code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
def lowerCamelCase_ ( _UpperCamelCase , _UpperCamelCase = 0 ) -> list:
"""simple docstring"""
snake_case_ : Dict = length or len(_UpperCamelCase )
snake_case_ : Any = False
for i in range(length - 1 ):
if l... | 60 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 603 | 0 |
from __future__ import annotations
def _A ( lowerCAmelCase_ : list , lowerCAmelCase_ : int , lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
"""simple docstring"""
lowerCAmelCase__ = []
lowerCAmelCase__ , lowerCAmelCas... | 61 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_num... | 603 | 0 |
import argparse
import copy
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = {}
with open(lowercase ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
SCREAMING_SNAKE_CASE : Li... | 62 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {'configuratio... | 603 | 0 |
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_torch, require_vision, slo... | 63 |
'''simple docstring'''
import torch
from transformers import AutoModel
class lowerCAmelCase_ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self : Tuple , _UpperCAmelCase : List[str]="sayef/fsner-bert-base-uncased" ):
"""simple docstring"... | 603 | 0 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_con... | 64 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
assert x is not None
assert y is not None
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ )
UpperCAmelCase__ ... | 603 | 0 |
"""simple docstring"""
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
fr... | 65 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __lt__( self : List[Any] , _Upper... | 603 | 0 |
import requests
from bsa import BeautifulSoup
def __magic_name__ ( SCREAMING_SNAKE_CASE = "https://www.worldometers.info/coronavirus" ) -> dict:
_lowercase : Optional[Any] = BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE ).text , 'html.parser' )
... | 66 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_longformer': [
'LONGFORMER_PRETRAINED_CO... | 603 | 0 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
snake_case = logging.get_logger(__name__) # pylint: disable=invalid-name
class A_ ( ... | 67 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generation... | 603 | 0 |
from __future__ import annotations
import math
def lowercase__ ( A_: float , A_: int ) -> float:
"""simple docstring"""
__UpperCAmelCase =u
for i in range(1 , A_ ):
__UpperCAmelCase =temp * (u - i)
... | 68 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, l... | 603 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
fro... | 69 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mas... | 603 | 0 |
import functools
def _SCREAMING_SNAKE_CASE ( lowercase : str , lowercase : str ):
'''simple docstring'''
lowerCamelCase_ = len(lowercase )
lowerCamelCase_ = len(lowercase )
@functools.cache
def min_dist... | 70 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_comm... | 603 | 0 |
'''simple docstring'''
import argparse
import os
import re
_lowerCamelCase = """src/diffusers"""
# Pattern that looks at the indentation in a line.
_lowerCamelCase = re.compile(R"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCamelCase ... | 71 |
'''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 To... | 603 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase : List[str] = {
'''configuration_xlm_roberta_xl''': [
'''XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XLMRobertaXLConfig''',
... | 72 |
'''simple docstring'''
import unittest
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ... | 603 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : str = logging.get_logger(__name__)
a_ : Any = {
'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json',
}
class _snake_case ( A__... | 73 |
'''simple docstring'''
from collections import namedtuple
import requests
from lxml import html # type: ignore
UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered')
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ... | 603 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def a__ ( snake_case ):
"""simple docstring"""
_... | 74 |
'''simple docstring'''
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase_ = {
'facebook/mask2former-swin-small-coco-instance': (
'https://huggingface.c... | 603 | 0 |
'''simple docstring'''
from manim import *
class lowerCamelCase_ ( __a ):
def lowercase_ ( self : List[Any] ):
'''simple docstring'''
UpperCAmelCase__ : Any = Rectangle(height=0.5 , width=0.5 )
... | 75 |
'''simple docstring'''
UpperCAmelCase_ = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDo... | 603 | 0 |
"""simple docstring"""
a_ = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def __UpperCAmelCase ( ):
__lowercase : Any = input('''Enter message: ''' )
__lowercase : Union[str, Any] = input('''Enter key [alphanumeric]: ''' )
__lowercase ... | 76 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase_ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAva... | 603 | 0 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase = "cpu" , UpperCamelCase = None ) -> None:
"""simple docstring"""
__UpperCAmelCase : Union[str,... | 77 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'tokenization_tr... | 603 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE_: List[Any] ={
'configuration_luke': ['LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LukeConfig'],
'tokenization_luke': ['LukeTokenizer'],
}
try:
