code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
... | 16 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : Dict = {
"configuration_roformer": ["ROFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "... | 273 | 0 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vision_... | 362 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_A = logging.get_logger(__name__)
_A = {"vocab_file": "vocab.txt", "... | 137 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_SCREAMING_SNAK... | 314 |
from functools import reduce
_SCREAMING_SNAKE_CASE : Any = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''
... | 314 | 1 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
A_ : set[int] = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
A_ : set[int] = set()
return any(
node not in visited and depth_first_search(SCREAMING_SNAKE_CASE , SCREAMING... | 65 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
if num <= 0:
A_ : Optional[int] = f'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(SCREAMING_SNAKE_CASE )
A_ : Union[str, Any] = [True] * (... | 65 | 1 |
import math
def lowerCamelCase__ ( _A ):
'''simple docstring'''
snake_case_ = [True] * n
snake_case_ = False
snake_case_ = False
snake_case_ = True
for i in range(3 , int(n**0.5 + 1 ) , 2 ):
s... | 187 |
import functools
def lowerCamelCase__ ( _A , _A ):
'''simple docstring'''
if not isinstance(_A , _A ) or not all(isinstance(_A , _A ) for day in days ):
raise ValueError("The parameter days should be a list of integers" )
... | 187 | 1 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def __lowerCamelCase ( UpperCamelCase__ ):
'''simple docstring'''
snake_case_ = []
snake_case_ = []... | 200 |
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
sna... | 200 | 1 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
_lowerCAmelCase = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def _SCREAMING_SNAKE_CASE ( ):
"""simple docstring"""
lowerCAmelCase__ : str = os.path.dirname(os.pa... | 37 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_lowerCAmelCase = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems... | 37 | 1 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
BertT... | 288 |
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from transform... | 288 | 1 |
from __future__ import annotations
class __lowercase :
"""simple docstring"""
def __init__( self , A ) -> None:
'''simple docstring'''
lowerCamelCase = order
# a_{0} ... a_{k}
lowerCamelCase = [1.0] + [0.0] * order
#... | 252 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import loggin... | 4 | 0 |
'''simple docstring'''
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be check... | 352 |
'''simple docstring'''
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 OptionalDepend... | 48 | 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
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'facebook/le... | 205 |
# 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 ... | 205 | 1 |
'''simple docstring'''
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassifica... | 357 |
'''simple docstring'''
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
_lowercase = """src/transformers"""
# This is to make... | 229 | 0 |
__A ={str(digit): digit**5 for digit in range(1_0)}
def a ( _UpperCAmelCase : int ):
'''simple docstring'''
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_UpperCAmelCase ) )
def a ( ):
''... | 226 | from collections import defaultdict
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = 1
SCREAMING_SNAKE_CASE_ : Tuple = True
for v in tree[start]:
if v not in visited:
ret += dfs(lowerCAmelCase )
if r... | 18 | 0 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import ... | 363 |
'''simple docstring'''
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Optional[int] = [3_1, 2_8, 3_1, 3_0, 3_1, 3_0, 3_1, 3_1, 3_0, 3_1, 3_0, 3_1]
_lowerCAmelCase : int = 6
_... | 25 | 0 |
from __future__ import annotations
from collections.abc import Generator
def SCREAMING_SNAKE_CASE_ ( ) -> Generator[int, None, None]:
"""simple docstring"""
a_ : dict[int, int] = {}
a_ : Tuple = 2
while True:
... | 32 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase : list[list[int]] = [[0 for _ in range(lowerCAmelCase__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__UpperCAmelCa... | 254 | 0 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOut... | 342 | import numpy as np
import datasets
_snake_case = '''
Compute the Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.
