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 |
|---|---|---|---|---|
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( __magic_name__ , unittest.TestCase ):
... | 711 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCamelCase__ ... | 69 | 0 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modelin... | 712 |
import unittest
from transformers import DonutProcessor
lowerCamelCase__ = """naver-clova-ix/donut-base"""
class A__ ( unittest.TestCase ):
def _lowerCamelCase ( self : Dict ):
'''simple docstring'''
... | 69 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impo... | 713 |
from numpy import exp, pi, sqrt
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = 0.0 , SCREAMING_SNAKE_CASE_ = 1.0 ) -> int:
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
... | 69 | 0 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokeniz... | 714 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( __magic_name__ , unittest.TestCase ):
... | 69 | 0 |
import mpmath # for roots of unity
import numpy as np
class A__ :
def __init__( self : Optional[Any] , a : Tuple=None , a : int=None ):
'''simple docstring'''
lowerCAmelCase__ : Tuple ... | 715 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
Eul... | 69 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load... | 716 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class A__ ( __magic_name__ ):
def __init__( self : Union[str, Any] , a : str="" , a : str="train" ):
'''simple docstring'''
... | 69 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class A__ ( unittest.TestCase... | 717 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCamelCase__ = """src/transformers"""
# This is to make sure... | 69 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"""configuration_git""": ["""GIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GitConfig""", """GitVisionConfig"""],
"""processin... | 718 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokenizer"""],
}
try:
i... | 69 | 0 |
from __future__ import annotations
from typing import Any
class A__ :
def __init__( self : List[str] , a : int , a : int , a : float = 0 ):
'''simple docstring'''
lowerCAmelCase__ : D... | 719 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""ChineseCLIPConfig""",
... | 69 | 0 |
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,
RobertaTokenizer,
RobertaTokenizerFast,... | 720 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers impo... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> float:
if principal <= 0:
raise Exception('Principal borrowed must be > 0' )
if rate_per_annum < 0:
raise Exception('Rate of interest must be >= 0' )
if years_to... | 721 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( __magic_name__ ):
lowercase = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : str , **a : Optional[i... | 69 | 0 |
import argparse
from collections import defaultdict
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
lowerCAmelCase__ : int = F'''{file}_{class_name}_{test_name}'''
... | 700 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( __magic_name__ ):
... | 69 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType... | 701 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_ten... | 69 | 0 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> list[int]:
lowerCAmelCase__ : Tuple = 2
lowerCAmelCase__ : Any = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(SCR... | 702 |
lowerCamelCase__ = """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
lowerCAmelCase__ : Union[str, Any] = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
lowerCAmelCase__ : Sta... | 69 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...uti... | 703 |
import numpy
class A__ :
def __init__( self : Tuple , a : numpy.ndarray , a : numpy.ndarray ):
'''simple docstring'''
lowerCAmelCase__ : int = input_array
# Random initial weights... | 69 | 0 |
from datetime import datetime
import requests
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> bytes:
lowerCAmelCase__ : Optional[int] = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
lowerCAmelCase__ : Tuple = requests.get(base_url + url ... | 704 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 69 | 0 |
import requests
from bsa import BeautifulSoup
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ = "https://www.worldometers.info/coronavirus" ) -> dict:
lowerCAmelCase__ : List[str] = BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE_ ).text , 'html.parser' )
lowerCAmelCase__ : ... | 705 |
from itertools import permutations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ : str = [7, 11, 1... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> str:
if isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
raise TypeError('\'float\' object cannot be interpreted as an integer' )
if isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
raise ... | 706 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_uti... | 69 | 0 |
from __future__ import annotations
lowerCamelCase__ = """Muhammad Umer Farooq"""
lowerCamelCase__ = """MIT"""
lowerCamelCase__ = """1.0.0"""
lowerCamelCase__ = """Muhammad Umer Farooq"""
lowerCamelCase__ = """contact@muhammadumerfarooq.me"""
lowerCamelCase__ = """Alph... | 707 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class A__ ( __magic_name__ ):
def __init__( self : int , a : List[str] , a : List[str] ):
'''simple docstring'''
... | 69 | 0 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
