code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from collections import defaultdict
from math import ceil, sqrt
def _lowercase( __a : int = 100_0000 , __a : int = 10 ):
a__ =defaultdict(__a )
for outer_width in range(3 , (t_limit // 4) + 2 ):
if outer_width * outer_width > t_l... | 20 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 0 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
UpperCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
def lowerCAmelCase_ ( lowerCamelCase=No... | 21 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class A :
lowercase_ = 42
lowercase_ = No... | 22 |
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
__lowerCAmelCase = {
... | 684 | 0 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
snake_case__ : Union[str, Any] = """__DUMMY_TRANSFORMERS_USER__"""
snake_case__ : Optional[int] =... | 23 |
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 transformers.testing_utils import TOKEN, USER... | 684 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax impor... | 24 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 0 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
... | 25 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 0 |
'''simple docstring'''
import argparse
import os
# New Code #
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_sch... | 26 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@re... | 27 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ):
'''simple docstring'''
... | 28 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 684 | 0 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
A_ = 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_copies # noqa: E402
# This is ... | 29 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> 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
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 0 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
__a = version.parse(version.parse(torch.__version__).base_version) < version.parse('1.11')
def lowerCamelCase__ ( _lowercase , _l... | 30 |
import json
from typing import TYPE_CHECKING, 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_blenderbot... | 684 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase__ : Dict = {
'configuration_longformer': [
'LONGFORMER_PRETRAINED_CONFIG_ARCHIVE... | 31 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__lowerCAmelCase = logging.g... | 684 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm": ["XLMTokenizer"],
}
try:
... | 32 |
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
_UpperCAmelCase = []
_UpperCAmelCase = set({"(", "[", "{"} )
_UpperCAmelCase = set({")", "]", "}"} )
_UpperCAmelCase = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_lowerCAme... | 684 | 0 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor... | 33 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> tuple[float, float]:
# Check if the input is valid
if not len(_lowerCAmelCase ) == len(_lowerCAmelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if equationa[0] == equationa[1] == equationa[0] == equatio... | 684 | 0 |
"""simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
SCREAMING_SNAKE_CASE_ = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=... | 34 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Optional[Any]:
# In... | 684 | 0 |
a_ :int = 6_55_21
def a ( A__ ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : List[Any] = 1
SCREAMING_SNAKE_CASE__ : str = 0
for plain_chr in plain_text:
SCREAMING_SNAKE_CASE__ : Any ... | 35 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, 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,
)
... | 684 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def lowercase ( __A : List[Any] ) -> Any:
'''... | 36 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvaila... | 684 | 0 |
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( A__ ):
"""simple docstring"""
_lowercase = (PNDMScheduler,)
_lowercase = (('num_inference_steps', 5_0),)
def _UpperCamelCase( self : int ,... | 37 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCRE... | 684 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( __magic_name__ : int ) -> int:
'''simple docstring'''
if not isinstance(__magic_name__ , __magic_name__ ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
snake_case__ : L... | 38 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , __UpperCamelCase : List[Any]=0 ): # a graph with Node 0,1,...,N-1
_UpperCAmelCase = n
_UpperCAmelCase = [
[math.inf for j in range... | 684 | 0 |
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
r... | 39 |
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class __SCREAMING... | 684 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''hustvl/yolos-small... | 40 |
import requests
__lowerCAmelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
# fetching a list of articles in json format
_UpperCAmelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()... | 684 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PAR... | 41 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Any ):
_UpperCAmelCase ... | 684 | 0 |
'''simple docstring'''
A_ = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "U": "..-",
"V": "...-", "W... | 42 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfi... | 43 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax... | 44 |
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
__lowerCAmelCase = {
... | 684 | 0 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 45 |
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 transformers.testing_utils import TOKEN, USER... | 684 | 0 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test... | 46 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 0 |
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
... | 47 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 0 |
'''simple docstring'''
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 Ba... | 48 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 0 |
"""simple docstring"""
_lowercase : Dict = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase__ ( snake_case_ :int ):
__UpperCAmelCase = 0
while number:
# Increased Speed Slightly by checking every 5 digits tog... | 49 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 0 |
'''simple docstring'''
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 BatchFeatur... | 50 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 684 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
a__ : Optional[Any] = {'tokenization_herbert': ['HerbertTokenizer']}
try:
if not is_tokenizers_available():
raise OptionalDepen... | 51 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> 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
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A = logging.get_logger(__name__)
A = {
'''facebook/convnextv... | 52 |
import json
from typing import TYPE_CHECKING, 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_blenderbot... | 684 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_snake_case : str = logging.get_logger(__name__)
_sna... | 53 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__lowerCAmelCase = logging.g... | 684 | 0 |
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention, Imag... | 54 |
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
_UpperCAmelCase = []
_UpperCAmelCase = set({"(", "[", "{"} )
_UpperCAmelCase = set({")", "]", "}"} )
_UpperCAmelCase = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_lowerCAme... | 684 | 0 |
