelCase__ , encoding="""utf-8""" , newline="""\n""" ) as f:
lower... | 30 | 1 |
'''simple docstring'''
import numpy as np
import datasets
_lowercase : Union[str, Any] = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean d... | 30 | '''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
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 BackboneTest... | 30 | 1 |
'''simple docstring'''
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __magic_name__ ( ... | 30 | '''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase : Optional[Any] = [
"Prosecutor: \"No videos were used in the crash investigation\" German papers say th... | 30 | 1 |
'''simple docstring'''
from collections.abc import Sequence
from queue import Queue
class __magic_name__ :
def __init__( self : Union[str, Any] , lowercase_ : Any , lowercase_ : List[Any] , lowercase_ : Tuple , lo... | 30 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"facebook/s2t-small-librispeech-asr": (
"https://huggingface.co/facebook/s2t-small... | 30 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
_low... | 30 | '''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ... | 30 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
_lowercase : List[Any] = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def lo... | 30 | '''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docst... | 30 | 1 |
'''simple docstring'''
import argparse
_lowercase : Optional[int] = "docs/source/_static/js/custom.js"
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Dict:
with open(UpperCAmelCase__ , encoding="""utf-8""" , newline="""\n""" ) as f:
lower... | 30 | '''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
try:
... | 30 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common ... | 30 | '''simple docstring'''
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("""dataset_size""" , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize("""input_in_memory_max_size""" , ["""default""", 0, 100 * 2**20, 900 * 2**20] ... | 30 | 1 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.md""", ... | 30 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer,... | 30 | 1 |
'''simple docstring'''
import math
import sys
def lowerCamelCase ( UpperCAmelCase__ : str ) -> str:
lowercase_ : Dict = """"""
try:
with open(UpperCAmelCase__ , """rb""" ) as binary_file:
lowercase_ : List[An... | 30 | '''simple docstring'''
from collections.abc import Callable
import numpy as np
def lowerCamelCase ( UpperCAmelCase__ : Callable , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : float ) -> np.array:
... | 30 | 1 |
'''simple docstring'''
import sys
_lowercase : Dict = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445... | 30 | '''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : float = 1 / sqrt(2 ) ) -> IIRFilter:
lowercase_ : str ... | 30 | 1 |
'''simple docstring'''
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transfo... | 30 | '''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import ... | 30 | 1 |
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