code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel... | 501 |
'''simple docstring'''
from collections.abc import Callable
def __snake_case (__UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ):
"""simple docstring"""
lowerCamelCase_ : float = a
lowerCamelCase_ : float = b
if function(__UpperCAmelCase... | 501 | 1 |
def lowerCamelCase( a__):
return " ".join(
''''''.join(word[::-1]) if len(a__) > 4 else word for word in sentence.split())
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words('''Hey wollef sroirraw''')) | 191 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_u... | 191 | 1 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def lowercase_ ( _UpperCamelCase , _UpperCamelCase=None ):
'''simple docstring'''
__lowercase = None
if token is not None:
__... | 639 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 110 | 0 |
'''simple docstring'''
import math
import random
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase = False ):
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
lowerCamelCase__ = 0.02
def __lowerCAmel... | 40 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
... | 40 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase ( metaclass=__snake_case ):
"""simple docstring"""
__snake_case = ['onnx']
def __init__( self , *_lowercase , **_lowercase ) -> List[Any]:
... | 434 | def lowerCAmelCase( __lowerCamelCase , __lowerCamelCase ):
_validate_point(__lowerCamelCase )
_validate_point(__lowerCamelCase )
if len(__lowerCamelCase ) != len(__lowerCamelCase ):
raise ValueError('Both points must be in the same n-dimensional space' )
return ... | 559 | 0 |
import socket
def a__ ( ):
'''simple docstring'''
__magic_name__ = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
__magic_name__ = socket.gethostname()
__magic_name__ = 12312
sock.connect((host, port) )
sock.send(b"""Hello s... | 702 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCAmelCase : List[str] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': ['Cani... | 76 | 0 |
'''simple docstring'''
from collections.abc import Sequence
from queue import Queue
class lowercase_ :
"""simple docstring"""
def __init__( self : Tuple, UpperCamelCase__ : Any, UpperCamelCase__ : List[Any], UpperCamelCase__ : Optional[int], UpperCamelCa... | 107 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
UpperCAmelCase =logging.get_logge... | 617 | 0 |
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
__UpperCamelCase : Any = {
... | 34 | import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
__UpperCamelCase : str = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
'text-classification... | 34 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.uti... | 426 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
'''facebook/xglm-564M''': '''https://huggingface.co/facebook/xglm-564M/resolve/main/config.json''',
... | 426 | 1 |
from __future__ import annotations
from cmath import sqrt
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ) -> tuple[complex, complex]:
if a == 0:
raise ValueError('Coefficient \'a\' must not be zero.' )
__lowerCamelCase ... | 337 |
import argparse
import json
import subprocess
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ ) -> Tuple:
__lowerCamelCase : List[str] = []
__lowerCamelCase : List[str] = (
F"curl -H \"Accept: application/v... | 337 | 1 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformer... | 18 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCamelCase__: str = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchm... | 127 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFXL... | 707 |
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 transformers.models... | 369 | 0 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase ) -> list:
SCREAMING_SNAKE_CASE__ : List[str] = int(__lowerCAmelCase )
if n_element < 1:
SCREAMING_SNAKE_CASE__ : Tuple = ValueError("""a should be a positive number""" )
... | 680 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logg... | 680 | 1 |
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
lowercase_ : Any = lo... | 652 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
lowercase_ : Optional[int] = object()
# For specifying empty leaf dict `{}`
lowercase_ : List[Any] = ... | 652 | 1 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
__A : Union[str, Any] = Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io # noqa... | 343 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_encoder import M... | 343 | 1 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_co... | 709 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTester... | 400 | 0 |
"""simple docstring"""
import sys
import turtle
def lowerCAmelCase_ ( UpperCamelCase__ : tuple[float, float] , UpperCamelCase__ : tuple[float, float] ):