... | 78 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Au... | 603 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer... | 79 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ = {
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileNetV2Con... | 603 | 0 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, logging
from .ben... | 80 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase_ = TypeVar('T')
UpperCAmelCase_ = TypeVar('U')
class lowerCAmelCase_ ( Generic[T, U] ):
'''simple docstring'''
d... | 603 | 0 |
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase = 1 / sqrt(2 ) ):
__snake_case : List[Any] = tau * frequency / samplerate
__snake... | 81 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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 To... | 603 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""bert-b... | 82 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 603 | 0 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
... | 83 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_num... | 603 | 0 |
import os
import numpy
import onnx
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase = a.name
lowercase = b.name
lowercase = ''
lowercase = ''
lowercase = a == b
lowercase = name_a
lowerc... | 84 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {'configuratio... | 603 | 0 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
SCREAMING_SNAKE_CASE__ : Any = logging.getLogger(__name__)
def _a ( ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Optiona... | 85 |
'''simple docstring'''
import torch
from transformers import AutoModel
class lowerCAmelCase_ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self : Tuple , _UpperCAmelCase : List[str]="sayef/fsner-bert-base-uncased" ):
"""simple docstring"... | 603 | 0 |
def __snake_case ( __UpperCamelCase : int = 6008_5147_5143 ):
"""simple docstring"""
try:
A_ = int(__UpperCamelCase )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:... | 86 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
assert x is not None
assert y is not None
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ )
UpperCAmelCase__ ... | 603 | 0 |
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
_lowerCamelCase : Dict = logging.get_logger(__name__)
_lowerCamelCase : ... | 87 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __lt__( self : List[Any] , _Upper... | 603 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils impor... | 88 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_longformer': [
'LONGFORMER_PRETRAINED_CO... | 603 | 0 |
from collections import defaultdict
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ ) -> bool:
_lowercase : Any = first_str.lower().strip()
_lowercase : List[str] = second_str.lower().strip()
# Remove whitespace
_lowercase : str... | 89 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generation... | 603 | 0 |
'''simple docstring'''
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
)
__UpperCAmelCase = logging.g... | 90 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, l... | 603 | 0 |
"""simple docstring"""
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import M... | 91 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mas... | 603 | 0 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
... | 92 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_comm... | 603 | 0 |
"""simple docstring"""
import re
def __A (_SCREAMING_SNAKE_CASE ) ->bool:
"""simple docstring"""
lowerCAmelCase__ :str = re.compile(r'^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$' )
if match := re.search(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
return mat... | 93 |
'''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 To... | 603 | 0 |
'''simple docstring'''
def lowercase_ ( __A : str , __A : str = " " ) -> list:
"""simple docstring"""
lowercase : List[str] =[]
lowercase : Union[str, Any] =0
for index, char in enumerate(__A ):
if char == separator:
... | 94 |
'''simple docstring'''
import unittest
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ... | 603 | 0 |
"""simple docstring"""
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
lowerCamelCase_ = TypeVar('''T''')
class UpperCamelCase_ (Generic[T]... | 95 |
'''simple docstring'''
from collections import namedtuple
import requests
from lxml import html # type: ignore
UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered')
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ... | 603 | 0 |
"""simple docstring"""
from __future__ import annotations
def a ( __UpperCAmelCase : int | str ) -> bool:
__magic_name__: List[str] = str(__UpperCAmelCase )
return n == n[::-1]
def a ( __UpperCAmelCase : int = ... | 96 |
'''simple docstring'''
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase_ = {
'facebook/mask2former-swin-small-coco-instance': (
'https://huggingface.c... | 603 | 0 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_m... | 97 |
'''simple docstring'''
UpperCAmelCase_ = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDo... | 603 | 0 |
'''simple docstring'''
import math
def a__ ( lowercase : int = 100 ) -> int:
"""simple docstring"""
_UpperCamelCase = sum(i * i for i in range(1, n + 1 ) )
_UpperCamelCase = int(math.pow(sum(range(1, n + 1 ) ), 2 ) )
... | 98 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase_ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAva... | 603 | 0 |
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def a (lowerCAmelCase__ ):
__a = [
"""encoder.version""",
