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 typing import Any
import numpy as np
def lowerCamelCase_ ( UpperCamelCase__ : np.ndarray ) -> bool:
"""simple docstring"""
return np.array_equal(lowerCamelCase_ , matrix.conjugate().T )
def lowerCamelCase_ ( Uppe... | 469 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ : Optional[Any] = {
'''configuration_whisper''': ['''WHISPER_PRETRAINE... | 105 | 0 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( lowercase : list[int] ):
'''simple docstring'''
lowerCamelCase_ = len(lowerCamelCase_ ) // 2
# choose the middle 3 elements
lowerCamelCase_ = lst[m - 1 : m + 2]
... | 70 |
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __UpperCAmelCase ( lowerCamelCase_ : np.ndarray , lowerCamelCase_ : np.ndarray ) -> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b , ... | 105 | 0 |
"""simple docstring"""
import unittest
from transformers import BigBirdConfig, 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
from transformer... | 438 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCamelCase__ : str = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase_ ):
def __init__( self ,*snake_case__ ,**snake... | 105 | 0 |
from __future__ import annotations
lowerCamelCase__ = list[list[int]]
# assigning initial values to the grid
lowerCamelCase__ = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, ... | 122 |
def __UpperCAmelCase ( lowerCamelCase_ : List[str] , lowerCamelCase_ : Optional[Any] ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] = [0 for i in range(r + 1 )]
# nc0 = 1
SCREAMING_SNAKE_CASE_ : Dict = 1... | 105 | 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 __lowerCamelCase ( lowerCamelCase__ ):
"""simple docstring"""
ret... | 496 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class lowerCAmelCase_ :
def __init__( self ,snake_case__ ):
SCREAMING_SNAKE_CASE_ : Optional[int] = list_of_points
# Degree determines the flexibility of the curve.
... | 105 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case_ ) -> int:
if not nums:
return 0
A__ : List[str] =nums[0]
A__ : Any =0
for num in nums[1:]:
A__ : Tuple =(
max_excluding + n... | 416 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_barthez im... | 105 | 0 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class ... | 495 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase__ : Optional[int] = {
'''configuration_bloom''': ['''BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BloomConfig''', '''BloomOnnxConfig'''],
}... | 105 | 0 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import... | 541 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
UpperCamelCase__ : List[Any] = pytest.mark.integration
@pytest.mark.parametrize('path' , ... | 105 | 0 |
from collections import defaultdict
from math import ceil, sqrt
def UpperCAmelCase__( __UpperCAmelCase : int = 1_00_00_00 , __UpperCAmelCase : int = 10 ):
__snake_case : defaultdict = defaultdict(lowerCamelCase_ )
for outer_width in range(3 , ... | 576 |
import os
import numpy
import onnx
def __UpperCAmelCase ( lowerCamelCase_ : str , lowerCamelCase_ : Optional[Any] ) -> Optional[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : int = a.name
SCREAMING_SNAKE_CASE_ : Dict = ... | 105 | 0 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos.js... | 405 |
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()
UpperCamelCase__ : Tuple = logging.get_logger(__name__)
UpperCamelCase__ : Option... | 105 | 0 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , **SCREAMING_SNAKE_CASE ):
A_ : str = AutoConfig.from_pretrained(lowerCamelCase_ , **lowerCamelCase_... | 590 |
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tenso... | 105 | 0 |
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__A = '''.'''