lowerCamelCase__ = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
from .safilesyste... | 708 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
... | 69 | 0 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> set[str]:
lowerCAmelCase__ : Union[str, Any] = set(SCREAMING_SNAKE_CASE_ ), [start]
while stack:
lowerCAmelCase__ : Optional[int] =... | 709 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_remb... | 69 | 0 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class A__ ( __magic_name__ ):
lowercase = ''
lowercase = (
None # protocol passed in prefix... | 710 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class A__ ( __magic_name__ ):
def __init__( self : List[Any] , a : Callable , ... | 69 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... | 711 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCamelCase__ ... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
assert column_title.isupper()
lowerCAmelCase__ : Optional[int] = 0
lowerCAmelCase__ : int = len(SCREAMING_SNAKE_CASE_ ) - 1
lowerCAmelCase__ : Union[str, Any] = 0
while index >= 0:
... | 712 |
import unittest
from transformers import DonutProcessor
lowerCamelCase__ = """naver-clova-ix/donut-base"""
class A__ ( unittest.TestCase ):
def _lowerCamelCase ( self : Dict ):
'''simple docstring'''
... | 69 | 0 |
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
lowerCamelCase__ = {
"""User-Agent""": """Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"""
""" (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582"... | 713 |
from numpy import exp, pi, sqrt
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = 0.0 , SCREAMING_SNAKE_CASE_ = 1.0 ) -> int:
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
... | 69 | 0 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
A... | 714 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( __magic_name__ , unittest.TestCase ):
... | 69 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if i... | 715 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
Eul... | 69 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class A__ :
def __init__( self : List[str] , a : Optional[int]=2 , a : Optiona... | 716 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class A__ ( __magic_name__ ):
def __init__( self : Union[str, Any] , a : str="" , a : str="train" ):
'''simple docstring'''
... | 69 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer
... | 717 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCamelCase__ = """src/transformers"""
# This is to make sure... | 69 | 0 |
'''simple docstring'''
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def l... | 718 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokenizer"""],
}
try:
i... | 69 | 0 |
import numpy
class A__ :
def __init__( self : Tuple , a : numpy.ndarray , a : numpy.ndarray ):
'''simple docstring'''
lowerCAmelCase__ : int = input_array
# Random initial weights a... | 719 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""ChineseCLIPConfig""",
... | 69 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowerCamelCase__ = {
"""configuration_gpt_neox_japanese""": ["""GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXJapaneseConfig"""],
"""... | 720 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers impo... | 69 | 0 |
import math
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = 0 , SCREAMING_SNAKE_CASE_ = 0 ) -> list:
lowerCAmelCase__ : str = end or len(SCREAMING_SNAKE_CASE_ )
for i in range(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
lowe... | 721 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( __magic_name__ ):
lowercase = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : str , **a : Optional[i... | 69 | 0 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenize... | 700 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( __magic_name__ ):
... | 69 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, s... | 701 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_ten... | 69 | 0 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if ... | 702 |
lowerCamelCase__ = """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
lowerCAmelCase__ : Union[str, Any] = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
lowerCAmelCase__ : Sta... | 69 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ = {
"""configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GraphormerConfig"""],
}
try:
if not is_t... | 703 |
import numpy
class A__ :
def __init__( self : Tuple , a : numpy.ndarray , a : numpy.ndarray ):
'''simple docstring'''
lowerCAmelCase__ : int = input_array
# Random initial weights... | 69 | 0 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> Any:
lowerCAmel... | 704 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 69 | 0 |
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ..... | 705 |
from itertools import permutations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ : str = [7, 11, 1... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> list:
lowerCAmelCase__ : Any = [0] * len(SCREAMING_SNAKE_CASE_ )
for i in range(1 , len(SCREAMING_SNAKE_CASE_ ) ):
# use last results for better performance - dynamic programming
lowerCAmelCase__ : Opt... | 706 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_uti... | 69 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... | 707 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class A__ ( __magic_name__ ):
