code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
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
snake_case__ = logging.get_logger(__name__)
snak... | 4 |
'''simple docstring'''
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[Any] , _lowerCamelCase : Union[str, Any] ):
"""simple docstring"""
A_ : Union[st... | 4 | 1 |
'''simple docstring'''
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case__ ( lowerCamelCa... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list ) -> list:
if len(lowerCamelCase__ ) <= 1:
return [tuple(lowerCamelCase__ )]
A_ : List[str] = []
def generate(lowerCamelCase__ : int , lowerCame... | 4 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers... | 4 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_co... | 4 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
snake_case__ = l... | 4 |
'''simple docstring'''
import heapq
def snake_case__ ( lowerCamelCase__ : dict ) -> set[int]:
A_ : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be fi... | 4 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
snake_case__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_... | 4 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransforme... | 4 | 1 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : int = 1_0_0_0 ) -> int:
A_ ,A_ : int = 1, 1
A_ : Dict = 2
while True:
A_ : List[Any] = 0
A_ : str = fa + fa
A_ ,A_ : ... | 4 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
Robe... | 4 | 1 |
'''simple docstring'''
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
snake_case__ = """scheduler_config.jso... | 4 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
snake_case... | 4 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessin... | 4 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 4 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, ... | 4 |
'''simple docstring'''
from __future__ import annotations
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> list[int]:
A_ : int = 0
A_ : str = len(lowerCamelCase__ ) - 1
while i < ... | 4 | 1 |
'''simple docstring'''
from maths.prime_check import is_prime
def snake_case__ ( lowerCamelCase__ : int ) -> int:
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
A_ : Dict = f'Input value of [number={number}] must be an... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enu... | 4 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
snake_case__ = {
"""configuration_mega""": ["""MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegaConfig""", """MegaOnnxCon... | 4 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
snake_case__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0... | 4 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils i... | 4 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils i... | 4 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase_ (metaclass=a__ ):
"""simple docstring"""
_lowerCAmelCase = ['keras_nlp']
def __init__( self : Optional[... | 4 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case__ = l... | 4 | 1 |
'''simple docstring'''
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
... | 4 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from tr... | 4 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCamelCase_ (a__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def _a ( _lowerCamelCase : Arg... | 4 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transform... | 4 | 1 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def snake_case__ ( lowerCamelCase__ : int , lowerCamelCase__ : int , lowerCamelCase__ : float = 1 / sqrt(2 ) ) -> IIRFilter:
... | 4 |
'''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/... | 4 | 1 |
'''simple docstring'''
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
snake_case__ = numpy.array([0, 0])
snake_case__ = numpy.array([0.5, 0.8_6_6_0_2_5_4])
snake_case__ = numpy.arra... | 4 |
'''simple docstring'''
from collections.abc import Sequence
def snake_case__ ( lowerCamelCase__ : Sequence[float] , lowerCamelCase__ : bool = False ) -> float:
if not arr:
return 0
A_ : Union[str, Any] = 0 if allow_empt... | 4 | 1 |
'''simple docstring'''
from __future__ import annotations
import os
from collections.abc import Mapping
snake_case__ = tuple[int, int]
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Tuple , _lo... | 4 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""facebook/s2t-wav2vec2-large-en-de""": (
"""https://huggingface.co/facebook/s2t-wav2vec2-large-... | 4 | 1 |
'''simple docstring'''
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
snake_case__ = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path"... | 4 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
snake_case__ = l... | 4 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json""",
... | 4 |
'''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_comm... | 4 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def snake_case__ ( lowerCamelCase__ : Union[str, Any] ) -> Optional[Any]:
A_ : ... | 4 |
'''simple docstring'''
import pprint
import requests
snake_case__ = """https://zenquotes.io/api"""
def snake_case__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/today''' ).json()
def snake_case__ ( ) -> list:
return ... | 4 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encod... | 4 |
'''simple docstring'''
from __future__ import annotations
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[int] , _lowerCamelCase : int ):
"""simple docstring"""
... | 4 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)... | 4 |
'''simple docstring'''
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[Any] , _lowerCamelCase : Union[str, Any] ):
"""simple docstring"""
A_ : Union[st... | 4 | 1 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cach... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list ) -> list:
if len(lowerCamelCase__ ) <= 1:
return [tuple(lowerCamelCase__ )]
A_ : List[str] = []
def generate(lowerCamelCase__ : int , lowerCame... | 4 | 1 |
'''simple docstring'''
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