"""decoder.version""",
"""model.encoder.version""",
"""model.decoder.version... | 99 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'tokenization_tr... | 603 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_A : Dict = logging.get_logger(__name__)
_A : int =... | 100 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Au... | 603 | 0 |
import os
def a__ ( ):
SCREAMING_SNAKE_CASE_ : List[str] = os.path.dirname(os.path.realpath(A__ ) )
SCREAMING_SNAKE_CASE_ : int = os.path.join(A__, 'triangle.txt' )
with open(A__ ) as f:
SCREAMING_SNAKE_CASE_ : Any = ... | 101 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ = {
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileNetV2Con... | 603 | 0 |
"""simple docstring"""
import functools
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
# Validation
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) or not all(isinstance(SCREAMING_SNAKE_CASE , SCREAM... | 102 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase_ = TypeVar('T')
UpperCAmelCase_ = TypeVar('U')
class lowerCAmelCase_ ( Generic[T, U] ):
'''simple docstring'''
d... | 603 | 0 |
"""simple docstring"""
class UpperCAmelCase :
def __init__( self : str , __lowerCamelCase : Optional[int] , __lowerCamelCase : Dict , __lowerCamelCase : Union[str, Any] ):
"""simple docstring"""
_snake_case ... | 103 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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 To... | 603 | 0 |
"""simple docstring"""
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torc... | 104 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 603 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ : Dict = {'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCHIVE_MAP''... | 105 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_num... | 603 | 0 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
__snake_case :List[Any] ='\\n@misc{chen2021evaluating,\n title={Evaluating Large La... | 106 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {'configuratio... | 603 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( __snake_case : int , __snake_case : int ):
while b:
_A , _A = b, a % b
return a
def _SCREAMING_SNAKE_CASE ( __snake_case : int , __snake_case : int ):
return a if... | 107 |
'''simple docstring'''
import torch
from transformers import AutoModel
class lowerCAmelCase_ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self : Tuple , _UpperCAmelCase : List[str]="sayef/fsner-bert-base-uncased" ):
"""simple docstring"... | 603 | 0 |
import re
from filelock import FileLock
try:
import nltk
__a: Any = True
except (ImportError, ModuleNotFoundError):
__a: Optional[int] = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet=True)
def _SCREAMING_SNAK... | 108 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
assert x is not None
assert y is not None
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ )
UpperCAmelCase__ ... | 603 | 0 |
'''simple docstring'''
from __future__ import annotations
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = str(__UpperCAmelCase )
return n == n[::-1]
def __magic_name__ ( __UpperCAmelCase = 10000... | 109 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __lt__( self : List[Any] , _Upper... | 603 | 0 |
from itertools import count
def _lowercase ( __SCREAMING_SNAKE_CASE = 50 ) -> str:
UpperCamelCase__ : str = [1] * min_block_length
for n in count(SCREAMING_SNAKE_CASE__ ):
fill_count_functions.append(1 )
for block_length in range(SCREAMING_SNAKE_CASE__ , ... | 410 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_longformer': [
'LONGFORMER_PRETRAINED_CO... | 603 | 0 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
A = logging.getLogger()
def lowerCamelCase ( ... | 544 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generation... | 603 | 0 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase__ : str = {
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingface.c... | 313 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, l... | 603 | 0 |
def UpperCAmelCase_ ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ):
if index == r:
for j in range(SCREAMING_SNAKE_CASE__ ):
print(data[j] , end=""" """ )
print("... | 423 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mas... | 603 | 0 |
import numpy as np
def lowerCamelCase__ ( _A ):
'''simple docstring'''
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 376 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_comm... | 603 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase ):
"""simple docstring"""
if not (isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_C... | 207 |
'''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 To... | 603 | 0 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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 Tokenizer... | 245 |
'''simple docstring'''
import unittest
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ... | 603 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = [
["attention", "... | 532 |
'''simple docstring'''
from collections import namedtuple
import requests
from lxml import html # type: ignore
UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered')
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ... | 603 | 0 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_token... | 170 |
'''simple docstring'''
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase_ = {
'facebook/mask2former-swin-small-coco-instance': (