It was introduced by Prof. P. C. Mah... | 342 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ : Union[str, Any] = {
"""configuration_funnel""": ["""FUNNEL_PRETRAIN... | 75 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''microsoft/unispeech-large-1500h-cv''': (
'''https://huggingface.c... | 72 | 0 |
"""simple docstring"""
import argparse
from collections import defaultdict
import yaml
lowercase__ = 'docs/source/en/_toctree.yml'
def __a ( _SCREAMING_SNAKE_CASE ) ->List[Any]:
a__: str = defaultdict(_SCREAMING_SNAKE_CASE )
for doc in model_doc:
... | 203 | """simple docstring"""
import math
def __a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->Optional[int]:
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(_SCREAMING_SNAKE_CASE )
else:
if x == 0: # 0 ... | 203 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A__: List[Any] = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xl... | 149 |
import doctest
from collections import deque
import numpy as np
class _a :
"""simple docstring"""
def __init__( self: Union[str, Any] ):
'''simple docstring'''
UpperCamelCase__: int = [2, 1, 2, -1]
UpperCa... | 149 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Any = logging.get_logger(__name__)
lowercase__ : List[Any] = {
'''funnel-transformer/small''': '''https://huggingface.co/funnel-transformer/small/resolve/main/config.json''',
'''... | 351 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 155 | 0 |
'''simple docstring'''
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase__ ( lowercase__ ):
"""simple docstring"""
def __init__( self , snake_case , snake_case ... | 311 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
a : int = datasets.load_iris()
a : Union[str, Any] = np.array(data["data"])
a : Optional[Any] = np.array(data["target"])
a... | 311 | 1 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""google/pix2struct-textcaps-base""": (
"""https://huggingface.co/goog... | 353 |
'''simple docstring'''
from math import factorial
def _A ( _lowerCAmelCase = 20 ):
"""simple docstring"""
__lowercase =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
__lowercase =n // 2
return int(facto... | 48 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_M... | 322 | '''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 67 | 0 |
"""simple docstring"""
from collections import deque
from math import floor
from random import random
from time import time
class UpperCamelCase :
def __init__( self) -> Dict:
snake_case_ = {}
def a_ ( self, lowerCAmelCase__, lowerCAmelCase_... | 351 | """simple docstring"""
from math import pi
def UpperCAmelCase ( UpperCAmelCase , UpperCAmelCase ) -> float:
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 312 | 0 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingface... | 192 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def UpperCamelCase (lowercase_: Optional[int] , lowercase_: Union[str, Any] , lowercase_: Optional[Any] ) -> Tu... | 192 | 1 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ = 2000000 )-> int:
'''simple docstring'''
_UpperCAmelCase : int = [0 for i in range(n + 1 )]
_UpperCAmelCase : int = 1
_UpperCAmelCase : Any = 1
f... | 349 |
'''simple docstring'''
def snake_case_ ( lowerCAmelCase_ )-> int:
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise TypeError("""only integers accepted as input""" )
else:
_UpperCAmelCase : Dict ... | 349 | 1 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class a__ ( unittest.TestCase ):
A = inspect.getfile(accelerate.test_... | 18 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A: List[str] = logging.get_l... | 109 | 0 |
from __future__ import annotations
from typing import Any
class _snake_case ( SCREAMING_SNAKE_CASE__ ):
pass
class _snake_case :
def __init__( self , _lowerCamelCase ):
a :Any = data
a :Node | None = None
def __iter__( self ):
... | 359 |
# 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 a... | 281 | 0 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class __snake_case ( lowerCAmelCase , unittest.TestCase ):
_a :... | 20 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowerCamelCase_ ( _a : List[Any] ):
'''simple docstring'''
UpperCAmelCase_ : Optional[int] = [
"""decoder.version""",
... | 345 | 0 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Optional[int] = logging.get_logger(__name__)
__A : Optional[int] = {
'''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/co... | 27 |
"""simple docstring"""
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import M... | 27 | 1 |
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
lowerCamelCase__ = logging.get_logger(__name__)
class A__ :
lowercase = None
@experimental
def lowerCAmelCase__ ( ... | 212 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class A__ :
@property
def _lowerCamelCase ... | 212 | 1 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torc... | 213 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(F... | 213 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase = {'''configuration_plbart''': ['''PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 74 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextI... | 96 | 0 |
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class __lowercase (tf.keras.layers.Layer ):
"""s... | 162 |
from typing import Any
def a__ ( A__, A__, A__, A__, A__, ):
_validation(
A__, A__, A__, A__, A__, )
# Creates data structures and fill initial step
SCREAMING_SNAKE_CASE_ : dict = {}
SCREAMING_SNAKE_CASE_ :... | 162 | 1 |
"""simple docstring"""
import inspect
import unittest
class UpperCAmelCase_ ( unittest.TestCase):
def _UpperCAmelCase ( self ) -> List[str]:
try:
import diffusers # noqa: F401
except ImportError:
assert F... | 77 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case__ ( __lowerCamelCase : List[Any] , __lowerCam... | 238 | 0 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def UpperCamelCase_ ( A__ : Union[str, Any] , A__ : Dict , A__ : Optional[int] ):
'''simple docstring'''
lowerCAmelCa... | 354 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licen... | 89 | 0 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
Juma... | 8 |
def _a ( UpperCAmelCase ) -> bool:
"""simple docstring"""
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('Program to check whether a number is a Perfect number or not...')