# Internal TensorFlow ops tha... | 469 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos.json'],
['d... | 105 | 0 |
from manim import *
class A( lowerCamelCase_ ):
'''simple docstring'''
def a__ ( self : Optional[Any] ) -> List[str]:
"""simple docstring"""
lowerCamelCase_ = Rectangle(height=0.5 , width=0.5 )
... | 70 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCamelCase__ : Any = logging.get_logger(__name__)
UpperCamelCase__ : Any = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/ma... | 105 | 0 |
"""simple docstring"""
import argparse
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_dummies.py
_lowerCAmelCase : List[str] = '''src/diffusers'''
# Matches is_xxx_available()
_lowerCAmelCase : Optio... | 438 |
import os
import sys
import unittest
UpperCamelCase__ : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dumm... | 105 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 122 |
def __UpperCAmelCase ( lowerCamelCase_ : str ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = 0
for ch in input_str:
SCREAMING_SNAKE_CASE_ : Union[str, Any] = ord(lowerCamelCase_ )
SCREAMING_SNAKE_CASE_ : Tup... | 105 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {'''configuration_sew''': ['''SEW_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWConfig''']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable... | 496 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
Fla... | 105 | 0 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPip... | 416 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, ... | 105 | 0 |
'''simple docstring'''
lowercase : List[Any] = '''Alexander Joslin'''
import operator as op
from .stack import Stack
def SCREAMING_SNAKE_CASE__ ( __A ) -> int:
_snake_case = {'*': op.mul, '/': op.truediv, '+': op.add, '-': op.sub}
_snake_case = Sta... | 495 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.mo... | 105 | 0 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_UpperCamelCase : ... | 541 |
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
UpperCamelCase__ : Dict = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase_ ):
def __init__( self ,*snake_case__ ,**s... | 105 | 0 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import Array... | 576 |
from __future__ import annotations
def __UpperCAmelCase ( lowerCamelCase_ : list[float] ) -> float:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = 0.0_0
SCREAMING_SNAKE_CASE_ : Tuple = 0
for resistor in resistors:
if... | 105 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils ... | 405 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCAmelCase ( lowerCamelCase_ : Dict , lowerCamelCase_ : Any , lo... | 105 | 0 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
A_ : Any = 0
for ch in input_str:
A_ : Union[str, Any] = ord(lowerCamelCase_ )
A_ : Tuple = pow(2 , lowerCamelCase_ )
# If we already turned on bit for current character's unicode... | 590 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _in... | 105 | 0 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__A = None
try:
import msvcrt
except ImportError:
__A = None
try:
import fcntl
except ImportError:
__A = None
# Backwa... | 469 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ : Optional[Any] = {
'''configuration_whisper''': ['''WHISPER_PRETRAINE... | 105 | 0 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class A( lowerCamelCase_ , unittest.TestCase ):
... | 70 |
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __UpperCAmelCase ( lowerCamelCase_ : np.ndarray , lowerCamelCase_ : np.ndarray ) -> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b , ... | 105 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def SCREAMING_SNAKE_CASE__ ( snake_case : np.ndarray , snake_case : np.ndarray )-> float:
'''simple docstring'''
return math.sqrt(sum(pow(... | 438 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCamelCase__ : str = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase_ ):
def __init__( self ,*snake_case__ ,**snake... | 105 | 0 |
import argparse
import json
from tqdm import tqdm
def A():
lowerCAmelCase_ = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" , type=lowerCamelCase_ , default="biencoder-nq-dev.json" , help="Path to raw DPR training data" ... | 122 |
def __UpperCAmelCase ( lowerCamelCase_ : List[str] , lowerCamelCase_ : Optional[Any] ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] = [0 for i in range(r + 1 )]
# nc0 = 1
SCREAMING_SNAKE_CASE_ : Dict = 1... | 105 | 0 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
lowerCAmelCase__ = logging.get_logger(__name__)
class snake_case__(lowerCamelCase_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *SCREAMING_SNAKE_CASE :... | 496 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class lowerCAmelCase_ :
def __init__( self ,snake_case__ ):
SCREAMING_SNAKE_CASE_ : Optional[int] = list_of_points
# Degree determines the flexibility of the curve.
... | 105 | 0 |
from scipy.stats import spearmanr
import datasets
__lowerCamelCase : List[str] = '''
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0 implying no correl... | 416 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_barthez im... | 105 | 0 |
'''simple docstring'''
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE__ ( __A , __A , _... | 495 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase__ : Optional[int] = {
'''configuration_bloom''': ['''BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BloomConfig''', '''BloomOnnxConfig'''],
}... | 105 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoin... | 541 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
UpperCamelCase__ : List[Any] = pytest.mark.integration
@pytest.mark.parametrize('path' , ... | 105 | 0 |
from __future__ import annotations
__magic_name__ = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],
'''G''': ['''C'''],
}
class ... | 576 |
import os
import numpy
import onnx
def __UpperCAmelCase ( lowerCamelCase_ : str , lowerCamelCase_ : Optional[Any] ) -> Optional[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : int = a.name
SCREAMING_SNAKE_CASE_ : Dict = ... | 105 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : int ) -> list[int]:
"""simple docstring"""