"""simple docstring"""
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowerCAmelCase_ ... | 616 |
"""simple docstring"""
def lowerCAmelCase_ ( UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : int ):
"""simple docstring"""
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation... | 616 | 1 |
"""simple docstring"""
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
A__ : List[str] = WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])
def _snake_case ... | 244 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import D... | 244 | 1 |
from __future__ import annotations
def lowerCamelCase__ ( __lowerCamelCase : list[float] ):
if len(__lowerCamelCase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i <= 0 for i in nums ):
r... | 63 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class a :
"""simple docstring"""
a : int
a : Node | None = ... | 63 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Mask2Fo... | 667 |
'''simple docstring'''
def UpperCAmelCase__ ( UpperCAmelCase__ ) -> int:
assert (
isinstance(UpperCAmelCase__, UpperCAmelCase__ ) and number_of_steps > 0
), F'''number_of_steps needs to be positive integer, your input {number_of_steps}'''
if number_... | 667 | 1 |
"""simple docstring"""
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def __A ( a_ :BertModel , a_ :str , a_ :str) -> str:
__a : List[str] = ('''dense.weigh... | 52 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_a : Tuple = logging.get_logger(__name__)
_a : Optional[int] = {
'xlm-mlm-en-204... | 213 | 0 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=A_ ):
"""simple docstring"""
UpperCAmelCase__ : str = ["torch", "torchsde"]
def __init__( self , *A_ , **A_ ) -> Dict:
requires_backen... | 682 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_util... | 682 | 1 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class lowercase_ :
"""simple docstring"""
def __init__( self : Optional[int] ,lowercase__ : list[tuple[float, float]] ):
__lowercase = list_of_points
# D... | 41 |
'''simple docstring'''
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to... | 41 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase ... | 720 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 152 | 0 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import ... | 504 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :list[list[float]] ) -> list[list[float]]:
__lowerCAmelCase : list[list[float]] = []
for data in source_data:
for i, el in enumerate(SCREAMING_SNAKE_CASE ):
if len(SCREAMING_SNAKE_CASE ) < i + 1:
da... | 504 | 1 |
def lowercase_ ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase=False ):
'''simple docstring'''
if isinstance(_UpperCamelCase , _UpperCamelCase ) and isinstance(_UpperCamelCase , _UpperCamelCase ):
__lowercase = len(set_a.intersection(_UpperC... | 527 |
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from... | 527 | 1 |
from ....utils import logging
a_ : str = logging.get_logger(__name__)
class lowerCamelCase__ ( lowercase_):
"""simple docstring"""
def __init__(self , __a , __a=None , __a=20_48 ):
'''simple docstring'''
... | 623 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCAmelCase ( lowercase_ ):
"""simple docstring"""
_lowercase : Optional[int] = ''''''
_lowercase : str = ... | 654 | 0 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def A (__A : Union[str, Any] = "AAPL" ) -> Union[str, Any]:
"""simple docstring"""
UpperCAmelCase_ = F"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
... | 701 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
snake_case_ : Tuple = False
class __snake_case ( unittest.Test... | 169 | 0 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configu... | 8 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 1 |
def snake_case ( lowerCamelCase ):
'''simple docstring'''
__lowercase = len(lowerCamelCase )
__lowercase = sum(lowerCamelCase )
__lowercase = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 , n + 1 ):
... | 711 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggi... | 53 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=UpperCamelCase_ ):
_a = ["""flax""", """transformers"""]
def __init__( self , *UpperCamelCase , **UpperCamelCase ) -> List[str... | 539 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import 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, random_attention_... | 680 | 0 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def A__ ( __A , __A , __A = False ):
'''simple docstring'''
if radian_mode:
return [magnitude * cos(__A ), magnitude * sin(__A... | 704 | lowerCAmelCase : Tuple =0 # The first color of the flag.
lowerCAmelCase : Union[str, Any] =1 # The second color of the flag.
lowerCAmelCase : Any =2 # The third color of the flag.