'https://huggingface.c... | 603 | 0 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
lowerCAmelCase_ : Dict = '\nimport os\n'
lowerCAmelCase_ : List[Any] = '\ndef foo():\n import os\n return False\n'
lowerCAmelCase_ : List[str... | 442 |
'''simple docstring'''
UpperCAmelCase_ = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDo... | 603 | 0 |
def a__ ( A_ ):
'''simple docstring'''
return 10 - x * x
def a__ ( A_, A_ ):
'''simple docstring'''
if equation(SCREAMING_SNAKE_CASE__ ) * equation(SCREAMING_SNAKE_CASE__ ) >= 0:
raise ValueError("""Wrong space!""" )
__magi... | 529 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase_ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAva... | 603 | 0 |
from collections.abc import Callable
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self , UpperCamelCase = None) -> Union[str, Any]:
UpperCamelCase__ : Optional[Any] = []
# Stores indexes of each item for supporting updates an... | 410 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'tokenization_tr... | 603 | 0 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAG... | 544 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Au... | 603 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def A ( snake_case__ : Optional[Any] , snake_case__ : List[Any]=1000 ) -> Dict:
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
__s... | 313 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ = {
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileNetV2Con... | 603 | 0 |
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ... | 423 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase_ = TypeVar('T')
UpperCAmelCase_ = TypeVar('U')
class lowerCAmelCase_ ( Generic[T, U] ):
'''simple docstring'''
d... | 603 | 0 |
lowercase__ : Optional[Any] = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
from .features ... | 376 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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 To... | 603 | 0 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
A__ : List[str] ='''\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks ... | 207 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 603 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Config... | 245 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_num... | 603 | 0 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class lowercase ( logging.LoggerAdapter ):
@staticmethod
def _snake_case ( lowercase ) -> List[Any]:
lowerCAmelCase = PartialState()
return not m... | 532 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {'configuratio... | 603 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase : str = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailab... | 170 |
'''simple docstring'''
import torch
from transformers import AutoModel
class lowerCAmelCase_ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self : Tuple , _UpperCAmelCase : List[str]="sayef/fsner-bert-base-uncased" ):
"""simple docstring"... | 603 | 0 |
'''simple docstring'''
import sys
lowerCAmelCase_ : Tuple = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'125406987471585238630507156932909632952274430... | 442 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
assert x is not None
assert y is not None
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ )
UpperCAmelCase__ ... | 603 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCAmelCase : List[Any] = {'configuration_reformer': ['REFORMER_PRETRAINED_CONFIG_ARCHIVE... | 529 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __lt__( self : List[Any] , _Upper... | 603 | 0 |
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__ : Any = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
'''text-classific... | 410 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_longformer': [
'LONGFORMER_PRETRAINED_CO... | 603 | 0 |
import csv
import tweepy
# Twitter API credentials
A = ''
A = ''
A = ''
A = ''
def lowerCamelCase ( UpperCamelCase : str ) -> Tuple:
_lowerCamelCase = tweepy.OAuthHandler(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ )
auth.s... | 544 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generation... | 603 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
UpperCAmelCase__ : Dict = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHI... | 313 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, l... | 603 | 0 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenizat... | 423 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mas... | 603 | 0 |
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase__ : List[Any] ... | 376 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_comm... | 603 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A__ : List[Any] =logging.get_logger(__name__)
class UpperCAm... | 207 |
'''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 To... | 603 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_ima... | 245 |
'''simple docstring'''
import unittest
import numpy as np
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray | None = None ... | 603 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import requests
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_in... | 532 |
'''simple docstring'''
from collections import namedtuple
import requests
from lxml import html # type: ignore
UpperCAmelCase_ = namedtuple('covid_data', 'cases deaths recovered')
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "https://www.worldometers.info/coronavirus/" ... | 603 | 0 |
import math
import qiskit