from math import factorial
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : List[str] ,A : Optional[int] ,A : int ):
__A = real
if isinstance(A ,A ):
__A = [1] * rank
else:
__A = ra... | 55 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> tuple[float, float]:
# Check if the input is valid
if not len(_lowerCAmelCase ) == len(_lowerCAmelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if equationa[0] == equationa[1] == equationa[0] == equatio... | 684 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
_a : int = (3, 9, -11, 0, 7, 5, 1, -1)
_a : Tuple = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class _lowercase :
_SCREAMING_SNAKE_CA... | 56 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Optional[Any]:
# In... | 684 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_tor... | 57 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, 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,
)
... | 684 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vis... | 58 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvaila... | 684 | 0 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class _SCREAMING_SNAKE_CASE ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = CustomTokenizer
pass
| 59 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCRE... | 684 | 0 |
import warnings
from ..trainer import Trainer
from ..utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
class __lowerCAmelCase ( _a ):
def __init__(self , __magic_name__=None , **__magic_name__ ) -> Dict:
'''simple docstring'''
... | 60 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , __UpperCamelCase : List[Any]=0 ): # a graph with Node 0,1,...,N-1
_UpperCAmelCase = n
_UpperCAmelCase = [
[math.inf for j in range... | 684 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {'configuration_glpn': ['GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GLPNConfig']}
try:
if not is_vision_available():
raise O... | 61 |
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class __SCREAMING... | 684 | 0 |
import operator as op
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Any = []
SCREAMING_SNAKE_CASE : Any = lambda lowercase , lowercase : int(x / y ) # noqa: E731 integer division operation
SCREA... | 62 |
import requests
__lowerCAmelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
# fetching a list of articles in json format
_UpperCAmelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()... | 684 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET... | 63 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Any ):
_UpperCAmelCase ... | 684 | 0 |
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 import (
AutoConfig,
AutoModelForMultipleChoice,
... | 64 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 0 |
"""simple docstring"""
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers impor... | 65 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 0 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import C... | 66 |
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
__lowerCAmelCase = {
... | 684 | 0 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class A_ ( UpperCAmelCase ):
"""simple docstring"""
def __UpperCAmelCase ( self : Tuple ) -> Optional... | 67 |
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 transformers.testing_utils import TOKEN, USER... | 684 | 0 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor... | 68 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 0 |
'''simple docstring'''
import numpy
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Any , a_ : numpy.ndarray , a_ : numpy.ndarray ):
"""simple docstring"""
__snake_case = input_array
# Random ... | 69 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 0 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logging.I... | 70 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 0 |
'''simple docstring'''
_lowerCamelCase = [
"""DownloadConfig""",
"""DownloadManager""",
"""DownloadMode""",
"""StreamingDownloadManager""",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_mana... | 71 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 0 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, U... | 72 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 684 | 0 |
def lowerCamelCase__ (_UpperCAmelCase):
return "".join(chr(ord(_UpperCAmelCase) - 32) if 'a' <= char <= 'z' else char for char in word)
if __name__ == "__main__":
from doctest import testmod
testmod()
| 73 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> 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
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 0 |
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=lowerCAmelCase__ ):
"""simple docstring"""
lowerCAmelCase_ = ['''torch''', '''transformers''', '''onnx''']
def __init__( self : Any , *_A : ... | 74 |
import json
from typing import TYPE_CHECKING, 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_blenderbot... | 684 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCa... | 75 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__lowerCAmelCase = logging.g... | 684 | 0 |
"""simple docstring"""
# flake8: noqa
# Lint as: python3
a_ = [
'VerificationMode',
'Version',
'disable_progress_bar',
'enable_progress_bar',
'is_progress_bar_enabled',
'experimental',
]
from .info_utils import VerificationMode
from .logging import di... | 76 |
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
_UpperCAmelCase = []
_UpperCAmelCase = set({"(", "[", "{"} )
_UpperCAmelCase = set({")", "]", "}"} )
_UpperCAmelCase = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_lowerCAme... | 684 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A = {
"""configuration_autoformer""": [
"""AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Autoforme... | 77 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> tuple[float, float]:
# Check if the input is valid
if not len(_lowerCAmelCase ) == len(_lowerCAmelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if equationa[0] == equationa[1] == equationa[0] == equatio... | 684 | 0 |
'''simple docstring'''
from torch import nn
class __A ( nn.Module ):
def __init__(self : Optional[int] , __a : List[Any] , __a : int ):
super().__init__()
UpperCAmelCase_ = class_size
UpperCAmelCase_ ... | 78 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Optional[Any]:
# In... | 684 | 0 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def _lowerCamelCase ( __lowerCamelCase ) -> List[Any]:
'''simple docstring'''
def wrapper(*__lowerCamelCase , ... | 79 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, 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,
)
... | 684 | 0 |
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMRobertaXLForSequence... | 80 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvaila... | 684 | 0 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
)
from tr... | 81 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCRE... | 684 | 0 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class low... | 82 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , __UpperCamelCase : List[Any]=0 ): # a graph with Node 0,1,...,N-1
_UpperCAmelCase = n
_UpperCAmelCase = [
[math.inf for j in range... | 684 | 0 |
"""simple docstring"""
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
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_co... | 83 |
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class __SCREAMING... | 684 | 0 |
import heapq as hq
import math
from collections.abc import Iterator
class A_ :
'''simple docstring'''