lowerCAmelCase : List[str] =(red, white, blue)
def A__ ( __A... | 15 | 0 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def UpperCAmelCase__ ( UpperCAmelCase_ : Union[str, Any] ) -> List[Any]:
def wrapper(*UpperCAmelCase_ ... | 13 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {'v... | 321 | 0 |
"""simple docstring"""
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging... | 183 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _UpperCAmelCase ( SCREAMING_SNAKE_CASE_ ):
@staticmethod
@abstractmethod
def a_ ( lowercase_ ) -> Optional[Any]:
raise NotIm... | 183 | 1 |
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import con... | 612 |
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/google/pix2struct-textcaps-ba... | 612 | 1 |
from ..utils import DummyObject, requires_backends
class __UpperCAmelCase ( metaclass=snake_case__ ):
"""simple docstring"""
lowercase = ["""onnx"""]
def __init__( self , *SCREAMING_SNAKE_CASE , **SCREAMING_SNAK... | 713 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : Tuple = logging.get_logger(__name__)
__a : List[str] = {
"""uclanlp/visualbert-vqa""": """https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json""",
... | 414 | 0 |
'''simple docstring'''
def lowerCAmelCase (__A , __A):
"""simple docstring"""
while b:
_a , _a = b, a % b
return a
def lowerCAmelCase (__A , __A):
"""simple docstring"""
return a if b == 0 else euclidean_gcd_recursiv... | 11 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6'''))
def lowerCAmelCase (__A):
"""simple docstring"""
_a = credit_card_number
_a ... | 11 | 1 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 709 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transf... | 623 | 0 |
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> int:
'''simple docstring'''
if len(_lowerCAmelCase ) < k or k < 0:
raise ValueError("Invalid Input" )
__snake_case = ... | 371 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCAmelCase ( ) -> Tuple:
'''simple docstring'''
import os as original_os
from os import path as original_path
from os impor... | 371 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A : List[Any] = logging.get_logger(__name__)
A : List[str] = {
"kssteven/iber... | 282 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sag... | 282 | 1 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def __lowercase ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = False ) -> Optional[Any]:
'''simple docstring'''
if radian_mode:
return [m... | 321 | '''simple docstring'''
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from ... | 152 | 0 |
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
snake_case_ ... | 262 |
def A__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = False ) -> bool:
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n % 1_0 not in (1, 3, 7, 9): # can quickly check last digit
return False
if n > 3_3_1_7_0_4_4_0_6_4_6_7... | 262 | 1 |
"""simple docstring"""
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase ) -> str:
"""simple docstring"""
__UpperCAmelCase : list[list[str]] = [[] for _ in range(UpperCamelCase )]
__UpperCAmelCase : Union[str, Any] ... | 77 | from pathlib import Path
import fire
def lowerCAmelCase_ ( lowercase: str , lowercase: str , lowercase: int ) -> int:
'''simple docstring'''
_UpperCamelCase: Any = Path(lowercase )
_UpperCamelCase: int = Path(lowercase )
dest_dir.mkdir(exist_o... | 271 | 0 |
"""simple docstring"""
def lowerCAmelCase_( lowercase_ : str , lowercase_ : str ) -> bool:
_lowerCamelCase = len(lowercase_ )
_lowerCamelCase = len(lowercase_ )
_lowerCamelCase = [[False for _ in range(m + 1 ... | 623 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transf... | 623 | 1 |
'''simple docstring'''
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
a_ : Optional[Any] = """http:... | 676 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import B... | 676 | 1 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
'https://huggingface.co/CarlCochet/traj... | 706 |
"""simple docstring"""
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def UpperCamelCase ( _A , _A , _A = 1 / sqrt(2 ) ) -> IIRFilter:
lowercase : Optional[int] = tau * frequency / samplerate
lowercase ... | 348 | 0 |
"""simple docstring"""
class UpperCamelCase_ (__A ):
pass
class UpperCamelCase_ (__A ):
pass
class UpperCamelCase_ :
def __init__( self : List[str] ) -> Tuple:
UpperCAmelCase_ : int = [
[],
[],
[],
]
def _SCR... | 95 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(_... | 511 | 0 |
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
snake_case : Dict = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplification},
authors={Xu, ... | 718 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : list[int] ): # This function is recursive
a__ = len(__lowerCAmelCase )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if ar... | 657 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase : int = logging.get_logger(__name__)
_UpperCAmelCase : int = {
"""facebook/timesformer""": """https://huggingface.co/facebook/timesformer/resolve/main/config.json""",
}
class... | 683 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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
#
# Unle... | 683 | 1 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
... | 701 |
'''simple docstring'''
from statistics import mean
import numpy as np
def __lowercase (_lowercase, _lowercase, _lowercase, _lowercase ) -> list:
"""simple docstring"""
__lowerCamelCase : str = 0
# Number of processes finished
__lowerCamelC... | 483 | 0 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_c... | 274 | '''simple docstring'''
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, ... | 274 | 1 |
"""simple docstring"""
def lowercase ( a__ : Union[str, Any] ) -> Union[str, Any]:
_UpperCamelCase = [0] * len(a__ )
_UpperCamelCase = []
_UpperCamelCase = [1] * len(a__ )
for values in graph.values():
for i in values:
indegree[i] += 1
... | 342 | """simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
UpperCAmelCase = input("""Enter image url: """).strip()
print(F'''Downloading image from {url} ...''')