if length <= 0 or not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - ... | 405 |
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()
UpperCamelCase__ : Tuple = logging.get_logger(__name__)
UpperCamelCase__ : Option... | 105 | 0 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 590 |
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tenso... | 105 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenizat... | 469 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos.json'],
['d... | 105 | 0 |
from PIL import Image
def _SCREAMING_SNAKE_CASE ( lowercase : Image ):
'''simple docstring'''
lowerCamelCase_ = image.size
lowerCamelCase_ = 0
lowerCamelCase_ = image.load()
for i in range(lowerCamelCase_ ):... | 70 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCamelCase__ : Any = logging.get_logger(__name__)
UpperCamelCase__ : Any = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/ma... | 105 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( snake_case : str , snake_case : str )-> str:
'''simple docstring'''
if not (isinstance(lowerCamelCase_ , lowerCamelCase_ ) and isinstance(lowerCamelCase_ , lowerCamelCase_ )):
raise... | 438 |
import os
import sys
import unittest
UpperCamelCase__ : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dumm... | 105 | 0 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {'''vocab_file''': '''vocab.json'''}
lowerCamelCase__ = {
'''v... | 122 |
def __UpperCAmelCase ( lowerCamelCase_ : str ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = 0
for ch in input_str:
SCREAMING_SNAKE_CASE_ : Union[str, Any] = ord(lowerCamelCase_ )
SCREAMING_SNAKE_CASE_ : Tup... | 105 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['''XLMToken... | 496 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
Fla... | 105 | 0 |
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 TFModelTesterMixin... | 416 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, ... | 105 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( __A = 1_000 ) -> int:
_snake_case = 3
_snake_case = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
return result
if __name__ == "__main__":
print(F'''... | 495 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.mo... | 105 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Union[str, Any] =logging.get_logger(__name__)
__snake_case :List[Any] ={
'facebook/nllb-moe-54B': 'https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json',
}
class ... | 106 |
import os
import time
import numpy as np
import onnxruntime as ort
__snake_case :Any ='1'
__snake_case :List[str] ='0'
__snake_case :Union[str, Any] ='1'
__snake_case :Optional[Any] =ort.SessionOptions()
__snake_case :List[str] =ort.GraphOptimizat... | 106 | 1 |
# flake8: noqa
# Lint as: python3
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
query_table,
)
fr... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Tuple ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class lowerCAmelCase_... | 106 | 1 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
__snake_case :Union[str, Any] =logging.get_logger(__name__)
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : int , *__UpperCamelCas... | 106 |
import re
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
if len(re.findall('[ATCG]' , lowerCAmelCase__ ) ) != len(lowerCAmelCase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketr... | 106 | 1 |
from math import sqrt
def lowerCamelCase_ ( lowerCAmelCase__ : int ) -> bool:
'''simple docstring'''
assert isinstance(lowerCAmelCase__ , lowerCAmelCase__ ) and (
number >= 0
), "'number' must been an int and positive"
A = ... | 106 |
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_t... | 106 | 1 |
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
__snake_case :Dict =logging.get_logger(__name__)
__snake_case :Any ={'vo... | 106 |
from collections.abc import Sequence
def lowerCamelCase_ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A = n... | 106 | 1 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class lowerCAmelCase__ ( _lowerCamelCase ):
A_ : Optional[int... | 106 |
from typing import List
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : dict ) -> int:
'''simple docstring'''
A = {key: len(lowerCAmelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__ , lowerCAmelCase__ )}
... | 106 | 1 |
__snake_case :str ={
0: '0',
1: '1',
2: '2',
3: '3',
4: '4',
5: '5',
6: '6',
7: '7',
8: '8',
9: '9',
10: 'a',
11: 'b',
12: 'c',
13: 'd',
14: 'e',
15: 'f',
}
def lowerCamelCase_ ( lowerCAmelCase__ : float ) -> str... | 106 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 | 1 |
import logging
import os
from .state import PartialState
class lowerCAmelCase__ ( logging.LoggerAdapter ):
@staticmethod
def __UpperCamelCase ( __UpperCamelCase : Optional[Any] ) -> Union[str, Any]:
A = PartialState()
re... | 106 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case :Any =None
try:
import msvcrt
except ImportError:
__snake_case :Union[str, Any] =None
try:
import fcntl
except ImportError:
__snake_case :str ... | 106 | 1 |
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
def ... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :int ={'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 | 1 |
def lowerCamelCase_ ( lowerCAmelCase__ : list[int] ) -> int:
'''simple docstring'''
if not numbers:
return 0
if not isinstance(lowerCAmelCase__ , (list, tuple) ) or not all(
isinstance(lowerCAmelCase__ , lowerCAmelCase__ ) for numb... | 106 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase__ ( _lowerCamelCase , unittest.TestCase ):
A_ : int = CTRLTok... | 106 | 1 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case :Any =None
try:
import msvcrt
except ImportError:
__snake_case :Union[str, Any] =None
try:
import fcntl
except ImportError:
__snake_case :str ... | 106 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 1 |
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import torch
__snake_case :Dict... | 106 |
__snake_case :Any =256
# Modulus to hash a string
__snake_case :Optional[int] =1000003
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = len(lowerCAmelCase__ )
... | 106 | 1 |
from __future__ import annotations
def lowerCamelCase_ ( lowerCAmelCase__ : list[int] ) -> list[int]:
'''simple docstring'''
if len(lowerCAmelCase__ ) == 0:
return array
A , A = min(lowerCAmelCase__ ), max(lowerCAmelCas... | 106 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available... | 106 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
logging,
)
logging.set... | 106 |
from bisect import bisect
from itertools import accumulate
def lowerCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[Any] ) -> Union[str, Any]:
'''simple docstring'''
A = sorted(z... | 106 | 1 |
import math
def lowerCamelCase_ ( lowerCAmelCase__ : Union[str, Any] , lowerCAmelCase__ : List[str] ) -> List[Any]:
'''simple docstring'''
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.l... | 106 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__snake_case :str =False
class lowerCAmelCase__ ( unittest.TestCas... | 106 | 1 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer, D... | 106 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 106 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 106 |
import argparse
from collections import defaultdict
def lowerCamelCase_ ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : List[str] ) -> Union[str, Any]:
'''simple docstring'''
... | 106 | 1 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowerCA... | 106 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeni... | 106 | 1 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepiece
@slow # s... | 106 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : int , __UpperCamelCase : Callable... | 106 | 1 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 106 |
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_tensor
if is_torch_availabl... | 106 | 1 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase__ ( _lowerCamelCase , unittest.TestCase ):
A_ : int = CTRLTok... | 106 |
import math
import sys
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
A = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
A = binary_file.read()
... | 106 | 1 |
# 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 repositor... | 106 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 106 | 1 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
__snake_case :Any =TypeVar('T')
class lowerCAmelCase__ ( Generic[T] ):
def __init__( self : Union[str, Any] , __UpperCamelCase : list[T] ... | 106 |
import os
import time
import numpy as np
import onnxruntime as ort
__snake_case :Any ='1'
__snake_case :List[str] ='0'
__snake_case :Union[str, Any] ='1'
__snake_case :Optional[Any] =ort.SessionOptions()
__snake_case :List[str] =ort.GraphOptimizat... | 106 | 1 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipe... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Tuple ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class lowerCAmelCase_... | 106 | 1 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, tor... | 106 |
import re
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
if len(re.findall('[ATCG]' , lowerCAmelCase__ ) ) != len(lowerCAmelCase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketr... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :int ={'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 |
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_t... | 106 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case :List[Any] ={
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
}
try:
if no... | 106 |
from collections.abc import Sequence
def lowerCamelCase_ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A = n... | 106 | 1 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__snake_case :Dict =logging.get_logger(__name__)
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : Optional[Any] , *__UpperCamelCase : L... | 106 |
from typing import List
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : dict ) -> int:
'''simple docstring'''
A = {key: len(lowerCAmelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__ , lowerCAmelCase__ )}
... | 106 | 1 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 106 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 | 1 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : Dict ) -> str:
'''simple docstring'''
... | 106 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case :Any =None
try:
import msvcrt
except ImportError:
__snake_case :Union[str, Any] =None
try:
import fcntl
except ImportError:
__snake_case :str ... | 106 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case :int =logging.get_logger(__name__)
__snake_case :Dict ={
'facebook/xlm-roberta-xl': 'https://h... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :int ={'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 | 1 |
from __future__ import annotations
def lowerCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
if len(lowerCAmelCase__ ) < k or k < 0:
raise ValueError('Invalid Input' )
A = A ... | 106 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase__ ( _lowerCamelCase , unittest.TestCase ):
A_ : int = CTRLTok... | 106 | 1 |
def lowerCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] ) -> tuple[float, float]:
'''simple docstring'''
if not len(lowerCAmelCase__ ) == len(lowerCAmelCase__ ) == 3:
raise ValueError('Please enter a valid equation.' )
... | 106 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 1 |
from __future__ import annotations
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = get_failure_array(lowerCAmelCase__ )
# 2) Step through text searching for pattern
A , ... | 106 |
__snake_case :Any =256
# Modulus to hash a string
__snake_case :Optional[int] =1000003
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = len(lowerCAmelCase__ )
... | 106 | 1 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
import... | 106 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available... | 106 | 1 |
import requests
__snake_case :List[str] ='YOUR API KEY'
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str = giphy_api_key ) -> list:
'''simple docstring'''
A = '+'.join(query.split() )
A = F'''h... | 106 |
from bisect import bisect
from itertools import accumulate
def lowerCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[Any] ) -> Union[str, Any]:
'''simple docstring'''
A = sorted(z... | 106 | 1 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