def __init__( self : int , a : List[str] , a : List[str] ):
'''simple docstring'''
... | 69 | 0 |
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
lowerCamelCase__ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
lowerCamelCase__ = [ord(letter) for letter in string.ascii_lowercase]
lowerC... | 708 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
... | 69 | 0 |
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
lowerCamelCase__ = logging.get_logger(__name__)... | 709 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_remb... | 69 | 0 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
... | 710 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class A__ ( __magic_name__ ):
def __init__( self : List[Any] , a : Callable , ... | 69 | 0 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class A__ :
lowercase = 42 # [batch_size x 3]
lowercase = 42 # [batch_size x 3]
lowercase = 42 # [batch_size x 3]
lowercase ... | 711 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCamelCase__ ... | 69 | 0 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( __magic_name__ ):
lowercase = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : str , **a : Optional[i... | 712 |
import unittest
from transformers import DonutProcessor
lowerCamelCase__ = """naver-clova-ix/donut-base"""
class A__ ( unittest.TestCase ):
def _lowerCamelCase ( self : Dict ):
'''simple docstring'''
... | 69 | 0 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ = 3 ) -> qiskit.result.counts.Counts:
if isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
... | 713 |
from numpy import exp, pi, sqrt
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = 0.0 , SCREAMING_SNAKE_CASE_ = 1.0 ) -> int:
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
... | 69 | 0 |
lowerCamelCase__ = {"""a""": ["""c""", """b"""], """b""": ["""d""", """e"""], """c""": [], """d""": [], """e""": []}
lowerCamelCase__ = ["""a""", """b""", """c""", """d""", """e"""]
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) ... | 714 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( __magic_name__ , unittest.TestCase ):
... | 69 | 0 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionP... | 715 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
Eul... | 69 | 0 |
'''simple docstring'''
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCA... | 716 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class A__ ( __magic_name__ ):
def __init__( self : Union[str, Any] , a : str="" , a : str="train" ):
'''simple docstring'''
... | 69 | 0 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
lowerCamelCase__ = Lock()
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , ... | 717 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCamelCase__ = """src/transformers"""
# This is to make sure... | 69 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import Paddin... | 718 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokenizer"""],
}
try:
i... | 69 | 0 |
from typing import Dict
from .base import GenericTensor, Pipeline
class A__ ( __magic_name__ ):
def _lowerCamelCase ( self : Dict , a : Optional[int]=None , a : Optional[int]=None , a : Dict=None , **a : Optiona... | 719 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""ChineseCLIPConfig""",
... | 69 | 0 |
from collections.abc import Callable
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> float:
lowerCAmelCase__ : float = a
lowerCAmelCase__ : float = b
if function(SCREAMING_SNAKE_CASE_ ) == 0: # one of... | 720 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers impo... | 69 | 0 |
from __future__ import annotations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> Tuple:
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(SCREAMING_SNAKE_CASE_ ):
print(F'''{i}\t\t{d}''' )
def lowerCAmelCase__ ... | 721 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( __magic_name__ ):
lowercase = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : str , **a : Optional[i... | 69 | 0 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {"""vocab_file""": """vocab.json""", """... | 700 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( __magic_name__ ):
... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
assert isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ), F'''The input value of [n={number}] is not an integer'''
if number == 1:
return 2
elif number < 1:
lowerCAmelCase__ : Dict = F'''Th... | 701 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_ten... | 69 | 0 |
from __future__ import annotations
class A__ :
def __init__( self : Any , a : int = 0 ):
'''simple docstring'''
lowerCAmelCase__ : Any = key
def _lowerCamelCase ( self : ... | 702 |
lowerCamelCase__ = """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
lowerCAmelCase__ : Union[str, Any] = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
lowerCAmelCase__ : Sta... | 69 | 0 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers import ... | 703 |
import numpy
class A__ :
def __init__( self : Tuple , a : numpy.ndarray , a : numpy.ndarray ):
'''simple docstring'''
lowerCAmelCase__ : int = input_array
# Random initial weights... | 69 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class A__ ( __magic_name__ ):
def __init__( self : int , a : List[str] , a : List[str] ):
'''simple docstring'''
... | 704 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 69 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"""configuration_table_transformer""": [