... | 4 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_co... | 4 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase_ (metaclass=a__ ):
"""simple docstring"""
_lowerCAmelCase = ['onnx']
def __init__( self : List[Any] ... | 4 |
'''simple docstring'''
import heapq
def snake_case__ ( lowerCamelCase__ : dict ) -> set[int]:
A_ : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be fi... | 4 | 1 |
'''simple docstring'''
from __future__ import annotations
snake_case__ = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""... | 4 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransforme... | 4 | 1 |
'''simple docstring'''
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
... | 4 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
Robe... | 4 | 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/... | 4 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
snake_case... | 4 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def snake_case__ ( lowerCamelCase__ : float , lowerCamelCase__ : int ) -> float:
A_ : Union[str, Any] = u
for i in range(1 , lowerCamelCase__ ):
... | 4 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 4 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMi... | 4 |
'''simple docstring'''
from __future__ import annotations
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> list[int]:
A_ : int = 0
A_ : str = len(lowerCamelCase__ ) - 1
while i < ... | 4 | 1 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
sna... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enu... | 4 | 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_inp... | 4 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
snake_case__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0... | 4 | 1 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list ) -> list:
if len(lowerCamelCase__ ) <= 1:
return lst
A_ : Any = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
... | 4 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils i... | 4 | 1 |
'''simple docstring'''
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
snake_case__ = logg... | 4 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case__ = l... | 4 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase_ (metaclass=a__ ):
"""simple docstring"""
_lowerCAmelCase = ['flax', 'transformers']
def __init__( self : ... | 4 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from tr... | 4 | 1 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : int , lowerCamelCase__ : int , lowerCamelCase__ : int ) -> float:
A_ : int = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for su... | 4 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transform... | 4 | 1 |
'''simple docstring'''
from typing import List
import numpy as np
def snake_case__ ( lowerCamelCase__ : dict ) -> int:
A_ : Tuple = {key: len(lowerCamelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCamelCase__ , lower... | 4 |
'''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/... | 4 | 1 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> list[int]:
A_ : Any = [0] ... | 4 |
'''simple docstring'''
from collections.abc import Sequence
def snake_case__ ( lowerCamelCase__ : Sequence[float] , lowerCamelCase__ : bool = False ) -> float:
if not arr:
return 0
A_ : Union[str, Any] = 0 if allow_empt... | 4 | 1 |
'''simple docstring'''
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers im... | 4 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""facebook/s2t-wav2vec2-large-en-de""": (
"""https://huggingface.co/facebook/s2t-wav2vec2-large-... | 4 | 1 |
'''simple docstring'''
import os
def snake_case__ ( ) -> List[str]:
A_ : Optional[Any] = os.path.join(os.path.dirname(lowerCamelCase__ ) , '''num.txt''' )
with open(lowerCamelCase__ ) as file_hand:
return str(sum(int(lowerC... | 4 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
snake_case__ = l... | 4 | 1 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def snake_case__ ( lowerCamelCase__ : int ) -> List[str]:
A_... | 4 |
'''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_comm... | 4 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""go... | 4 |
'''simple docstring'''
import pprint
import requests
snake_case__ = """https://zenquotes.io/api"""
def snake_case__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/today''' ).json()
def snake_case__ ( ) -> list:
return ... | 4 | 1 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
snake_case__ = """
import os
"""
snake_case__ = """
def foo():
import os
return False
"""
snake_case__ = """
def foo():
def bar():
if T... | 4 |
'''simple docstring'''
from __future__ import annotations
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[int] , _lowerCamelCase : int ):
"""simple docstring"""
... | 4 | 1 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
snake_case__ = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understand... | 4 |
'''simple docstring'''
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[Any] , _lowerCamelCase : Union[str, Any] ):
"""simple docstring"""
A_ : Union[st... | 4 | 1 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
snake_case__ = datasets.load_iris()
snake_case__ = np.array(data["""data"""])
snake_case__ = np.array(data[""... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list ) -> list:
if len(lowerCamelCase__ ) <= 1:
return [tuple(lowerCamelCase__ )]
A_ : List[str] = []
def generate(lowerCamelCase__ : int , lowerCame... | 4 | 1 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list[list[int]] , lowerCamelCase__ : int , lowerCamelCase__ : int , lowerCamelCase__ : set ) -> int:
A_ ,A_ : Optional[Any] = len(lowerCamelCase__ ), len(... | 4 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_co... | 4 | 1 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, s... | 4 |
'''simple docstring'''
import heapq
def snake_case__ ( lowerCamelCase__ : dict ) -> set[int]:
A_ : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be fi... | 4 | 1 |
'''simple docstring'''
from __future__ import annotations