_A : ... | 142 | 0 |
"""simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtr... | 361 |
"""simple docstring"""
from __future__ import annotations
lowerCAmelCase_ = '#'
class __A :
'''simple docstring'''
def __init__( self : str ) -> None:
"""simple docstring"""
lowercase__ : dict... | 302 | 0 |
UpperCAmelCase : List[str] = 2_56
# Modulus to hash a string
UpperCAmelCase : Optional[Any] = 1_00_00_03
def _SCREAMING_SNAKE_CASE ( a , a ) -> Any:
__A : Optional[Any] = len(__UpperCamelCase )
__A : List[Any] = ... | 280 |
import cva
import numpy as np
class _a :
"""simple docstring"""
def __init__( self : Any , UpperCAmelCase : float , UpperCAmelCase : int ):
if k in (0.04, 0.06):
A_ = k
A_ ... | 312 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json',
}
class... | 366 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase = logging.get_logger(__name__)
_UpperCAmelCase = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
# See all BioGPT models at http... | 232 | 0 |
"""simple docstring"""
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class _UpperCAmelCase ( unittest.TestCase ):
'''simple docstring'''
def __lowerCAmelCase ( self ) -> ... | 263 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCAmelCase :Optional[int] = logging.get_logger(__name__)
class _UpperCAmelCase ( a ):
'''simple docstring'''
def __init__( self ... | 263 | 1 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
return np.dot(lowercase__ , lowercase__ )
class __UpperCamelCa... | 354 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase_... | 57 | 0 |
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_C... | 195 |
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
if not isinstance(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
raise TypeError('Input value must be an \'int\' type' )
lowercase = 0
while number:
position += 1
number >>= 1
return position
if __name__ ==... | 195 | 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 UpperCAmelCase ( unittest.TestCase ):
... | 356 | from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDependencyNotAvailable()
... | 192 | 0 |
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
require_torch_mi... | 76 |
import os
def lowerCamelCase__ ( ):
with open(os.path.dirname(_a) + "/p022_names.txt") as file:
SCREAMING_SNAKE_CASE : List[str] = str(file.readlines()[0])
SCREAMING_SNAKE_CASE : List[Any] = names.replace("\"" , "").split(",")
names.sort()
SCREAMING_SNAKE_... | 76 | 1 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ ) -> bool:
'''simple docstring'''
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print("Program to check whether a number is a Perfect number or... | 361 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class snake_case__ :
"""simple docstring"""
def __init__( self : Dict , UpperCamelCase__ : int , UpperCamelCase__ : MutableSeque... | 83 | 0 |
"""simple docstring"""
lowerCAmelCase__ : List[Any] = '''Input must be a string of 8 numbers plus letter'''
lowerCAmelCase__ : Any = '''TRWAGMYFPDXBNJZSQVHLCKE'''
def a_ ( lowerCamelCase ):
if not isinstance(_lowercase , _lowercase ):
UpperCAmel... | 98 |
'''simple docstring'''
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 Tokenize... | 318 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_a... | 368 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import... | 156 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : List[str] = {
'''configuration_mobilebert''': [
'''MOBILEBERT_PR... | 264 | import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('.')
