code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFea... | 717 |
'''simple docstring'''
from datetime import datetime
import requests
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : Tuple = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
UpperCAmelCase : List[str] = requests.get(base_url + url ).js... | 695 | 0 |
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class A_ ( _sna... | 718 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ = 10**9 ):
UpperCAmelCase : Union[str, Any] = 1
UpperCAmelCase : Optional[int] = 2
UpperCAmelCase : List[str] = 0
UpperCAmelCase : Union[str, Any] = 0
UpperCAmelCase : List[Any] =... | 695 | 0 |
'''simple docstring'''
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
lowercase__ = ... | 719 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
e... | 695 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {"configuration_ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig", "IBertOnnxConfig"]}
try:
if not is_torch_available():
... | 720 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class A_ ( u... | 695 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=_snake_case )
class A_ ( _snake_case ):
'''simple docstring'''
... | 721 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"huggingface/autoformer-tourism-monthly": "https://huggingface.co/huggingface... | 695 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lowercase__ : Dict = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode... | 700 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
return [sentence[i : i + ngram_size] for i in range(len(UpperCAmelCase_ ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
testmod()
| 695 | 0 |
'''simple docstring'''
from pathlib import Path
import torch
from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter
lowercase__ = "Create a default config file for Accelerat... | 701 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ = 1 / sqrt(2 ) ):
UpperCAmelCase : int = tau * frequency / samplerate
UpperCAmelCase : ... | 695 | 0 |
'''simple docstring'''
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError("To use the rich extension, install rich with `pip install rich`")
| 702 |
'''simple docstring'''
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
lowercase__ = TypeVar("T")
class A_ ( Generic[T] ):
'''simple docstring'''
UpperCAmelCase_ : deque[T]... | 695 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
8: [5, 7],
},
{
0: [... | 703 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversat... | 695 | 0 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowercase__ = 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... | 704 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LIC... | 695 | 0 |
'''simple docstring'''
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_ ( _snake_case , unitt... | 705 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extr... | 695 | 0 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
... | 706 |
'''simple docstring'''
# 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-... | 695 | 0 |
'''simple docstring'''
import string
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : Tuple = ''
for i in sequence:
UpperCAmelCase : Any = ord(UpperCAmelCase_ )
if 65 <= extract <= 90:
output += chr(1_55 - extract )
elif 97 <= extract ... | 707 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowercase__ = logging.get_logger(__name__)
class A_ ( _snake_case ):
'''simple docstring'''
def __init__... | 695 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAme... | 708 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer... | 695 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
UpperCAmelCase : List[Any] = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
UpperCAmelCas... | 709 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ = 10_00 ):
UpperCAmelCase , UpperCAmelCase : Any = 1, 1
UpperCAmelCase : Any = []
for i in range(1 , n + 1 ):
UpperCAmelCase : Tuple = prev_numerator + 2 * prev_denominator
UpperCAmelCa... | 695 | 0 |
'''simple docstring'''
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxL... | 710 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ = 10_00 ):
UpperCAmelCase : List[Any] = 2**power
UpperCAmelCase : List[Any] = 0
while n:
UpperCAmelCase , UpperCAmelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__ == "__ma... | 695 | 0 |
'''simple docstring'''
from scipy.stats import pearsonr
import datasets
lowercase__ = "\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on... | 711 |
'''simple docstring'''
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
lowercase__ = logging.get_log... | 695 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ = "▁"
lowercase__ = {"vocab_file": "sp... | 712 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
lowerca... | 695 | 0 |
'''simple docstring'''
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
lowercase__ = WebClient(token=os.environ["CI_SLACK_BOT_TOKEN"])
def UpperCam... | 713 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"google/pix2struct-textcaps-base": (
"https://hugging... | 695 | 0 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in... | 714 |
'''simple docstring'''
import baseaa
def UpperCamelCase( UpperCAmelCase_ ):
return baseaa.baaencode(string.encode('utf-8' ) )
def UpperCamelCase( UpperCAmelCase_ ):
return baseaa.baadecode(UpperCAmelCase_ ).decode('utf-8' )
if __name__ == "__main__":
lowercase__ ... | 695 | 0 |
def UpperCamelCase( ):
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowercase__ = generate_large_matrix()
lowercase__ = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
[[3, 2], [1, 0]],
[[7, 7, 6]],
... | 715 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(UpperCAmelCase_ , UpperCAmelCase_ ) ) ... | 695 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
