code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from datetime import datetime
import requests
def UpperCAmelCase_ ( _A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
SCREAMING_SNAKE_CASE__ = requests.get(base_url + url ... | 493 |
def lowerCAmelCase_ (lowercase__ : list ) -> list:
'''simple docstring'''
lowerCAmelCase__ = len(lowercase__ )
for _ in range(lowercase__ ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i... | 668 | 0 |
from collections import namedtuple
UpperCAmelCase_ : Dict = namedtuple('''from_to''', '''from_ to''')
UpperCAmelCase_ : str = {
"cubicmeter": from_to(1, 1),
"litre": from_to(0.001, 1_000),
"kilolitre": from_to(1, 1),
"gallon": from_to(0.0_0454, 264.172),
"cubicyard": ... | 17 |
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_ten... | 668 | 0 |
'''simple docstring'''
import string
from math import logaa
def UpperCamelCase ( lowercase_ : str , lowercase_ : str ) -> int:
'''simple docstring'''
lowercase =document.translate(
str.maketrans('''''' , '''''' , string.punctuation ) ).rep... | 72 |
from typing import Any
def lowerCAmelCase_ (lowercase__ : list , lowercase__ : list , lowercase__ : dict , lowercase__ : dict , lowercase__ : dict , ) -> list:
'''simple docstring'''
_validation(
... | 668 | 0 |
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
a__: Optional[Any] = 0
a__: Tuple = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0]... | 190 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
_UpperCAmelCase : A... | 668 | 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 AddedToken, PreTrainedTokenizer
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNA... | 366 |
from collections import namedtuple
_UpperCAmelCase : Dict = namedtuple("from_to", "from_ to")
_UpperCAmelCase : str = {
"cubicmeter": from_to(1, 1),
"litre": from_to(0.001, 1_000),
"kilolitre": from_to(1, 1),
"gallon": from_to(0.00454, 264.172),
"cubicyard": fr... | 668 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : int = logging.get_logger(__name__)
a : Tuple = {
"facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json",
... | 633 |
def lowerCAmelCase_ (lowercase__ : list ) -> list:
'''simple docstring'''
lowerCAmelCase__ = len(lowercase__ )
for i in range(1 , lowercase__ ):
lowerCAmelCase__ = collection[i]
lowerCAmelCase__ = 0
... | 668 | 0 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/config.json",
... | 9 |
def lowerCAmelCase_ (lowercase__ : str , lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase__ = len(lowercase__ ) + 1
lowerCAmelCase__ = len(lowercase__ ) + 1
# dp is a 2d matrix where dp[i][j] den... | 668 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def SCREAMING_SNAKE_CASE ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __Upper... | 159 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : str = logging.get_logger(__name__)
_UpperCAmelCase : Dict = {"vocab_file": "vocab.json"}
_UpperCAmelCase : Optiona... | 668 | 0 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( snake_case__ ):
__lowerCAmelCase : Optional[Any] = (DDIMParallelScheduler,)
__lowerCAmelCase : List[str] = (('eta', 0.0), ('num_inference_st... | 188 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : List[Any] = {
"configuration_distilbert": [
"DISTILBERT_P... | 668 | 0 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def __UpperCamelCase (lowerCAmelCase : dict ) -> tuple:
return (d... | 699 |
from collections import deque
class lowerCAmelCase_ :
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ):
lowerCAmelCase__ = process_name # process name
lowerC... | 668 | 0 |
"""simple docstring"""
from functools import lru_cache
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 2
__SCREAMING_SNAKE_CASE = set()
while i * i <= n:
if n % i:
i += 1
else:
... | 682 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerat... | 668 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipel... | 493 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
_UpperCAmelCase : str = {
"vocab_file": "vocab.json"... | 668 | 0 |
class lowerCamelCase_ :
def __init__( self : Optional[int] ):
__A : Dict = {}
def lowerCAmelCase_ ( self : Tuple ):
print(self.vertex )
for i in self.vertex:
print(SCREAMING_SNAKE_CASE_ , """ -> """ , """ ... | 17 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class lowerCAmelCase_ :
def __snake_case ( self : Any , SCREAMING_SNAKE_CASE_ : int ):
raise NotImplementedError()
def ... | 668 | 0 |
'''simple docstring'''
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
_UpperCAmelCase : int = Mapping[str, np.ndarray]
_UpperCAmelCase : Optional[Any] = Mapping[str, Any] # Is a... | 72 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 668 | 0 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('''socket.socket''' )
@patch('''builtins.open''' )