def __lowercase ( lowerCamelCase : Any ):
UpperCamelCase_ : Union[str, Any] = test_file.split(os.path.sep ... | 175 | 0 |
"""simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class UpperCAmelCase_ ( _lowercase):
def _UpperCamelCase ( self : Optional[Any] , __UpperCamelCase : str ) -> List[str]:
... | 351 | """simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCAmelCase_ ( _lowercase):
def __init__( self : Any , __UpperCamelCase : Optional... | 54 | 0 |
def a ( _UpperCAmelCase : Optional[Any] , _UpperCAmelCase : int , _UpperCAmelCase : Tuple , _UpperCAmelCase : List[Any] , _UpperCAmelCase : List[str] ):
'''simple docstring'''
if index == number_of_item... | 226 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__a = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies # noqa: E402
# This is the reference code that wi... | 337 | 0 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , **_SCREAMING_SNAKE_CASE ):
_snake_case = AutoConfig.from_pretrained(_SCREAMING_SNAKE_CASE , **_SCREAMING_SNAK... | 359 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
if not (isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) and isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE )):
raise ValueError("""longest_comm... | 270 | 0 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/license... | 223 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .toke... | 223 | 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
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_C... | 367 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_comm... | 88 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowerCamelCase ( a ):
"""simple docstring"""
UpperCAmelCase_ : Optional[Any] =["image_processor", "tokenizer"]
UpperCAmelCase_ : i... | 326 |
def lowerCAmelCase__( lowercase : List[Any] , lowercase : Optional[Any] , lowercase : Optional[int] , lowercase : str , lowercase : List[Any] , lowercase : List[str] ) -> int:
if index == r:
for j in range(lowercase ):
prin... | 326 | 1 |
import math
class lowerCamelCase__ :
def _lowerCamelCase ( self : Optional[Any] , _a : list[list[float]] , _a : list[int] ):
a__: str =0.0
a__: Dict =0.0
for i in range(len(_a ) ):
... | 42 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
__UpperCAmelCase = logging.getLogger(__name... | 42 | 1 |
"""simple docstring"""
from collections import namedtuple
__A : Dict = namedtuple("from_to", "from_ to")
__A : Any = {
"cubicmeter": from_to(1, 1),
"litre": from_to(0.001, 1000),
"kilolitre": from_to(1, 1),
"gallon": from_to(0.0_0454, 264.172),
... | 260 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def lowercase ( _SCREAMING_SNAKE_CASE : Any ):
'''simple docstring'''
_UpperCAmel... | 260 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase = 60_08_51_47_51_43 ) -> int:
try:
UpperCAmelCase__ : List[Any] = int(lowerCAmelCase )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable to int.""" )
if n <= 0:
... | 166 |
"""simple docstring"""
def a__ ( lowerCAmelCase ) -> bool:
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
UpperCAmelCase__ : Tuple = F"""Input value of [number={number}] must be an integer"""
raise TypeError(lowerCAmelCase )
if number < 0:
... | 166 | 1 |
# 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.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controln... | 127 |
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 ):
... | 127 | 1 |
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class _a :
def __init__( self : int, lowerCAmelCase__ : Collection[float] | None = None ) -> None:
... | 364 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelin... | 128 | 0 |
from collections import deque
from math import floor
from random import random
from time import time
class _snake_case :
def __init__( self ):
a :Optional[int] = {}
def SCREAMING_SNAKE_CASE__ ( self , _lowerCamelCase , _lowerCamelCase , _lowe... | 94 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class UpperCAmelCase__ ( logging.LoggerAdapter):
@staticmethod
def __lowerCamelCase ( lowercase ) -> Dict:
__UpperCamelCase = PartialState()
return not main_process_... | 349 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__UpperCAmelCase :List[str] = logging.get_logger(__name__)
__UpperCAmelCase :int = {
"speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-c... | 350 |
'''simple docstring'''
import requests
__UpperCAmelCase :Union[str, Any] = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def _a ( _lowercase : str ):
'''simple docstring'''
__UpperCAmelCase : Unio... | 240 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _lowerCamelCase ( unit... | 331 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoMode... | 331 | 1 |
"""simple docstring"""
from collections.abc import Callable
class lowercase :
'''simple docstring'''
def __init__( self , _snake_case = None ) -> None:
"""simple docstring"""
UpperCAmelCase = []
... | 369 |
# Function to print upper half of diamond (pyramid)
def _lowerCAmelCase ( A__: str ):
'''simple docstring'''
for i in range(0 , A__ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(''' ''' , end='''''' )
fo... | 152 | 0 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCAmelCase_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_copies # noqa: E402
# This is the reference code... | 12 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : str = logging.get_logger(__name__)
_lowercase : Dict = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swin... | 332 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.c... | 354 |
'''simple docstring'''
from math import isqrt
def lowercase (_A ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(_A ) + 1 ) )
def lowercase (_A = 1_0**6 ):