# Return True if there is node that has not iterated.
UpperCAmelCase : Dict = [False] * len(UpperCAmelCase_ )
UpperCAmelCase : Optional[Any] ... | 716 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
fr... | 695 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class A_ ( _snake_case ):
... | 717 |
'''simple docstring'''
from datetime import datetime
import requests
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : Tuple = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
UpperCAmelCase : List[str] = requests.get(base_url + url ).js... | 695 | 0 |
import math
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
return math.pow(UpperCAmelCase_ , 2 ) - a
def UpperCamelCase( UpperCAmelCase_ ):
return 2 * x
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : str = 2.0
while st... | 718 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ = 10**9 ):
UpperCAmelCase : Union[str, Any] = 1
UpperCAmelCase : Optional[int] = 2
UpperCAmelCase : List[str] = 0
UpperCAmelCase : Union[str, Any] = 0
UpperCAmelCase : List[Any] =... | 695 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
DiffusionP... | 719 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
e... | 695 | 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_f... | 720 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class A_ ( u... | 695 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_utils ... | 721 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"huggingface/autoformer-tourism-monthly": "https://huggingface.co/huggingface... | 695 | 0 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : Any = ['image_processor', 'tokenizer']
lowerCamelCase__ :... | 696 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class a_ ( metaclass=snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : str = ['speech']
def __init__(self, *lowerCamelCase_, **lowerCamelCase_ ):
'''simple docstring... | 696 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : List[str] = False
while is_sorted is False: # Until all the indices are traversed keep looping
lowerCamelCase__ : Dict = True
for i in range(0 , len(_lowerCamelCase ) - 1 ... | 696 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Optional[Any] = 0
wh... | 696 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.u... | 696 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_comm... | 696 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : Optional[int] = logging.get_logger(__name__)
A_ : Optional[int] = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class a_ ( sn... | 696 |
"""simple docstring"""
from math import pi, sqrt, tan
def lowerCamelCase_ ( _lowerCamelCase ):
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def lowerCamelCase_ ( _lowerCamelCase , _lowerCam... | 696 | 1 |
"""simple docstring"""
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_t... | 696 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_co... | 696 | 1 |
"""simple docstring"""
from math import pi, sqrt, tan
def lowerCamelCase_ ( _lowerCamelCase ):
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def lowerCamelCase_ ( _lowerCamelCase , _lowerCam... | 696 |
"""simple docstring"""
import importlib
import inspect
import os
import re
# 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
A_ : Dict = "src/transformers"
# This is to make sure the transformers ... | 696 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A_ : Dict = logging.get_logger(__name__)
A_ : Optional[Any] = {
"google/... | 696 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ : Tuple = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_... | 696 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase = 100 ):
lowerCamelCase__ : int = 0
lowerCamelCase__ : Optional[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name_... | 696 |
"""simple docstring"""
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("Googling.....")