def UpperCamelCase__( UpperCamelCase__ : int , UpperCamelCase__ : Union[str, Any] )->Tuple:
A__ = Mock()
... | 190 |
from __future__ import annotations
def lowerCAmelCase_ (lowercase__ : list[int] , lowercase__ : list[int] , lowercase__ : int ) -> tuple[float, list[float]]:
'''simple docstring'''
lowerCAmelCase__ = list(range(len(lowercase... | 668 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ..... | 366 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow... | 668 | 0 |
"""simple docstring"""
import copy
import re
class __UpperCamelCase :
lowerCamelCase : int ='hp'
lowerCamelCase : Dict ={}
lowerCamelCase : List[Any] =None
@classmethod
def __a ( cls , lowerCAmelCase__ ,... | 633 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : Dict = logging.get_logger(__name__)
_UpperCAmelCase : Op... | 668 | 0 |
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
f... | 9 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceClassification,
D... | 668 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",
}
class lowerCamelCase (snake_cas... | 159 |
def lowerCAmelCase_ (lowercase__ : float , lowercase__ : int ) -> float:
'''simple docstring'''
if digit_amount > 0:
return round(number - int(lowercase__ ) , lowercase__ )
return number - int(lowercase__ )
if __name_... | 668 | 0 |
import itertools
import math
def UpperCAmelCase_ ( _UpperCAmelCase :int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even nu... | 188 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ..... | 668 | 0 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, logging
from .benchmar... | 699 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
_UpperCAmelCase : int = Mapping[str, np.ndarray]
_UpperCAmelCase : Optional[Any] = Mapping[str, Any] # ... | 668 | 0 |
"""simple docstring"""
from math import factorial
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
if successes > trials:
raise ValueError("successes must be lower or equal to trials" )
if trials < 0 or success... | 682 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple reposi... | 668 | 0 |
_SCREAMING_SNAKE_CASE : Optional[Any] = {
"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",
"dataclasses": ... | 493 |
def lowerCAmelCase_ (lowercase__ : list ) -> list:
'''simple docstring'''
lowerCAmelCase__ = len(lowercase__ )
for _ in range(lowercase__ ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i... | 668 | 0 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate.tes... | 17 |
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_ten... | 668 | 0 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa... | 72 |
from typing import Any
def lowerCAmelCase_ (lowercase__ : list , lowercase__ : list , lowercase__ : dict , lowercase__ : dict , lowercase__ : dict , ) -> list:
'''simple docstring'''
_validation(
... | 668 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor... | 190 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
_UpperCAmelCase : A... | 668 | 0 |
'''simple docstring'''
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTok... | 366 |
from collections import namedtuple
_UpperCAmelCase : Dict = namedtuple("from_to", "from_ to")
_UpperCAmelCase : str = {
"cubicmeter": from_to(1, 1),
"litre": from_to(0.001, 1_000),
"kilolitre": from_to(1, 1),
"gallon": from_to(0.00454, 264.172),
"cubicyard": fr... | 668 | 0 |
"""simple docstring"""
import functools
def _SCREAMING_SNAKE_CASE ( _lowercase : str , _lowercase : str ) ->int:
'''simple docstring'''
a : Tuple = len(lowercase__ )
a : int = len(low... | 633 |
def lowerCAmelCase_ (lowercase__ : list ) -> list:
'''simple docstring'''
lowerCAmelCase__ = len(lowercase__ )
for i in range(1 , lowercase__ ):
lowerCAmelCase__ = collection[i]
lowerCAmelCase__ = 0
... | 668 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
logging.... | 9 |
def lowerCAmelCase_ (lowercase__ : str , lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase__ = len(lowercase__ ) + 1
lowerCAmelCase__ = len(lowercase__ ) + 1
# dp is a 2d matrix where dp[i][j] den... | 668 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE ( __UpperCAmelCase ) -> list:
SCREAMING_SNAKE_CASE__ = len(lowercase__ )
for _ in range(lowercase__ ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
... | 159 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : str = logging.get_logger(__name__)
_UpperCAmelCase : Dict = {"vocab_file": "vocab.json"}
_UpperCAmelCase : Optiona... | 668 | 0 |
def UpperCAmelCase_ ( _UpperCAmelCase :int , _UpperCAmelCase :int ) -> int:
'''simple docstring'''
A_ = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
A_ = n - k
# Calculate C(n,k)
... | 188 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : List[Any] = {
"configuration_distilbert": [
"DISTILBERT_P... | 668 | 0 |
import random