... | 106 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__snake_case :str =False
class lowerCAmelCase__ ( unittest.TestCas... | 106 | 1 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Optional[int] ='T5Config'
class lowerCAmelCas... | 106 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Tuple =logging.get_logger(__name__)
__snake_case :str ={
'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json',
'microsoft/markuplm-large... | 106 |
import argparse
from collections import defaultdict
def lowerCamelCase_ ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : List[str] ) -> Union[str, Any]:
'''simple docstring'''
... | 106 | 1 |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCAmelCase__ ( _lowerCamelCa... | 106 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeni... | 106 | 1 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( _lowerCamelCase ):
A_ : List[Any] = (EulerDiscreteScheduler,)
A_ : str = 1_0
... | 106 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : int , __UpperCamelCase : Callable... | 106 | 1 |
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_tensor
if is_torch_availabl... | 106 |
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_tensor
if is_torch_availabl... | 106 | 1 |
from math import ceil
def lowerCamelCase_ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : int ) -> Tuple:
'''simple docstring'''
A = list(range(0 , lowerCAmelCase__ ) )
A = [item for sublist in list(device_map.valu... | 106 |
import math
import sys
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
A = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
A = binary_file.read()
... | 106 | 1 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers... | 106 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 106 | 1 |
def lowerCamelCase_ ( lowerCAmelCase__ : list , lowerCAmelCase__ : int = 0 ) -> list:
'''simple docstring'''
A = length or len(lowerCAmelCase__ )
A = False
for i in range(length - 1 ):
if list_data[i] > list_da... | 106 |
import os
import time
import numpy as np
import onnxruntime as ort
__snake_case :Any ='1'
__snake_case :List[str] ='0'
__snake_case :Union[str, Any] ='1'
__snake_case :Optional[Any] =ort.SessionOptions()
__snake_case :List[str] =ort.GraphOptimizat... | 106 | 1 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import Padd... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Tuple ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class lowerCAmelCase_... | 106 | 1 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> Any:
'''simple docstring'''
A = FileLock(str(tmpdir / 'foo.lock' ) )
A = FileLock(str... | 106 |
import re
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
if len(re.findall('[ATCG]' , lowerCAmelCase__ ) ) != len(lowerCAmelCase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketr... | 106 | 1 |
import os
import unicodedata
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
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case ... | 106 |
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_t... | 106 | 1 |
import math
import tensorflow as tf
from packaging import version
def lowerCamelCase_ ( lowerCAmelCase__ : Optional[int] ) -> Any:
'''simple docstring'''
A = tf.convert_to_tensor(lowerCAmelCase__ )
A = 0.5 * (1.0 + tf.math.erf(x ... | 106 |
from collections.abc import Sequence
def lowerCamelCase_ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A = n... | 106 | 1 |
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 TFModelTesterMixin, ids_tensor... | 106 |
from typing import List
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : dict ) -> int:
'''simple docstring'''
A = {key: len(lowerCAmelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__ , lowerCAmelCase__ )}
... | 106 | 1 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 106 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_rembert impor... | 106 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case :Any =None
try:
import msvcrt
except ImportError:
__snake_case :Union[str, Any] =None
try:
import fcntl
except ImportError:
__snake_case :str ... | 106 | 1 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :int ={'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 | 1 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__snake_case :Tuple =HfArgumentParser(InitializationArguments)
__snake_case :Optional[int] =parser.parse_args()
# Load codeparrot tok... | 106 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase__ ( _lowerCamelCase , unittest.TestCase ):
A_ : int = CTRLTok... | 106 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case :Optional[int] ={
'configuration_jukebox': [
'JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP',
'JukeboxConfig',
'JukeboxPriorConfig',
'Jukebox... | 106 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 1 |
from typing import List
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : dict ) -> int:
'''simple docstring'''
A = {key: len(lowerCAmelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__ , lowerCAmelCase__ )}
... | 106 |
__snake_case :Any =256
# Modulus to hash a string
__snake_case :Optional[int] =1000003
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = len(lowerCAmelCase__ )
... | 106 | 1 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizerOutput
from ... | 106 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available... | 106 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__snake_case :List[str] ={
'configuration_mobilevit': ['MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MobileViTConfig'... | 106 |
from bisect import bisect
from itertools import accumulate
def lowerCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[Any] ) -> Union[str, Any]:
'''simple docstring'''
A = sorted(z... | 106 | 1 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__snake_case :Tuple =logging.get_logger(__name__)
__snake_case :Dict ={'voc... | 106 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__snake_case :str =False
class lowerCAmelCase__ ( unittest.TestCas... | 106 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_proc... | 106 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 106 | 1 |
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