A_ : Optional[int] = "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
A_ : L... | 696 | 1 |
"""simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
Be... | 696 |
"""simple docstring"""
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
... | 696 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feature... | 696 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
A_ : Dict = logging.get_logger(__name__) # pylint: disable=invalid-name
class a_ ( snake_c... | 696 | 1 |
"""simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
A_ : Any = "__DUMMY_TRANSFORMERS_USER__"
A_ : Tuple = "Dummy User"
A_ : str = "hf_hZEm... | 696 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identif... | 696 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
if mass < 0:
raise ValueError('The mass of a body cannot be negative' )
return 0.5 * mass * abs(_lowerCamelCase ) * abs(_lowerCamelCase )
if __name__ == "__main__":
import doctest
... | 696 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import f... | 696 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase = 3 , _lowerCamelCase = 7 , _lowerCamelCase = 100_0000 ):
lowerCamelCase__ : List[Any] = 0
lowerCamelCase__ : Optional[Any] = 1
for current_denominator in range(1 , limit + 1 ):
lo... | 696 |
"""simple docstring"""
A_ : List[str] = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
"datacla... | 696 | 1 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def lowerCamelCase_ ( _lowerCamelCase ):
if num <= 0:
raise ValueError('math domain error' )
return quad(_lowerCamelCase , 0 , _lowerCamelCase , args=(_lowerCamelCase) ... | 696 |
"""simple docstring"""
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
A_ : Optional[int] = {
# 1536-bit
5: {
"p... | 696 | 1 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import... | 696 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
if mass < 0:
raise ValueError('The mass of a body cannot be negative' )
return 0.5 * mass * abs(_lowerCamelCase ) * abs(_lowerCamelCase )
if __name__ == "__main__":
import doctest
... | 696 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
... | 696 |
"""simple docstring"""
import json
import os
import shutil
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 AutoConfig, BertConfig, GPTaConfig
fro... | 696 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : str = len(_lowerCamelCase )
while cur > 1:
# Find the maximum number in arr
lowerCamelCase__ : str = arr.index(max(arr[0:cur] ) )
# Reverse from 0 to mi
lowerCamel... | 696 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class a_ ( snake_case_ ):
'''simple docstring'''
... | 696 | 1 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Optional[int] = prime_factors(_lowerCamelCase )
if is_square_free(_lowerCamelCase ):
ret... | 696 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ , lowerCamelCase__ : List[str] = analyze_text(_lowerCamelCase )
lowerC... | 696 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Dict = len(_lowerCamelCase )
lowerCamelCase__ : Dict = len(_lowerCamelCase )
lowerCamelCase__ : Optional[int] = [[False for _ in range(m +... | 696 |
"""simple docstring"""
import os
def lowerCamelCase_ ( ):
with open(os.path.dirname(_lowerCamelCase ) + '/p022_names.txt' ) as file:
lowerCamelCase__ : Union[str, Any] = str(file.readlines()[0] )
lowerCamelCase__ : int = names.replace('"' , '' ... | 696 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
from typing import Any
import requests
A_ : int = "https://api.github.com"
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
A_ : Optional[int] = BASE_URL + "/user... | 696 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : int = 'Speech2TextFeatureExtractor'
lowerCamelCase__ : Dict = ... | 696 | 1 |
"""simple docstring"""
# 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
#
... | 696 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 696 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class a_ ( snake_case_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def a__ (lowerCamelCase_ ):
'''simple docstring'''
raise NotImp... | 696 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data im... | 696 | 1 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
A_ : Union[str, Any] = {
"<": operator.lt,
"<=": operator.le,
"==": operator.eq,
"!=": operator.ne,
">=": operator.ge,
">": ope... | 696 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class a_ ( metaclass=snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : str = ['speech']
def __init__(self, *lowerCamelCase_, **lowerCamelCase_ ):
'''simple docstring... | 696 | 1 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 696 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Optional[Any] = 0
wh... | 696 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
fr... | 696 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_comm... | 696 | 1 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
A_ : Optional[int] = "\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n"
A_ : List[str] = ... | 696 |
"""simple docstring"""
from math import pi, sqrt, tan
def lowerCamelCase_ ( _lowerCamelCase ):
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def lowerCamelCase_ ( _lowerCamelCase , _lowerCam... | 696 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : List[Any] = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_... | 696 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_co... | 696 | 1 |
"""simple docstring"""
import numpy
# List of input, output pairs
A_ : Tuple = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
A_ : List[Any] = (((5_15, 22, 13), 5_55), ((61, 35, 49), 1_50))
A_ : int = ... | 696 |
"""simple docstring"""
import importlib
import inspect
import os
import re
# 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
A_ : Dict = "src/transformers"
# This is to make sure the transformers ... | 696 | 1 |
"""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_ : List[Any] = {"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTCo... | 696 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ : Tuple = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_... | 696 | 1 |
"""simple docstring"""
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowe... | 696 |
"""simple docstring"""
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("Googling.....")
A_ : Optional[int] = "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
A_ : L... | 696 | 1 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
A_ : Any = (7_20, 12_80) # Height, Width
A_ : List[Any] = (0.4, 0.6) # if height or width lower than this scale, drop it.