def __UpperCamelCase (lowerCAmelCase : list, lowerCAmelCase : int ) -> tuple:
A , A , A = [], [], []
for element in data:
if element < pivot:
less.append(lowercase__ )
elif element > pivot:
... | 699 |
from collections import deque
class lowerCAmelCase_ :
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ):
lowerCAmelCase__ = process_name # process name
lowerC... | 668 | 0 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class UpperCamelCase_ ( snake_case__ , snake_case__):
"""simple docstring"... | 682 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerat... | 668 | 0 |
def UpperCAmelCase_ ( _A , _A ):
'''simple docstring'''
if digit_amount > 0:
return round(number - int(lowercase__ ) , lowercase__ )
return number - int(lowercase__ )
if __name__ == "__main__":
print(decimal_isolate(1.5_3, 0))
... | 493 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
_UpperCAmelCase : str = {
"vocab_file": "vocab.json"... | 668 | 0 |
from __future__ import annotations
import math
def __SCREAMING_SNAKE_CASE ( a__ : float ,a__ : int ) -> float:
__A : Dict = u
for i in range(1 ,lowercase__ ):
__A : List[Any] = temp * (u - i)
return temp
def __SCREAMING_SNAKE_CASE ( ) ... | 17 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class lowerCAmelCase_ :
def __snake_case ( self : Any , SCREAMING_SNAKE_CASE_ : int ):
raise NotImplementedError()
def ... | 668 | 0 |
'''simple docstring'''
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : Any = logging.get_logger(__name__)
_UpperCAmelCase : Union[str, ... | 72 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 668 | 0 |
import sys
def UpperCamelCase__( UpperCamelCase__ : List[Any] )->Optional[Any]:
A__ = len(lowercase__ )
A__ = [[0 for x in range(lowercase__ )] for x in range(lowercase__ )]
A__ = [[0 for x in range(lowercase__ )] for x in range(lowerc... | 190 |
from __future__ import annotations
def lowerCAmelCase_ (lowercase__ : list[int] , lowercase__ : list[int] , lowercase__ : int ) -> tuple[float, list[float]]:
'''simple docstring'''
lowerCAmelCase__ = list(range(len(lowercase... | 668 | 0 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
"x... | 366 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow... | 668 | 0 |
"""simple docstring"""
import mpmath # for roots of unity
import numpy as np
class __UpperCamelCase :
def __init__( self , lowerCAmelCase__=None , lowerCAmelCase__=None ) -> Tuple:
# Input as list
a : Any = list(pol... | 633 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : Dict = logging.get_logger(__name__)
_UpperCAmelCase : Op... | 668 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"facebo... | 9 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceClassification,
D... | 668 | 0 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaSt... | 159 |
def lowerCAmelCase_ (lowercase__ : float , lowercase__ : int ) -> float:
'''simple docstring'''
if digit_amount > 0:
return round(number - int(lowercase__ ) , lowercase__ )
return number - int(lowercase__ )
if __name_... | 668 | 0 |
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
from unilm.wavlm.WavL... | 188 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ..... | 668 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_UpperCAmelCase = {
"configuration_transfo_xl": ["TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP", "TransfoXLConfig"],
"tokenization_transfo_xl": ["TransfoXLCorpus... | 699 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
_UpperCAmelCase : int = Mapping[str, np.ndarray]
_UpperCAmelCase : Optional[Any] = Mapping[str, Any] # ... | 668 | 0 |
"""simple docstring"""
import os
from distutils.util import strtobool
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
for e in env_keys:
__SCREAMING_SNAKE_CASE = int(os.environ.get(lowercase__ , -1 ) )
if val >= ... | 682 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple reposi... | 668 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 493 |
def lowerCAmelCase_ (lowercase__ : list ) -> list:
'''simple docstring'''
lowerCAmelCase__ = len(lowercase__ )
for _ in range(lowercase__ ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i... | 668 | 0 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_tok... | 17 |
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_ten... | 668 | 0 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTe... | 72 |
from typing import Any
def lowerCAmelCase_ (lowercase__ : list , lowercase__ : list , lowercase__ : dict , lowercase__ : dict , lowercase__ : dict , ) -> list:
'''simple docstring'''
_validation(
... | 668 | 0 |
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 SCREAMING_SNAKE... | 190 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
_UpperCAmelCase : A... | 668 | 0 |
'''simple docstring'''
def lowerCamelCase( SCREAMING_SNAKE_CASE_ = 6008_5147_5143 ) -> int:
try:
A_ = int(lowercase__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ValueError('Paramete... | 366 |
from collections import namedtuple
_UpperCAmelCase : Dict = namedtuple("from_to", "from_ to")
_UpperCAmelCase : str = {
"cubicmeter": from_to(1, 1),
"litre": from_to(0.001, 1_000),
"kilolitre": from_to(1, 1),
"gallon": from_to(0.00454, 264.172),
"cubicyard": fr... | 668 | 0 |
"""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, ra... | 633 |
def lowerCAmelCase_ (lowercase__ : list ) -> list:
'''simple docstring'''
lowerCAmelCase__ = len(lowercase__ )
for i in range(1 , lowercase__ ):
lowerCAmelCase__ = collection[i]
lowerCAmelCase__ = 0
... | 668 | 0 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {"vocab_file": "vocab.json"}
SCREAMING_SNAKE_CASE__ = {
"vocab_file... | 9 |
def lowerCAmelCase_ (lowercase__ : str , lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase__ = len(lowercase__ ) + 1
lowerCAmelCase__ = len(lowercase__ ) + 1
# dp is a 2d matrix where dp[i][j] den... | 668 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A = {
"configuration_longformer": [
"LONGFORMER_PRETRAINED_... | 159 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : str = logging.get_logger(__name__)
_UpperCAmelCase : Dict = {"vocab_file": "vocab.json"}
_UpperCAmelCase : Optiona... | 668 | 0 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import... | 188 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : List[Any] = {
"configuration_distilbert": [
"DISTILBERT_P... | 668 | 0 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def __UpperCamelCase (lowerCAmelCase :... | 699 |
from collections import deque
class lowerCAmelCase_ :
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ):
lowerCAmelCase__ = process_name # process name
lowerC... | 668 | 0 |
"""simple docstring"""
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenizatio... | 682 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerat... | 668 | 0 |
_SCREAMING_SNAKE_CASE : Any = 8.3_1_4_4_6_2 # Unit - J mol-1 K-1
def UpperCAmelCase_ ( _A , _A , _A ):
'''simple docstring'''
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter positive value.''' )
return m... | 493 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
_UpperCAmelCase : str = {
"vocab_file": "vocab.json"... | 668 | 0 |
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
UpperCAmelCase_ : Optional[Any] = parse(importlib.metadata.version('''torch'''))
def __SCREAMING_SNAKE_CASE ( a__ : Union[str, Version] ,a_... | 17 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class lowerCAmelCase_ :
def __snake_case ( self : Any , SCREAMING_SNAKE_CASE_ : int ):
raise NotImplementedError()
def ... | 668 | 0 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def UpperCamelCase ( lowercase_ : str = "" , ) -> bool:
'''simple docstring'''
return sum(c % 2 for c in Counter(input_str.replace(''' ''' , '''''' ).lower() ).values() ) < 2
def Uppe... | 72 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 668 | 0 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def UpperCamelCase__( ... | 190 |
from __future__ import annotations
def lowerCAmelCase_ (lowercase__ : list[int] , lowercase__ : list[int] , lowercase__ : int ) -> tuple[float, list[float]]:
'''simple docstring'''
lowerCAmelCase__ = list(range(len(lowercase... | 668 | 0 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def lowerCamelCase( SCREAMING_SNAKE_CASE_ ,SCREAMIN... | 366 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow... | 668 | 0 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class A_ :
'''simple docstring'''
__snake_case = None
__snake_case = False
__snake_case = False
__snake_case = False
__sn... | 669 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_utils import en... | 669 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json',
'microsoft/markuplm-large': 'https://h... | 669 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'
),
# Se... | 669 | 1 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = False ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : List[str] = f'Expected string as input, found {type(SCREAMING_SNAKE_CASE__ )}'
raise ValueError(SCREAMING... | 669 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A_ ( __UpperCamelCase ):
'''simple docstring'''
__snake_case = ["""image_processor""", """tokenizer"""]
__snake_case = """CLIPImageProcessor"""... | 669 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils impor... | 669 |
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
enable_full_determinism()
class A... | 669 | 1 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(SCREAMING_SNAKE_CASE__ , int(b / 2 ) ) * actual_power(SCREAMING_SNAKE_CASE__ , int(b / 2 ) )
else:
return a * actual_power(SCREAMING_SNAKE_CASE__ ... | 669 |