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[int] , _lowerCamelCase : int ):
"""simple docstring"""
... | 4 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransforme... | 4 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ = {
"""configuration... | 4 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
Robe... | 4 | 1 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
snake_case__ = {
"""facebook/ma... | 4 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
snake_case... | 4 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
Robe... | 4 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 4 | 1 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class UpperCamelCase_ (logging.LoggerAdapter ):
"""simple docstring"""
@staticmethod
def _a ( _lowerCamelCase : Union[str, Any] ... | 4 |
'''simple docstring'''
from __future__ import annotations
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> list[int]:
A_ : int = 0
A_ : str = len(lowerCamelCase__ ) - 1
while i < ... | 4 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTe... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enu... | 4 | 1 |
'''simple docstring'''
from ... import PretrainedConfig
snake_case__ = {
"""sijunhe/nezha-cn-base""": """https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json""",
}
class UpperCamelCase_ (a__ ):
"""simple docstring... | 4 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
snake_case__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0... | 4 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
snake_case__ = {
"""configuration_xlm""": ["""XLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMConfig""", """XLMOnnxConfig"""],... | 4 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils i... | 4 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""Intel/dpt-large""": """https://huggingface.co/Intel/dpt-lar... | 4 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case__ = l... | 4 | 1 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_comm... | 4 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from tr... | 4 | 1 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip i... | 4 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transform... | 4 | 1 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
... | 4 |
'''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/... | 4 | 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_comm... | 4 |
'''simple docstring'''
from collections.abc import Sequence
def snake_case__ ( lowerCamelCase__ : Sequence[float] , lowerCamelCase__ : bool = False ) -> float:
if not arr:
return 0
A_ : Union[str, Any] = 0 if allow_empt... | 4 | 1 |
'''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class UpperCamelCase_ (ctypes.Structure ):
"""simple docst... | 4 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""facebook/s2t-wav2vec2-large-en-de""": (
"""https://huggingface.co/facebook/s2t-wav2vec2-large-... | 4 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import Tok... | 4 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
snake_case__ = l... | 4 | 1 |
'''simple docstring'''
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
... | 4 |
'''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_comm... | 4 | 1 |
'''simple docstring'''
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShar... | 4 |
'''simple docstring'''
import pprint
import requests
snake_case__ = """https://zenquotes.io/api"""
def snake_case__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/today''' ).json()
def snake_case__ ( ) -> list:
return ... | 4 | 1 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from tr... | 4 |
'''simple docstring'''
from __future__ import annotations
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[int] , _lowerCamelCase : int ):
"""simple docstring"""
... | 4 | 1 |
'''simple docstring'''
def snake_case__ ( ) -> int:
return 1
def snake_case__ ( lowerCamelCase__ : int ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def snake_case__ ( lowerCamelCase__ : int ) -... | 4 |
'''simple docstring'''
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[Any] , _lowerCamelCase : Union[str, Any] ):
"""simple docstring"""
A_ : Union[st... | 4 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase_ (a__ ):
... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list ) -> list:
if len(lowerCamelCase__ ) <= 1:
return [tuple(lowerCamelCase__ )]
A_ : List[str] = []
def generate(lowerCamelCase__ : int , lowerCame... | 4 | 1 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list ) -> list:
if len(lowerCamelCase__ ) <= 1:
return [tuple(lowerCamelCase__ )]
A_ : List[str] = []
def generate(lowerCamelCase__ : int , lowerCame... | 4 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_co... | 4 | 1 |
'''simple docstring'''
snake_case__ = frozenset(
[
"""prompt""",
"""height""",
"""width""",
"""guidance_scale""",
"""negative_prompt""",
"""prompt_embeds""",
"""negative_prompt_embeds""",
"""cross_attention_kwargs"""... | 4 |
'''simple docstring'''
import heapq
def snake_case__ ( lowerCamelCase__ : dict ) -> set[int]:
A_ : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be fi... | 4 | 1 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, ... | 4 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransforme... | 4 | 1 |
'''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def snake_case__ ( lowerCamelCase__ : int ) -> str:
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
raise TypeError('''Undefined for... | 4 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
Robe... | 4 | 1 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
snake_case__ = """docs/source/en/_toctree.yml"""
def snake_case__ ( lowerCamelCase__ : Optional[Any] ) -> List[str]:
A_ : List[str] = defaultdict(lo... | 4 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
snake_case... | 4 | 1 |
'''simple docstring'''
import warnings
from .generation import TFGenerationMixin
class UpperCamelCase_ (a__ ):
"""simple docstring"""
warnings.warn(
'Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.p... | 4 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 4 | 1 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
snake_case__ = False
snake_case__ = True
snake_case__ = False
if __name__ == "__m... | 4 |
'''simple docstring'''
from __future__ import annotations
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> list[int]:
A_ : int = 0
A_ : str = len(lowerCamelCase__ ) - 1
while i < ... | 4 | 1 |
'''simple docstring'''
snake_case__ = {str(digit): digit**5 for digit in range(10)}
def snake_case__ ( lowerCamelCase__ : int ) -> int:
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowerCamelCase__ ) )
def snake_case__ ( ) ... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enu... | 4 | 1 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class UpperCamelCase_ (unittest.TestCase ):
"""simple docstring"""
def... | 4 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
snake_case__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0... | 4 | 1 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_seque... | 4 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils i... | 4 | 1 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class UpperCamelCase_ (unittest.TestCase ):
... | 4 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case__ = l... | 4 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ = {
"""configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}
try:
if not is_torch... | 4 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from tr... | 4 | 1 |
'''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_docs... | 4 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transform... | 4 | 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/... | 4 |
'''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/... | 4 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, 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_ava... | 4 |
'''simple docstring'''
from collections.abc import Sequence
def snake_case__ ( lowerCamelCase__ : Sequence[float] , lowerCamelCase__ : bool = False ) -> float:
if not arr:
return 0
A_ : Union[str, Any] = 0 if allow_empt... | 4 | 1 |
'''simple docstring'''
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def snake_case__ ( lowerCamelCase__ : str , lowerCamelCase__ : Tuple... | 4 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""facebook/s2t-wav2vec2-large-en-de""": (
"""https://huggingface.co/facebook/s2t-wav2vec2-large-... | 4 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils i... | 4 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
snake_case__ = l... | 4 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
... | 4 |
'''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_comm... | 4 | 1 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def snake_case__ ( lowerCamelCase__ : Callable , lowerCamelCase__ : float , lowerCamelCase__ : float , lowerCamelCase__ : float , lowerCamelCase__ ... | 4 |
'''simple docstring'''
import pprint
import requests
snake_case__ = """https://zenquotes.io/api"""
def snake_case__ ( ) -> list:
return requests.get(API_ENDPOINT_URL + '''/today''' ).json()
def snake_case__ ( ) -> list:
return ... | 4 | 1 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : str , lowerCamelCase__ : str ) -> float:
def get_matched_characters(lowerCamelCase__ : str , lowerCamelCase__ : str ) -> str:
A_ : Any = []
... | 4 |
'''simple docstring'''
from __future__ import annotations
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[int] , _lowerCamelCase : int ):
"""simple docstring"""
... | 4 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePi... | 4 |
'''simple docstring'''
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Optional[Any] , _lowerCamelCase : Union[str, Any] ):
"""simple docstring"""
A_ : Union[st... | 4 | 1 |
'''simple docstring'''
import heapq
def snake_case__ ( lowerCamelCase__ : dict ) -> set[int]:
A_ : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be fi... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list ) -> list:
if len(lowerCamelCase__ ) <= 1:
return [tuple(lowerCamelCase__ )]
A_ : List[str] = []
def generate(lowerCamelCase__ : int , lowerCame... | 4 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers imp... | 4 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_co... | 4 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTester... | 4 |
'''simple docstring'''
import heapq
def snake_case__ ( lowerCamelCase__ : dict ) -> set[int]:
A_ : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be fi... | 4 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 4 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransforme... | 4 | 1 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_config... | 4 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
Robe... | 4 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespa... | 4 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
snake_case... | 4 | 1 |
'''simple docstring'''
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids... | 4 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 4 | 1 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimest... | 4 |
'''simple docstring'''
from __future__ import annotations
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> list[int]:
A_ : int = 0
A_ : str = len(lowerCamelCase__ ) - 1
while i < ... | 4 | 1 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datase... | 4 |
'''simple docstring'''
def snake_case__ ( lowerCamelCase__ : list[int] , lowerCamelCase__ : list[int] , lowerCamelCase__ : int ) -> bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enu... | 4 | 1 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
snake_case__ = """\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},
... | 4 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
snake_case__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0... | 4 | 1 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
snake_case__ = log... | 4 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils i... | 4 | 1 |
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