"""TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""TableTransformerConfig""",
"""TableTransfor... | 705 |
from itertools import permutations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ : str = [7, 11, 1... | 69 | 0 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_uti... | 706 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_uti... | 69 | 0 |
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
from tra... | 707 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class A__ ( __magic_name__ ):
def __init__( self : int , a : List[str] , a : List[str] ):
'''simple docstring'''
... | 69 | 0 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class A__ ( __magic_name__ ):
lowercase = (KDPMaDiscreteScheduler,)
lowercase = 10
d... | 708 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
raise TypeError('Input value must be an \'int\' type' )
lowerCAmelCase__ : List[Any] = 0
while number:
position += 1
... | 709 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_remb... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , ) -> float:
lowerCAmelCase__ : Union[str, Any] = [redshift, radiation_density, matter_density, dark_energy]
... | 710 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class A__ ( __magic_name__ ):
def __init__( self : List[Any] , a : Callable , ... | 69 | 0 |
from __future__ import annotations
from PIL import Image
# Define glider example
lowerCamelCase__ = [
[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, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0... | 711 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCamelCase__ ... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> float:
lowerCAmelCase__ : Union[str, Any] = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
return total
def ... | 712 |
import unittest
from transformers import DonutProcessor
lowerCamelCase__ = """naver-clova-ix/donut-base"""
class A__ ( unittest.TestCase ):
def _lowerCamelCase ( self : Dict ):
'''simple docstring'''
... | 69 | 0 |
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class A__ ( __magic_name__ ):
lowerca... | 713 |
from numpy import exp, pi, sqrt
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = 0.0 , SCREAMING_SNAKE_CASE_ = 1.0 ) -> int:
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
... | 69 | 0 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class A__ ( __magic_name__ ):
def __init__( self : ... | 714 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( __magic_name__ , unittest.TestCase ):
... | 69 | 0 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeli... | 715 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
Eul... | 69 | 0 |
'''simple docstring'''
import random
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = False ) -> dict:
lowerCAmelCase__ : dict = {i: [] for i in range(SCREAMING_SNAKE_CASE_ )}
# if probability is greater or ... | 716 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class A__ ( __magic_name__ ):
def __init__( self : Union[str, Any] , a : str="" , a : str="train" ):
'''simple docstring'''
... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> list:
lowerCAmelCase__ : Tuple = len(SCREAMING_SNAKE_CASE_ )
lowerCAmelCase__ : Union[str, Any] = []
for i in range(len(SCREAMING_SNAKE_CASE_ ) - pat_len + 1 ):
lowerCAmelCase... | 717 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCamelCase__ = """src/transformers"""
# This is to make sure... | 69 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_... | 718 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokenizer"""],
}
try:
i... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> int:
if len(SCREAMING_SNAKE_CASE_ ) != len(SCREAMING_SNAKE_CASE_ ):
raise ValueError('String lengths must match!' )
lowerCAmelCase__ : Tuple = 0
for chara, chara in zip(SCREAMING_SNAKE... | 719 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""ChineseCLIPConfig""",
... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> list:
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError('The given input must be positive' )
# get the generated string sequence
lowerCAmelCase__ : Any = gray_code_sequence_... | 720 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers impo... | 69 | 0 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import... | 721 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( __magic_name__ ):
lowercase = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : str , **a : Optional[i... | 69 | 0 |
lowerCamelCase__ = """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ):
lowerCAmelCase__ : Union[str, Any] = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
lowerCAmelCase__ : Stack[int] ... | 700 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A__ ( __magic_name__ ):
... | 69 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCamelCase__ = {"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOnnxConfig"""]}
try:
if not is_torch_available(... | 701 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_ten... | 69 | 0 |
import numpy as np
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> np.array:
return 1 / (1 + np.exp(-vector ))
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> np.array:
return vector * sigmoid(1.702 * vector )
if __name__ == "__main__":
import doctest
... | 702 |
lowerCamelCase__ = """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
lowerCAmelCase__ : Union[str, Any] = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