UpperCAmelCase = BeautifulSoup(requests.get(url).content, ... | 342 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ :Any = {"""configuration_xlnet""": ["""XLNE... | 355 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
A__ = []
def generate(lowercase_ , lowercase_ ):
if k == 1:
res.append... | 87 | 0 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
'snap-research/efficientformer-l1-300': (
'https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json... | 403 |
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
_A = logging.get_logger(__name__)
def __SCREAMING_SNAKE_CASE ( ) ... | 403 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : Dict = {
'configuration_rembert': ['REM... | 98 |
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 | 0 |
"""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... | 713 |
"""simple docstring"""
from __future__ import annotations
from math import pow, sqrt
def lowerCAmelCase_( lowercase_ : float , lowercase_ : float , lowercase_ : float ) -> dict[str, float]:
if (resistance, reactance, impedance).count(0 )... | 623 | 0 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils ... | 68 |
from torch import nn
class __lowerCAmelCase ( nn.Module ):
"""simple docstring"""
def __init__( self : Optional[int] , _snake_case : List[Any] , _snake_case : Tuple ):
super().__init__()
__lower... | 509 | 0 |
from math import isqrt
def _A ( __snake_case :int ) -> Optional[Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in ra... | 710 |
from typing import List
import numpy as np
def _A ( __snake_case :dict ) -> int:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {key: len(__snake_case ) for key, value in gen_kwargs.items() if isinstance(__snake_case , __snake_case ... | 214 | 0 |
"""simple docstring"""
import sys
def __lowerCamelCase ( __UpperCamelCase ) -> Union[str, Any]:
"""simple docstring"""
lowerCAmelCase_ : int = len(__UpperCamelCase )
lowerCAmelCase_ : List[Any] = [[0 for x in range(__UpperCamelCase )] f... | 610 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
lowercase__ = re.compile(r"""([a-z\d])([A-Z])""")
lowercase__ = re.compile(r"""(?<!_)_(?!_)""")
lowercase__ = re.compile(r"""(_{2,})""")
lowerc... | 610 | 1 |
'''simple docstring'''
from typing import Any
class UpperCAmelCase :
'''simple docstring'''
def __init__( self , lowercase__ ) -> Dict:
SCREAMING_SNAKE_CASE : Optional[int] = data
SCREAMING_SNAKE_CASE ... | 179 | '''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.activations import gelu_new, gelu_python, get_activation
@require_torch
class UpperC... | 179 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case = {
"""configuration_convbert""": ["""CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ConvBertConfig""... | 62 |
'''simple docstring'''
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available... | 596 | 0 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrFor... | 711 |
'''simple docstring'''
def lowerCAmelCase__ ( UpperCAmelCase ):
"""simple docstring"""
if a < 0:
raise ValueError("""Input value must be a positive integer""" )
elif isinstance(UpperCAmelCase , UpperCAmelCase ):
... | 172 | 0 |
from __future__ import annotations
def lowerCamelCase_ ( _lowercase ) -> bool:
__A : str = len(_lowercase )
# We need to create solution object to save path.
__A : Union[str, Any] = [[0 for _ in range(_lowercase )] for _ in range(_lowe... | 520 | import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
... | 520 | 1 |
def a__ ( a ) -> str:
return "".join([hex(a )[2:].zfill(2 ).upper() for byte in list(a )] )
def a__ ( a ) -> bytes:
# Check data validity, following RFC3548
# https://www.ietf.org/rfc/rfc3548.txt
if (len(a ) % 2) != 0:
... | 236 | import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name__)
de... | 236 | 1 |
'''simple docstring'''
def lowerCAmelCase__ ( ):
_A : Dict = 0
for i in range(1 ,1001 ):
total += i**i
return str(lowerCamelCase )[-10:]
if __name__ == "__main__":
print(solution())
| 128 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(a_ ) ... | 128 | 1 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
UpperCamelCase__ : Tuple = ... | 486 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoCo... | 486 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICE... | 525 |
def _SCREAMING_SNAKE_CASE ( a ) -> list:
if len(a ) <= 1:
return lst
__A : Any = 1
while i < len(a ):
if lst[i - 1] <= lst[i]:
i += 1
else:
__A , __A : str = lst[i]... | 239 | 0 |
"""simple docstring"""
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
lowercase__ : List[... | 485 |
"""simple docstring"""
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def __lowercase ( _a , _a , _a ):
snake_case_ : Tuple = AutoConfig.from_pretrained(_a )
snake_case_ : Tuple = FlaxAutoModelF... | 485 | 1 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowercase_ = get_tests_dir('fixtures/test_sentencepiece_with_bytefallback.model')
... | 562 |
lowercase_ = 9.80665
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = g ) -> float:
if fluid_density <= 0:
raise ValueError('Impossible fluid density' )
if volume < 0:
raise ValueError('Impossible Object vol... | 562 | 1 |
"""simple docstring"""
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def SCREAMING_SNAKE_CASE ( snake_case, snake_case, snake_case):
__snake_case = ('''dense.weight''', '''attention.se... | 93 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( snake_case):
return 1 if digit in (0, 1) else (digit * factorial(digit - 1))
def SCREAMING_SNAKE_CASE ( snake_case):
__snake_case = 0
__snake_case = number
while duplicate > 0:
... | 93 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 65 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK... | 138 | 0 |
from __future__ import annotations
import requests
__SCREAMING_SNAKE_CASE = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categorie... | 716 |
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
fro... | 17 | 0 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class _A ( snake_case ):
'''simple docstring'''
__lowerCamelCase : List[str] = CustomTokenizer
pass
| 36 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLImgaImgPipeline,
UNeta... | 122 | 0 |
'''simple docstring'''
import qiskit
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ,_UpperCAmelCase : int ) -> qiskit.result.counts.Counts:
_a : Union[str, Any] =qiskit.Aer.get_backend("""aer_simulator""" )
# Create... | 506 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ,_UpperCAmelCase : str = " " ) -> list:
_a : int =[]
_a : Tuple =0
for index, char in enumerate(_UpperCAmelCase ):
... | 506 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE ( snake_case__ ):
snake_case__ = (IPNDMScheduler,)
snake_case__ = ... | 466 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import loa... | 364 | 0 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class SCREAMING_SNAKE_CASE_ ( __SCREAMING_SNAKE_CA... | 705 |
import re
def _SCREAMING_SNAKE_CASE ( snake_case_ : str ):
__magic_name__ = re.compile(
r'''^(?:0|94|\+94|0{2}94)''' r'''7(0|1|2|4|5|6|7|8)''' r'''(-| |)''' r'''\d{7}$''' )
return bool(re.search(snake_case_ , snake_case_ ) )
if __name__ == "__main__":
a_ : ... | 678 | 0 |
"""simple docstring"""
def snake_case ( A__ ):
return "".join(chr(ord(A__ ) - 32 ) if "a" <= char <= "z" else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 95 |
import requests
from bsa import BeautifulSoup
def __lowerCamelCase ( A__ : str = "https://www.worldometers.info/coronavirus" ) -> dict:
lowerCamelCase_ : List[str] = BeautifulSoup(requests.get(A__ ).text , """html.parser""" )
lowerCamelCase_ : Tuple ... | 278 | 0 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def SCREAMING_SNAKE_CASE( __UpperCamelCase = "laptop" ) -> str:
a__ : List[str] = F'https://www.amazon.in/laptop/s?k={product}'
a__ : int = {
'User-A... | 716 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Tra... | 207 | 0 |
'''simple docstring'''
import qiskit
def __snake_case ( UpperCAmelCase_ : int , UpperCAmelCase_ : int ):
lowerCamelCase_ = qiskit.Aer.get_backend("aer_simulator" )
# Create a Quantum Circuit acting on the q register
lowerCamelCase_ = qiskit.QuantumCirc... | 675 |
'''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
a_ : Any = [
"""Prosecutor: \"No videos were used in the crash investigation\" German paper... | 675 | 1 |