def __init__( self , snake_case ):
lowercase = str(id_ )
lowercase = None
lowercase = None
lowercase = []
lowercase = {} ... | 84 |
import requests
__lowerCAmelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
# fetching a list of articles in json format
_UpperCAmelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()... | 684 | 0 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bart.t... | 85 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Any ):
_UpperCAmelCase ... | 684 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__a :int = {'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}
try:
if not is_torch_available():
... | 86 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 0 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowerCamelCase : Any = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1), 6: (3... | 87 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_a... | 88 |
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
__lowerCAmelCase = {
... | 684 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Any = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.... | 89 |
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 transformers.testing_utils import TOKEN, USER... | 684 | 0 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
__UpperCAmelCase = '''\
@misc{chen2... | 90 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 0 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's easier... | 91 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( __magic_name__ : int = 600851475143 ) -> int:
try:
lowercase : Any =int(__magic_name__ )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' ... | 92 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 0 |
"""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 import require_visio... | 93 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 0 |
'''simple docstring'''
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
SCREAMING_SNAKE_CASE = argparse.ArgumentParser()
parser.add_argument('--du... | 94 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 684 | 0 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def snake_case ( ):
print("Making key files..." )
make_key_files("rsa" ,10_24 )
print("Key files generation succe... | 95 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> 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
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def a ( ) -> Tuple:
__magic_name__: Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
... | 96 |
import json
from typing import TYPE_CHECKING, 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_blenderbot... | 684 | 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... | 97 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__lowerCAmelCase = logging.g... | 684 | 0 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_fl... | 98 |
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
_UpperCAmelCase = []
_UpperCAmelCase = set({"(", "[", "{"} )
_UpperCAmelCase = set({")", "]", "}"} )
_UpperCAmelCase = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_lowerCAme... | 684 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_t... | 99 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> tuple[float, float]:
# Check if the input is valid
if not len(_lowerCAmelCase ) == len(_lowerCAmelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if equationa[0] == equationa[1] == equationa[0] == equatio... | 684 | 0 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 100 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Optional[Any]:
# In... | 684 | 0 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a__ ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
with pyt... | 101 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, 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,
)
... | 684 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline... | 102 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvaila... | 684 | 0 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
snake_case = logging.get_logger(__name__)
... | 103 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCRE... | 684 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 104 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , __UpperCamelCase : List[Any]=0 ): # a graph with Node 0,1,...,N-1
_UpperCAmelCase = n
_UpperCAmelCase = [
[math.inf for j in range... | 684 | 0 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTokenizerFast,
)
de... | 105 |
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class __SCREAMING... | 684 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case :Tuple ={
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvBertConfig', '... | 106 |
import requests
__lowerCAmelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
# fetching a list of articles in json format
_UpperCAmelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()... | 684 | 0 |
'''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 107 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Any ):
_UpperCAmelCase ... | 684 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__a: Optional[Any] = logging.get_logger(__name__)
__a: Optional[Any] = {
'''camembert-base''': '''ht... | 108 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class __a ( _snake_case ):
def __init__... | 109 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 0 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class snake_case ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
snake_case_ : Union[str, Any] = """M-CLIP"""
def __init__( self : Op... | 477 |
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
__lowerCAmelCase = {
... | 684 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
A_ = {"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig"]}
tr... | 391 |
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 transformers.testing_utils import TOKEN, USER... | 684 | 0 |
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import sql # noqa F401
... | 194 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 0 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class lo... | 395 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def A__ ( A_ ) -> Any:
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJK_Unified_Ide... | 497 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 0 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'snap-research/efficientformer-l1-300': (
'https://huggingface.co/snap-research/efficientformer-l1-300/resolve/mai... | 321 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 0 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unit... | 69 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 684 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json''',
}
class ... | 354 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> 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
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 0 |
'''simple docstring'''
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keeping the
# ful... | 92 |
import json
from typing import TYPE_CHECKING, 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_blenderbot... | 684 | 0 |
import string
import numpy
def UpperCamelCase ( _a , _a ) -> int:
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a , _lowerCAmelCase )
class UpperCamelCase :
'''simple docstring'''
... | 257 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__lowerCAmelCase = logging.g... | 684 | 0 |
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