lowerCAmelCase__ : Sta... | 69 | 0 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ = logging.get_logger(__name__)
class A__ ( __magic_name__ ):
def __init__( self : List[Any] , *a : str , **a... | 703 |
import numpy
class A__ :
def __init__( self : Tuple , a : numpy.ndarray , a : numpy.ndarray ):
'''simple docstring'''
lowerCAmelCase__ : int = input_array
# Random initial weights... | 69 | 0 |
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
lowerCamelCase__ = re.compile(r"""^(?P<major>\d+)""" r"""\.(?P<minor>\d+)""" r"""\.(?P<patch>\d+)$""")
@total_ordering
@dataclass
... | 704 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 69 | 0 |
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCase__ = get_tests_dir("""fixtures/spiece.model""")
... | 705 |
from itertools import permutations
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ : str = [7, 11, 1... | 69 | 0 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
lowerCamelCase__ = 2048
lowerCamelCase__ = 4096
lowerCamelCase__ = 42
lowerCamelCase__ = os.environ.pop("""PROCESS_TRAIN""", """false""")
lowerCamelCase__ = {"""null""": 0, """short""": 1, """long""": ... | 706 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_uti... | 69 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class A__ ( __magic_name__ ):
... | 707 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class A__ ( __magic_name__ ):
def __init__( self : int , a : List[str] , a : List[str] ):
'''simple docstring'''
... | 69 | 0 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"""huggingface/autoformer-tourism-monthly""": """https://huggingface.co/huggingface/autoformer-tourism-... | 708 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
... | 69 | 0 |
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_availab... | 709 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_remb... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
lowerCAmelCase__ : Any = abs(SCREAMING_SNAKE_CASE_ )
lowerCAmelCase__ : List[Any] = 0
while n > 0:
res += n % 10
n //= 10
return res
def lowerCAmelCase__ ( SCREAMING_SNAKE_... | 710 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class A__ ( __magic_name__ ):
def __init__( self : List[Any] , a : Callable , ... | 69 | 0 |
import tensorflow as tf
from ...tf_utils import shape_list
class A__ ( tf.keras.layers.Layer ):
def __init__( self : Any , a : List[str] , a : Optional[int] , a : Tuple , a : int , a : Optional[int]=1 ... | 711 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCamelCase__ ... | 69 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {"""vocab_file""": """sentence... | 712 |
import unittest
from transformers import DonutProcessor
lowerCamelCase__ = """naver-clova-ix/donut-base"""
class A__ ( unittest.TestCase ):
def _lowerCamelCase ( self : Dict ):
'''simple docstring'''
... | 69 | 0 |
from __future__ import annotations
import math
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> list[int]:
if num <= 0:
lowerCAmelCase__ : Dict = F'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(SCREAMING_SNAKE_CASE_ )
lowerCA... | 713 |
from numpy import exp, pi, sqrt
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = 0.0 , SCREAMING_SNAKE_CASE_ = 1.0 ) -> int:
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
... | 69 | 0 |
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
... | 714 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( __magic_name__ , unittest.TestCase ):
... | 69 | 0 |
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor... | 715 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
Eul... | 69 | 0 |
'''simple docstring'''
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCamelCase__ = """src/transform... | 716 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class A__ ( __magic_name__ ):
def __init__( self : Union[str, Any] , a : str="" , a : str="train" ):
'''simple docstring'''
... | 69 | 0 |
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 lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_... | 717 |
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowerCamelCase__ = """src/transformers"""
# This is to make sure... | 69 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class A__ :
def __init__( self : int , a : int , a : MutableSequence[float] ):
'''simple docstring'''
... | 718 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokenizer"""],
}
try:
i... | 69 | 0 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tenso... | 719 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""ChineseCLIPConfig""",
... | 69 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> list[list[int]]:
lowerCAmelCase__ : Union[str, Any] = []
if len(SCREAMING_SNAKE_CASE_ ) == 1:
return [nums.copy()]
for _ in range(len(SCREAMING_SNAKE_CASE_ ) ):
lowerCAmelCase__ : Optional[int] = nu... | 720 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers impo... | 69 | 0 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
requ... | 721 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( __magic_name__ ):
lowercase = (DDPMParallelScheduler,)
def _lowerCamelCase ( self : str , **a : Optional[i... | 69 | 0 |
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,
TrainerCallback,
Traini... | 70 | from math import sqrt
def UpperCamelCase ( __lowercase : int = 1_00_00_00 ):
'''simple docstring'''
A_ : int = 0
A_ : int = 0
A_ : int
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 ,... | 70 | 1 |
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