A_ : ... | 696 |
"""simple docstring"""
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
... | 696 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ : Any = {
"configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}
try:
if not is_torch_available():
raise ... | 696 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
A_ : Dict = logging.get_logger(__name__) # pylint: disable=invalid-name
class a_ ( snake_c... | 696 | 1 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : List[str] = np.max(_lowerCamelCase , axis=-1 , keepdims=_lowerCamelCase )
lowerCamelCase__ : List[Any] = np.e... | 696 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identif... | 696 | 1 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.confi... | 696 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import f... | 696 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : str = logging.get_logger(__name__)
A_ : List[str] = {
"google/canine-s": "https://huggingface.co/google/canine-s/resolve/main/config.json",
# See all CANINE models... | 696 |
"""simple docstring"""
A_ : List[str] = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
"datacla... | 696 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
... | 696 |
"""simple docstring"""
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
A_ : Optional[int] = {
# 1536-bit
5: {
"p... | 696 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A_ : Dict = {
"configuration_graphormer": ["GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "GraphormerConfig"],
}
try:
if ... | 696 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
if mass < 0:
raise ValueError('The mass of a body cannot be negative' )
return 0.5 * mass * abs(_lowerCamelCase ) * abs(_lowerCamelCase )
if __name__ == "__main__":
import doctest
... | 696 | 1 |
"""simple docstring"""
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 696 |
"""simple docstring"""
import json
import os
import shutil
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 AutoConfig, BertConfig, GPTaConfig
fro... | 696 | 1 |
"""simple docstring"""
from __future__ import annotations
A_ : int = "#"
class a_ :
'''simple docstring'''
def __init__(self ):
'''simple docstring'''
lowerCamelCase__ : dict = {}
def a__ (self, lowerCamelCase_ ... | 696 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class a_ ( snake_case_ ):
'''simple docstring'''
... | 696 | 1 |
"""simple docstring"""
from ....utils import logging
A_ : List[str] = logging.get_logger(__name__)
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowerCamelCase_=None, lowerCamelCase_=2_0_4_8 ):
'''simple docstr... | 696 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ , lowerCamelCase__ : List[str] = analyze_text(_lowerCamelCase )
lowerC... | 696 | 1 |
"""simple docstring"""
A_ : List[str] = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
"datacla... | 696 |
"""simple docstring"""
import os
def lowerCamelCase_ ( ):
with open(os.path.dirname(_lowerCamelCase ) + '/p022_names.txt' ) as file:
lowerCamelCase__ : Union[str, Any] = str(file.readlines()[0] )
lowerCamelCase__ : int = names.replace('"' , '' ... | 696 | 1 |
"""simple docstring"""
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, ... | 696 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : int = 'Speech2TextFeatureExtractor'
lowerCamelCase__ : Dict = ... | 696 | 1 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = sorted(zip(_lowerCamelCase , _lowerCam... | 696 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 696 | 1 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Tuple = int(np.ceil((x_end - xa) / step_... | 696 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data im... | 696 | 1 |
"""simple docstring"""
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Any = ('dense.weight', 'atte... | 696 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class a_ ( metaclass=snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : str = ['speech']
def __init__(self, *lowerCamelCase_, **lowerCamelCase_ ):
'''simple docstring... | 696 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
A_ : Optional[Any] = {"configuration_gpt_neox": ["GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXConfi... | 696 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Optional[Any] = 0
wh... | 696 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ : Union[str, Any] = {
"configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
"tokenization_luke": ["LukeTokenizer"],
}
tr... | 696 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_comm... | 696 | 1 |
"""simple docstring"""
# 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
#
... | 696 |
"""simple docstring"""
from math import pi, sqrt, tan
def lowerCamelCase_ ( _lowerCamelCase ):
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def lowerCamelCase_ ( _lowerCamelCase , _lowerCam... | 696 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLIm... | 696 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_co... | 696 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
fr... | 696 |
"""simple docstring"""
import importlib
import inspect
import os
import re
# 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
A_ : Dict = "src/transformers"
# This is to make sure the transformers ... | 696 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
A_ : List[Any] = logging.get_logge... | 696 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ : Tuple = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_... | 696 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError('check_bouncy() accepts only integer arguments' )
lowerCamelCase__ : List[Any] = str(_lowerCamelCase )
lowerCamelCase__ ... | 696 |
"""simple docstring"""
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("Googling.....")
