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"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case_ )
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : str ... | 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"""
def lowerCamelCase_ ( _lowerCamelCase ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 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"""
import re
def lowerCamelCase_ ( _lowerCamelCase ):
return [char.split() for char in re.split(r'[^ a-z A-Z 0-9 \s]' , str_ )]
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Optional[int] = split_input(str_ ... | 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 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 |
"""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 itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class a_ ( datasets.BuilderConfig ):
'''simple docstring'''
lowerCamelCa... | 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 = 400_0000 ):
lowerCamelCase__ : Union[str, Any] = []
lowerCamelCase__ , lowerCamelCase__ : int = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(_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 argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.... | 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 ..utils import DummyObject, requires_backends
class a_ ( metaclass=snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : str = ['onnx']
def __init__(self, *lowerCamelCase_, **lowerCamelCase_ ):
'''simple docstring''... | 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 __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFM... | 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 ):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
lowerCamelCase__ : Tuple = (boundary[1] - boundary[0]) / steps
lowerCamelCase__ : List[str] = boundary[0]
lowe... | 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 unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTes... | 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"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ : List[Any] = {
"configuration_perceiver": ["PERCEIVER_PRETRAINED_CONFIG_ARC... | 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 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 |
"""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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ : List[Any] = {
"configuration_o... | 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 typing import Any
import numpy as np
def lowerCamelCase_ ( _lowerCamelCase ):
return np.array_equal(_lowerCamelCase , matrix.conjugate().T )
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : U... | 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 inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common imp... | 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 ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A_ : Union[str, Any] = {
"configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
"tokenization_tapas": ["T... | 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"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : list[list[int]] = [[0 for _ in range(_lowerCamelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
lowerCamelCase__ : Any = 1
for n in range(m + 1 ):
for ... | 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"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
lowerCamelCase__ : int = str(bin(_lowerCamelCase ) )[2:] # remove the leading "0b"
lowerCam... | 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 warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
A_ : Optional[int] = logging.get_logger(__name__)
class a_ :
'''simple... | 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 collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
A_ : Union[str,... | 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 os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
A_ ... | 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 packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def lowerCamelCase_ ( _lowerCamelCase ):
if not is_accelerate_available():
return method
lowerCamelCase__ : int = ver... | 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"""
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowerCamelCase_, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Any = None
lowerCamelCase__ : List[str] = None
lowerC... | 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"""
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
... | 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"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A_ : Union[str, Any] = logging.get_logger(__name__)
A_ : Optional[Any] = {
... | 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"""
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
A_ : List[str] = logging.get_logger(__name__)
A_ : Dict ... | 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"""
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
A_ : Optional[int] = logging.get_logger(__name__)
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__(self, *lowerCamelCa... | 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 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 |
"""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"""
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 |
"""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"""
def lowerCamelCase_ ( _lowerCamelCase = 6008_5147_5143 ):
try:
lowerCamelCase__ : Tuple = int(_lowerCamelCase )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ValueError('Param... | 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
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DE... | 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 __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , ):
lowerCamelCase__ : Dict = len(_lowerCamelCase )
# If row is equal to t... | 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 re
def lowerCamelCase_ ( _lowerCamelCase ):
if len(re.findall('[ATCG]' , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' , 'TAGC' ) ... | 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 inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_t... | 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 __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
A_ : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
A_ : list[int] = [ord(letter) for letter in string... | 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 os
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Optional[Any] = len(grid[0] )
lowerCamelCase__ : str = len(_lowerCamelCase )
lowerCamelCase__ : Optional[int] = 0
lowerCamelCase__ : Tuple ... | 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"""
from jiwer import compute_measures
import datasets
A_ : List[str] = "\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WIL:... | 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 datetime import datetime
import requests
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Any = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
lowerCamelCase__ : Union[str, Any] = requests.get(base_url ... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : int = logging.get_logger(__name__)
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : str = 'timm_backbone'
def __init... | 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 importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase=False ):
lowerCamelCase__ : List[str] = OmegaConf.load(_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 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 |
"""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"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tes... | 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 inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_configuration_common import... | 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 __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 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 logging
import os
from .state import PartialState
class a_ ( logging.LoggerAdapter ):
'''simple docstring'''
@staticmethod
def a__ (lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Union[str, Any]... | 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
A_ : Optional[Any] = logging.get_logger(__name__)
A_ : str ... | 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 unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 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 ):
lowerCamelCase__ : Optional[int] = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
lowerCamelCase__ : Optional[Any] = n - k
# Calculate C(n,k)
for i... | 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"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class a_ ( tf.keras.layers.Layer ):