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
lowercase_ = 'Usage of script: script_name <size_of_canvas:int>'
lowercase_ = [0] * 1_0_0 + [1] * 1_0
random.shuffle(choice)
def UpperCamelCase__ ( SCREAMIN... | 669 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
# See all PEGASUS models at https://huggingf... | 669 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class A_ ( __UpperCamelCase ):
'''simpl... | 669 | 1 |
import warnings
from functools import wraps
from typing import Callable
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
@wraps(SCREAMING_SNAKE_CASE__ )
def _inner_fn(*SCREAMING_SNAKE_CASE__ , **SCREAMING_SNAKE_CASE__ ):
warnings.warn(
(f'\'{fn.__name__}\' is experimental and might be subject... | 669 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowercase_ = logging.get_logger(__name__)
lowercase_ = {name: getattr(transformers, name + 'Fast') for name in SLOW_TO_F... | 669 | 1 |
from ..utils import DummyObject, requires_backends
class A_ ( metaclass=__UpperCamelCase ):
'''simple docstring'''
__snake_case = ["""speech"""]
def __init__( self: List[str] , *a: Any , **a: Dict ):
requires_backends(self , ['speech'] ... | 669 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
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 TokenizerTesterMixin
lowercas... | 669 | 1 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 669 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
... | 669 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'roberta-base': 'https://huggingface.co/roberta-b... | 669 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Dict = 1
__lowerCamelCase : str = 2
while i * i <= n:
__lowerCamelCase : int = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
if n > 1:
... | 669 | 1 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Dict = 1
__lowerCamelCase : str = 2
while i * i <= n:
__lowerCamelCase : int = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
if n > 1:
... | 669 |
import numpy as np
class A_ :
'''simple docstring'''
def __init__( self: Optional[int] ):
__lowerCamelCase : int = (0, 0)
__lowerCamelCase : List[str] = None
__lowerCamelCase : int = 0
__lowerCamelCa... | 669 | 1 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
return base * power(SCREAMING_SNAKE_CASE__ , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('Raise base to the power of exponent using recursion...')
lowercase_ = int(input... | 669 |
import math
from datetime import datetime, timedelta
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Tuple = year % 19
__lowerCamelCase : int = year % 4
__lowerCamelCase : Any = year % 7
__lowerCamelCase : Dict = math.fl... | 669 | 1 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTes... | 669 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class A_ ( __U... | 669 | 1 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , **SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Union[str, Any] = AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__ , ... | 669 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : str = int(SCREAMING_SNAKE_CASE__ )
if n_element < 1:
__lowerCamelCase : str = ValueError('a should be a positive number' )
raise my_error
__lowerCamelCase : Tuple = [1]
__lowerCamelC... | 669 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class A_ ( unittest.TestCase ):
'... | 669 |
import unittest
from knapsack import greedy_knapsack as kp
class A_ ( unittest.TestCase ):
'''simple docstring'''
def _snake_case ( self: List[Any] ):
__lowerCamelCase : str = [10, 20, 30, 40, 50, 60]
__lowerCamelCase : List... | 669 | 1 |
from jiwer import compute_measures
import datasets
lowercase_ = '\\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: improved evaluation measures fo... | 669 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
fro... | 669 | 1 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
lowercase... | 669 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_to... | 669 | 1 |
from __future__ import annotations
import math
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All prime... | 669 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowercase_ = False
try:
lowercase_ = _is_... | 669 | 1 |
from __future__ import annotations
lowercase_ = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class A_ :
'''simple docstring'''
def __init__( self: Optional[in... | 669 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class A_ ( __UpperCamelCase ):
'''simple docstring'''
__snake_case = (CMStochasticIterativeScheduler,)
__snake_case = 10
def _snake_case ... | 669 | 1 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@sl... | 669 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowercase_ = input('Enter image url: ').strip()
print(F"""Downloading image from {url} ...""")