... | 25 | 0 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_im... | 2 |
class _lowercase :
"""simple docstring"""
def __init__( self : List[Any] , __lowerCamelCase : int ):
'''simple docstring'''
lowerCamelCase__ : Optional[Any] = size
lowerCamelCase__ : Lis... | 184 | 0 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
if num < 0:
return False
_UpperCamelCase : int = num
_UpperCamelCase : int = 0
while num > 0:
_UpperCamelCase : int = rev_num * 1_0 + (num % 1_0)
num //... | 350 |
'''simple docstring'''
from datetime import datetime
import requests
def A__ ( UpperCAmelCase_ ):
_UpperCamelCase : List[Any] = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
_UpperCamelCase : Optional[int] = requests.get(base_url + ur... | 236 | 0 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def _A ( _lowerCAmelCas... | 166 |
from abc import ABC, abstractmethod
from typing import List, Optional
class a_ ( a__ ):
"""simple docstring"""
def __init__( self ) ->List[str]:
# test for the above condition
self.test()
def __lowerCAmelCase ( self ... | 313 | 0 |
'''simple docstring'''
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 349 |
'''simple docstring'''
A_ : Optional[Any] = """0.21.0"""
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from ... | 349 | 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_proce... | 9 |
def _UpperCamelCase ( lowercase__ , lowercase__ , lowercase__=False ):
if isinstance(lowercase__ , lowercase__ ) and isinstance(lowercase__ , lowercase__ ):
__SCREAMING_SNAKE_CASE : List[str] = len(set_a.intersectio... | 9 | 1 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
_lowerCAmelCase : Union[str, Any] = logging.getLogger(__name__)
class __magic_name__ ( lowerCamelCase__ )... | 355 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : int = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'''microsoft/git-base''': '''https://huggingface.co/microsoft/git-base/resol... | 70 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__lowerCAmelCase = {
'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}
try:
if not is_torch_availa... | 341 |
'''simple docstring'''
__lowerCAmelCase = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE ):
# Make sure the supplied data is a bytes-like object
if not isinstance(_SCREAMING_SNAKE_CASE , ... | 341 | 1 |
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : list ) -> list:
UpperCAmelCase_ = len(__UpperCamelCase )
for _ in range(__UpperCamelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
U... | 371 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
_lowerCamelCase = logging.getLogger(__name__)
if __name__ == "__main... | 177 | 0 |
"""simple docstring"""
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class lowerCamelCase ( unittest.TestCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self: Optional[Any] ) -> Union[str, Any]... | 66 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase : List[str] = {"""configuration_vit_msn""": ["""VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMSNConfig"""]}
try:
if not is_torch_available():
raise Opti... | 14 | 0 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPM... | 359 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipelin... | 184 | 0 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class A (unittest.TestCase ):
'''... | 274 |
'''simple docstring'''
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __lowerCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) -> np.array:
_a : Optional[int] = f"""{sampling_rate}"""
_a ... | 89 | 0 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class a ( a__ ):
# to overwrite at feature extractactor specific tes... | 370 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Dict = {
'''configuration_mctct''': ['''MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MCTCTConfig'''],
'''feature_extraction_mctc... | 309 | 0 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
snake_case_ = logging.get_logger(__name__)
snake_case_ = {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokeni... | 214 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_UpperCAmelCase : int = {"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}
try:
if not is_torch_available():
rai... | 236 | 0 |
import cmath
import math
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[Any] = math.radians(_lowerCamelCase )
_lowerCAmelCase : Optional[Any] ... | 356 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
"configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig", "ConvNextOnnxConfig"]
}... | 300 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import Conf... | 70 |
"""simple docstring"""
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCAmelCase_ = version.parse(importlib_metadata.version('nltk'))
if NLTK_VERSION >= version.Version('3.6.4'):
f... | 16 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,... | 366 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common im... | 55 | 0 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from ... | 34 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
... | 34 | 1 |
"""simple docstring"""
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBer... | 259 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase=() , _UpperCamelCase=None , _UpperCamelCa... | 259 | 1 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowerCamelCase__ : int ) -> list[int]:
lowerCamelCase_ : int =[True] * limit
lowerCamelCase_ : List[str] =False
lowerCamelCase_ : List[Any] ... | 144 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.p... | 227 | 0 |
"""simple docstring"""
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torch_neuron... | 54 | """simple docstring"""