def lowercase__( A = 1 , A = 1 , A = 1 ):
if (
isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ )
or isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ )
or isinstance(SCREAMING_SNA... | 170 |
'''simple docstring'''
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase_ = {
'facebook/mask2former-swin-small-coco-instance': (
'https://huggingface.c... | 603 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ : Any = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARC... | 442 |
'''simple docstring'''
UpperCAmelCase_ = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDo... | 603 | 0 |
def a__ ( A_ = 600851475143 ):
'''simple docstring'''
try:
__magic_name__ = int(SCREAMING_SNAKE_CASE__ )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable to int.""" )
if n <= 0:
raise ValueError("""Parameter ... | 529 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase_ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAva... | 603 | 0 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
UpperCAmelCase__ : Union[str, Any] = 2_048
UpperCAmelCase__ : Tuple = 4_096
UpperCAmelCase__ : List[str] = 42
UpperCAmelCase__ : Any = os.environ.pop('''PROCESS_TRA... | 410 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'tokenization_tr... | 603 | 0 |
def lowerCamelCase ( UpperCamelCase : int = 3 , UpperCamelCase : int = 7 , UpperCamelCase : int = 1_00_00_00 ) -> int:
_lowerCamelCase = 0
_lowerCamelCase = 1
for current_denominator in range(1 , limit + 1 ):
_lowerCamelCas... | 544 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Au... | 603 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase__ : Optional[int] = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/viv... | 313 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ = {
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileNetV2Con... | 603 | 0 |
def UpperCAmelCase_ ( _UpperCAmelCase ):
if not all(x.isalpha() for x in string ):
raise ValueError("""String must only contain alphabetic characters.""" )
lowerCamelCase_: str = sorted(string.lower() )
return len(SCREAMING_SNAKE_CASE__ ... | 423 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase_ = TypeVar('T')
UpperCAmelCase_ = TypeVar('U')
class lowerCAmelCase_ ( Generic[T, U] ):
'''simple docstring'''
d... | 603 | 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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_ver... | 376 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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 To... | 603 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = get_failure_array(SCREAMING_SNAKE_CASE__ )
# 2) Step through text search... | 207 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 603 | 0 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql imp... | 245 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_num... | 603 | 0 |
"""simple docstring"""
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... | 532 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {'configuratio... | 603 | 0 |
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
AutoencoderKL,
DDIM... | 170 |
'''simple docstring'''
import torch
from transformers import AutoModel
class lowerCAmelCase_ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self : Tuple , _UpperCAmelCase : List[str]="sayef/fsner-bert-base-uncased" ):
"""simple docstring"... | 603 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowerCAmelCase_ : Optional[Any] = {'tokenization_byt5': ['ByT5Tokenizer']}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
lowerCAmelCase_ : ... | 442 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
assert x is not None
assert y is not None
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE__ )
UpperCAmelCase__ ... | 603 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCAmelCase : str = {
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data... | 529 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __lt__( self : List[Any] , _Upper... | 603 | 0 |
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
from... | 410 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_longformer': [
'LONGFORMER_PRETRAINED_CO... | 603 | 0 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
A = logging.get_logger(__name__)
class lowerCAmelCase__ ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self : List[str] , *snak... | 544 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generation... | 603 | 0 |
from __future__ import annotations
class __lowercase :
def __init__( self , lowercase_ , lowercase_) -> int:
__snake_case , __snake_case = text, pattern
__snake_case , __snake_case = len(_UpperC... | 313 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, l... | 603 | 0 |
def UpperCAmelCase_ ( _UpperCAmelCase , _UpperCAmelCase ):
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
lowerCamelCase_: Dict = str(bin(SCREAMING_SNAKE_CASE__ ) )[2:] # remove the leading "0b"
lowe... | 423 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mas... | 603 | 0 |
def lowerCamelCase__ ( _A ):
'''simple docstring'''
snake_case_ = [0 for i in range(len(SCREAMING_SNAKE_CASE__ ) )]
# initialize interval's left pointer and right pointer
snake_case_ , snake_case_ = 0, 0
for i in range(1... | 376 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_comm... | 603 | 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
c... | 207 |
'''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 To... | 603 | 0 |
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