A_ : Optional[int] = "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
A_ : L... | 696 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A_ : Optional[Any] = {
"configuration_conditional_detr": [
"CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Con... | 696 |
"""simple docstring"""
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
... | 696 | 1 |
"""simple docstring"""
A_ : Optional[Any] = "Alexander Joslin"
import operator as op
from .stack import Stack
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
lowerCamelCase__... | 696 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
A_ : Dict = logging.get_logger(__name__) # pylint: disable=invalid-name
class a_ ( snake_c... | 696 | 1 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_comm... | 696 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identif... | 696 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
impo... | 696 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import f... | 696 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
# Return True if there is node that has not iterated.
lowerCamelCase__ : Optional[Any] = [False] * len(_lowerCamelCase )
lowerCamelCase__ ... | 696 |
"""simple docstring"""
A_ : List[str] = {
"Pillow": "Pillow<10.0.0",
"accelerate": "accelerate>=0.20.3",
"av": "av==9.2.0",
"beautifulsoup4": "beautifulsoup4",
"black": "black~=23.1",
"codecarbon": "codecarbon==1.2.0",
"cookiecutter": "cookiecutter==1.7.3",
"datacla... | 696 | 1 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 696 |
"""simple docstring"""
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
A_ : Optional[int] = {
# 1536-bit
5: {
"p... | 696 | 1 |
"""simple docstring"""
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVis... | 696 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
if mass < 0:
raise ValueError('The mass of a body cannot be negative' )
return 0.5 * mass * abs(_lowerCamelCase ) * abs(_lowerCamelCase )
if __name__ == "__main__":
import doctest
... | 696 | 1 |
"""simple docstring"""
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import com... | 696 |
"""simple docstring"""
import json
import os
import shutil
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 AutoConfig, BertConfig, GPTaConfig
fro... | 696 | 1 |
"""simple docstring"""
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : List[str] = AutoConfig.from_pretrained... | 696 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class a_ ( snake_case_ ):
'''simple docstring'''
... | 696 | 1 |
"""simple docstring"""
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
... | 696 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ , lowerCamelCase__ : List[str] = analyze_text(_lowerCamelCase )
lowerC... | 696 | 1 |
"""simple docstring"""
import math
def lowerCamelCase_ ( _lowerCamelCase ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : List[Any] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(_lowerCamelCase )
... | 696 |
"""simple docstring"""
import os
def lowerCamelCase_ ( ):
with open(os.path.dirname(_lowerCamelCase ) + '/p022_names.txt' ) as file:
lowerCamelCase__ : Union[str, Any] = str(file.readlines()[0] )
lowerCamelCase__ : int = names.replace('"' , '' ... | 696 | 1 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_att... | 696 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : int = 'Speech2TextFeatureExtractor'
lowerCamelCase__ : Dict = ... | 696 | 1 |
"""simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : List[Any] ... | 696 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 696 | 1 |
"""simple docstring"""
import argparse
from collections import defaultdict
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Optional[int] = f'''{file}_{class_name}_{test... | 696 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data im... | 696 | 1 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visi... | 696 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class a_ ( metaclass=snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : str = ['speech']
def __init__(self, *lowerCamelCase_, **lowerCamelCase_ ):
'''simple docstring... | 696 | 1 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase = 10**-10 ):
lowerCamelCase__ : Optional[int] = ... | 696 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Optional[Any] = 0
wh... | 696 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ : Dict = {
"configuration_time_series_transformer": [
"TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TimeSeriesTransform... | 696 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_comm... | 696 | 1 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : List[str] = ['image_processor', 'tokenizer']
lowerCamelCase__ ... | 696 |
"""simple docstring"""
from math import pi, sqrt, tan
def lowerCamelCase_ ( _lowerCamelCase ):
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def lowerCamelCase_ ( _lowerCamelCase , _lowerCam... | 696 | 1 |
"""simple docstring"""
import os
import sys
import unittest
A_ : Any = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy... | 696 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_co... | 696 | 1 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data im... | 696 |
"""simple docstring"""
import importlib
import inspect
import os
import re
# 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
A_ : Dict = "src/transformers"
# This is to make sure the transformers ... | 696 | 1 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class a_ ( snake_case_ ):
'''simple docstring'''
... | 696 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ : Tuple = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_... | 696 | 1 |
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