lowercase_ = BeautifulSoup(requests.get(url).content, 'html.parser')... | 669 | 1 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class A_ ( unittest.TestCase ):
'''simple docstring'''
def _snake_case ( self: Union[str, Any] ):
__lowerCa... | 669 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
lowercase_ = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
lowercase_ = [file for file in filepaths if... | 669 | 1 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
... | 669 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'xlm-roberta-base': 'https://huggingface.co/xlm-r... | 669 | 1 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : str = hex_num.strip()
if not hex_num:
raise ValueError('No value was passed to the function' )
__lowerCamelCase : int = hex_num[0] == '-'
if is_negative:
__lowerCamelCase : int = hex_... | 669 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_utils import en... | 669 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
class A_ ( __UpperCamelCase ):
'''simple docstring'''
__snake_case = """timm_backbone"""
def __init__( self: Union[str, A... | 669 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'
),
# Se... | 669 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
... | 669 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A_ ( __UpperCamelCase ):
'''simple docstring'''
__snake_case = ["""image_processor""", """tokenizer"""]
__snake_case = """CLIPImageProcessor"""... | 669 | 1 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class A_ ( __UpperCamelCase ):
'''simple docstring'''
__snake_case = (CMStochasticIterativeScheduler,)
__snake_case = 10
def _snake_case ... | 669 |
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
enable_full_determinism()
class A... | 669 | 1 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class A_ ( __UpperCamelCase ):
'''simple docstring'''
__snake_case = ["""image_processor""", """tokenizer"""]
__snake_case = """AutoImageProcessor"""
... | 669 |
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
lowercase_ = 'Usage of script: script_name <size_of_canvas:int>'
lowercase_ = [0] * 1_0_0 + [1] * 1_0
random.shuffle(choice)
def UpperCamelCase__ ( SCREAMIN... | 669 | 1 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
if n_term == "":
return []
__lowerCamelCase : list = []
for temp in range(int(SCREAMING_SNAKE_CASE__ ) ):
series.append(f'1/{temp + 1}' if series else '1' )
return series
if __name__ == "__main__":
lowercase_ = i... | 669 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class A_ ( __UpperCamelCase ):
'''simpl... | 669 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A_ ( __UpperCamelCase ):
'''simple docstring'''
__snake_case = ["""image_processor""", """tokenizer"""]
__snake_case = """CLIPImageProcessor"""... | 669 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowercase_ = logging.get_logger(__name__)
lowercase_ = {name: getattr(transformers, name + 'Fast') for name in SLOW_TO_F... | 669 | 1 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceClassification,
DataC... | 669 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
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 TokenizerTesterMixin
lowercas... | 669 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkou... | 669 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
... | 669 | 1 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class A_ ( unittest.TestCase ):
'''simple docstring'''
def _snake_case ( self: str ):
__lowerCamelCase : O... | 669 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Dict = 1
__lowerCamelCase : str = 2
while i * i <= n:
__lowerCamelCase : int = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
if n > 1:
... | 669 | 1 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
lowercase_ = TypeVar('T')
class A_ ( Generic[T] ):
'''simple docstring'''
__snake_case = 42 # Cache store of keys
__snake_case = 42 # Re... | 669 |
import numpy as np
class A_ :
'''simple docstring'''
def __init__( self: Optional[int] ):
__lowerCamelCase : int = (0, 0)
__lowerCamelCase : List[str] = None
__lowerCamelCase : int = 0
__lowerCamelCa... | 669 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
lowercase_ = R'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the model outputs. Read the d... | 669 |
import math
from datetime import datetime, timedelta
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Tuple = year % 19
__lowerCamelCase : int = year % 4
__lowerCamelCase : Any = year % 7
__lowerCamelCase : Dict = math.fl... | 669 | 1 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
def wrapper(*SCREAMING_SNAKE_CASE__ , **SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Union[str, Any]... | 669 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class A_ ( __U... | 669 | 1 |
from ..utils import DummyObject, requires_backends
class A_ ( metaclass=__UpperCamelCase ):
'''simple docstring'''
__snake_case = ["""note_seq"""]
def __init__( self: List[Any] , *a: Optional[Any] , **a: str ):
requires_backends(self , ['no... | 669 |
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : str = int(SCREAMING_SNAKE_CASE__ )
if n_element < 1:
__lowerCamelCase : str = ValueError('a should be a positive number' )
raise my_error
__lowerCamelCase : Tuple = [1]
__lowerCamelC... | 669 | 1 |
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_flax_available():
im... | 669 |
import unittest
from knapsack import greedy_knapsack as kp
class A_ ( unittest.TestCase ):
'''simple docstring'''
def _snake_case ( self: List[Any] ):
__lowerCamelCase : str = [10, 20, 30, 40, 50, 60]
__lowerCamelCase : List... | 669 | 1 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class A_ :
'''simple docstring'''
def _snake_case ( self: Union[str, Any] , a: str ):
raise NotImplementedError()
def ... | 669 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import cached_property
fro... | 669 | 1 |
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
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'google/mobilenet_... | 669 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_to... | 669 | 1 |
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
@require_torch
@require_optimum
@slow
class A_ ( ... | 669 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
lowercase_ = False
try:
lowercase_ = _is_... | 669 | 1 |
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