"""simple docstring"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def lowercase ( A_ )->... | 708 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _A ( _a ):
"""simple docstring"""
UpperCAmelCase : Any = (IPNDMScheduler,)
... | 135 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCase = 100 , ) -> float:
"""simple docstring"""
__UpperC... | 77 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 77 | 1 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def UpperCamelCase ( lowercase_ : np.ndarray ) -> np.ndarray:
'''simple docstring'''
lowercase , lowercase , lowercase =rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return ... | 720 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
IM... | 145 | 0 |
'''simple docstring'''
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanv... | 26 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {
'''configuration_electra''': ['''ELECTRA_PRETRAINE... | 657 | 0 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
snake_case_ : str = logging.get_logger(__name__)
class __snake_case ( a ):
def __init__( self : List[Any] , *_snake_case : int ... | 169 |
def A (__A : int ) -> bool:
"""simple docstring"""
if not isinstance(__A , __A ):
UpperCAmelCase_ = F"""Input value of [number={number}] must be an integer"""
raise TypeError(__A )
if number < 0:
return... | 169 | 1 |
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
fr... | 37 |
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_comm... | 37 | 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... | 704 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase : Union[str, Any] = {
"configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"],
"processing_git": ["GitProcessor"],
}
try:... | 3 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
A : str = {"""vocab_file""": """vocab.txt""", """tokeniz... | 516 |
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncoder,
... | 540 | 0 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __A ... | 705 | '''simple docstring'''
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
... | 10 | 0 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> List[Any]:
... | 205 | import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configurati... | 417 | 0 |
'''simple docstring'''
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class _Upper... | 454 |
'''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 .tokenization_bart impo... | 454 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class a__ ( metaclass=a__ ):
'''simple docstring'''
lowercase__ : List[str] = ["transformers", "torch", "note_seq"]
def __init__... | 90 |
"""simple docstring"""
from timeit import timeit
def UpperCAmelCase ( snake_case : int ):
if number < 0:
raise ValueError('''the value of input must not be negative''' )
_lowerCAmelCase:str = 0
while number:
number &= number - 1
... | 227 | 0 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def lowerCAmelCase_ ( a : Optional[int] , a : str=False ):
a__ = OmegaConf.load(a )
if display:
... | 719 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_comm... | 126 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE = {'configuration_ibert': ['IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'IBertConfig', 'IBertOnnxConfig']}
try:
if not is_torch_available():
r... | 220 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNA... | 220 | 1 |
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_... | 702 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowerCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase = None, UpperCAmel... | 336 | 0 |
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE ( lowerCAmelCase ):
'''simple docstring'''
UpperCamelCase_ : int = ['''image_processor''', '''feature_extractor''']
UpperCamelCase_ : Union[str, Any] = '''TvltImageProce... | 62 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import torch
i... | 514 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d-tiny-100k/resolve/ma... | 572 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( snake_case_ = 100 ):
_lowercase = set()
_lowercase = 0
_lowercase = n + 1 # maximum limit
for a in range(2 , snake_case_ ):
for b in range(2 , snake_case_ ):
_lowercase = a**b # calculat... | 572 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_... | 28 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common im... | 706 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCAmelCase__ =logging.get_logger(__name__)
UpperCAmelCase__ ... | 442 | 0 |
"""simple docstring"""
def snake_case_ ( A_ : str = 2_00 ):
'''simple docstring'''
_lowerCamelCase : Dict = [1, 2, 5, 10, 20, 50, 1_00, 2_00]
_lowerCamelCase : Union[str, Any] = [0] * (pence + 1)
_lowerCamelCase : ... | 83 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel... | 295 | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, Flax... | 315 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import is_xformers_availabl... | 315 | 1 |
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