'''simple docstr... | 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 List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class a_ ( snake_case_ ):
'''simple... | 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 collections.abc import Iterable
from typing import Any
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ = None ):
'''simple docstring'''
lowerCamelCase__ : Any = value
lowerCamelCase__ : Node... | 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 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 |
"""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"""
# 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... | 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 json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common ... | 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_ : dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609344,
"knot": 1.852,
}
A_ : dict[str, float] = {
"km/h": 1.0,
"m/s": 0.277777778,
"mph": 0.621371192,
"knot": 0.539956803,
}
def lowerCamelCase_ ( _lowe... | 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 json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
A_ : Tuple = logging.get_logger(__name__)
A_ : Lis... | 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 __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
A_ : Union[str, Any] = {"UserAgent": UserAgent().random}
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : i... | 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 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 |
"""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 inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...t... | 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 ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A_ : List[str] = {
"config... | 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 os
from datetime import datetime as dt
from github import Github
A_ : List[str] = [
"good first issue",
"good second issue",
"good difficult issue",
"enhancement",
"new pipeline/model",
"new scheduler",
"wip",
]
def lowerCamelCase... | 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 datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Optional[int] = f'''{sampling_rate}'''
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 unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_ten... | 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 torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowe... | 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 __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : str = list(_lowerCamelCase )
lowerCamelCase__ : Optional[int]... | 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 __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 |
"""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 gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,... | 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"""
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 |
"""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"""
def lowerCamelCase_ ( _lowerCamelCase = 10**9 ):
lowerCamelCase__ : Optional[int] = 1
lowerCamelCase__ : int = 2
lowerCamelCase__ : int = 0
lowerCamelCase__ : Tuple = 0
lowerCamelCase__ : str = 0
while per... | 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 argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_... | 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"""
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mod... | 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 __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Optional[int] = 0.00
lowerCamelCase__ : int = 0
for resistor in resistors:
if resistor <= 0:
lowerCamelCase__ : Union[str, Any] = ... | 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_tf_available,
is_tokenizers_available,
is_torch_available,
)
A_ : str = {
"configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "Lxme... | 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"""
def lowerCamelCase_ ( _lowerCamelCase ):
if length <= 0 or not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(_lowerCamelCase )]
if __name__ == "__ma... | 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
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ , lowerCamelCase__ : Optional[Any] = text, pattern
... | 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 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 (
Ma... | 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"""
from typing import Any
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , ):
_validation(
_lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCame... | 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 math
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = len(_lowerCamelCase )
lowerCamelCase__ : Optional[int] = int(math.floor(math.sqrt(_lowerCamelCase ) ) )
... | 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"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCamelCase_ ( _lowerCamelCase ):
return np.dot(_lowerCamelCase , _lowerCamelCase )
class a_ :
'''simple docstring'''
... | 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 tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : Union[str, Any] = (PNDMScheduler,)
lowerCamelCase__ : ... | 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"""
from ..utils import DummyObject, requires_backends
class a_ ( metaclass=snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : str = ['speech']
def __init__(self, *lowerCamelCase_, **lowerCamelCase_ ):
'''simple docstring... | 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 scipy.stats import pearsonr
import datasets
A_ : Any = "\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 the... | 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"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git wo... | 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 argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verb... | 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 dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, Li... | 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"""
def lowerCamelCase_ ( _lowerCamelCase ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError('only integers accepted as input' )
else:
lowerCamelCase__ : List[Any] = str(abs(_lowerCamelCase ) )
lowerCamelC... | 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 PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
A_ : Dict = {
"linear": PIL.Image.Resampling.BILINEAR,
"bilinear": PI... | 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 __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common... | 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"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
if principal <= 0:
raise Exception('Principal borrowed must be > 0' )
if rate_per_annum < 0:
raise Exception('Rate of interest must be >= 0' )
if years_to_repay <= 0 o... | 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"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : int = len(_lowerCamelCase )
lowerCamelCase__ : int = len(_lowerCamelCase )
lowerCamelCase__ : int = (
first_str_length if first_str_l... | 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 warnings
from ..trainer import Trainer
from ..utils import logging
A_ : Dict = logging.get_logger(__name__)
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__(self, lowerCamelCase_=None, **lowerCamelCase_ ):
... | 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 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 |
"""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"""
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| 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 os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
A_ : Tuple = get_tests_dir("fixtur... | 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 collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import Patchi... | 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 typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
A_ : Union[str, Any] = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFI... | 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 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 tra... | 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 random import shuffle
import tensorflow as tf
from numpy import array
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : str = int(_lowerCamelCase )
assert noofclusters < len(_lowerCamelCase )
# Find ou... | 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 argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _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 |
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