# limitations under the License.
# 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 .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils impor... | 54 | 1 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( UpperCamelCase : list[int] , UpperCamelCase : int , UpperCamelCase : int , UpperCamelCase : int ):
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and ar... | 109 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A: List[str] = logging.get_l... | 109 | 1 |
from __future__ import annotations
lowercase : Dict = list[tuple[int, int]]
lowercase : List[str] = [
[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],
[0, 0, 1, 0, 0, 0, 0],
[1, ... | 350 |
lowercase : Optional[int] = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '''flax>=0.4.1''... | 36 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils... | 105 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
UpperCAmelCase : Dict =TypeVar("""T""")
class _lowercase (Generic[T] ):
'''simple docstring'''
def __init__( self , snake_case__ ):
... | 128 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'tiiuae/falcon-7b': 'https://huggingface.co/tiiuae/falcon-7b/r... | 370 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase_ = 5_0_0_0_0
lowercase_ = 5_0_0_0
lowercase_ ,lowercase_ = os.path.split(__file__)
lowercase_ = os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.replace... | 194 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import log... | 56 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
__snake_case = get_tes... | 310 | 0 |
"""simple docstring"""
import math
import os
import sys
def lowercase__ ( snake_case_ :str ):
__UpperCAmelCase = ''''''
try:
with open(snake_case_ , '''rb''' ) as binary_file:
__UpperCAmelCase = binar... | 353 |
"""simple docstring"""
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_lowercase : int = logging.get_logger(__name__)
_lowercase : Tuple ... | 86 | 0 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class __UpperCAmelCase (_UpperCAmelCase ):
def UpperCamelCase ( self: Any , UpperCAmelCase_: Union[str, Any] ... | 306 | """simple docstring"""
from ..utils import DummyObject, requires_backends
class _A ( metaclass=lowerCAmelCase ):
snake_case__ : List[str] = ['onnx']
def __init__( self , *__lowerCAmelCase , **__lowerCAmelCase ):
... | 197 | 0 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def a__ ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : dict ):
'''simple docstring'''
lowerCAmelCase : Any = BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE , params=SC... | 133 |
"""simple docstring"""
def a__ ( SCREAMING_SNAKE_CASE : list[int] ):
'''simple docstring'''
lowerCAmelCase : str = len(SCREAMING_SNAKE_CASE )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE ):
if nu... | 133 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json',
}
class SCREAMING_SNAKE_CASE... | 24 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_... | 24 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class __UpperCAmelCase :
'''simple docstring'''
__lo... | 18 | '''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
... | 18 | 1 |
import logging
from transformers.configuration_utils import PretrainedConfig
__A = logging.getLogger(__name__)
class _SCREAMING_SNAKE_CASE ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "masked_bert"
def __init__(self : Dict , UpperCAmelCase_ ... | 10 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class UpperCamelCase_ ( unittest.TestCase):
"""s... | 54 | 0 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase ) -> Any:
'''simple docstrin... | 313 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase ) -> list:
'''simple docstring'''
if any(not isinstance(__lowerCAmelCase , __lowerCAmelCase ) or x < 0 for x in sequence ):
raise TypeError("""Sequence must be list of non-negative integ... | 313 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE__ :
def __init__( self , _SCREAMING_SNAKE_CASE ) -> int:
'''simple docstring'''
UpperCAmelCase : Optional[int] = size
# approximate the overall size of segme... | 109 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_ava... | 156 | 0 |
"""simple docstring"""
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def lowerCamelCase ( _UpperCamelCase : str , _UpperCamelCase : str , _UpperCamelCase : int , _UpperCamelCase : Dict , _UpperCa... | 360 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvaila... | 320 | 0 |
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