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 |
|---|---|---|---|---|
'''simple docstring'''
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestC... | 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"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {"configuration_opt": ["OPT_PRETRAINED_CONFIG_A... | 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 unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class snake_case__ ( unittest.TestCase ):
@require_torch
def ... | 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 doctest
from collections import deque
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] ):
'''simple docstring'''
a_ : Dict = [2, 1, 2... | 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 |
from functools import lru_cache
@lru_cache
def a__ ( A_ ):
'''simple docstring'''
if num < 0:
raise ValueError("""Number should not be negative.""" )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase__ : Tuple = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/co... | 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 warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'nvidia/segformer-b0-fi... | 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 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,
BertEmbeddin... | 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 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase : Optional[Any] = {"""configuration_yolos""": ["""YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """YolosConfig""", """YolosOnnxConfig"""]}
try:
i... | 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 itertools
import os
import re
lowercase__ : int = re.compile(R"([A-Z]+)([A-Z][a-z])")
lowercase__ : Optional[Any] = re.compile(R"([a-z\d])([A-Z])")
lowercase__ : Union[str, Any] = re.compile(R"(?<!_)_(?!_)")
lowercase__ : Optional[Any... | 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 gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
A__ : Any =False
cla... | 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'''
_snake_case = {
'km/h': 1.0,
'm/s': 3.6,
'mph': 1.6_0_9_3_4_4,
'knot': 1.8_5_2,
}
_snake_case = {
'km/h': 1.0,
'm/s': 0.2_7_7_7_7_7_7_7_8,
'mph': 0.6_2_1_3_7_1_1_9_2,
'knot': 0.5_3_9_9_5_6_8_0_3,
}
def _A ( snake_case , ... | 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"""
from __future__ import annotations
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : list , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
if len(SCREAMING_SNAKE_CASE__ ) <= 1 or n <= 1:
return
insert_next(SCREAMING... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Any = logging.get_logger(__name__)
lowerCamelCase : Any = {
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.j... | 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 ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline # noqa: F401
deprecate(
'stable diffusion controlnet',
'0.22.0',
'Importi... | 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 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_m... | 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 gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def _lowercase ( __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 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_att... | 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
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class __lowercase ( lowerCamelCase_ ):
def __lt__( self , lowercase_) -> Union[str, Any]:... | 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 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ... | 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 |
from __future__ import annotations
def lowerCamelCase__ ( _A ):
'''simple docstring'''
snake_case_ = 2
snake_case_ = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(SCREAMING_SNAKE_CASE__ )
i... | 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 os
def UpperCamelCase__ ( ):
"""simple docstring"""
with open(os.path.dirname(SCREAMING_SNAKE_CASE__ ) + """/p022_names.txt""" ) as file:
_lowerCAmelCase = str(file.readlines()[0] )
_lowe... | 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 warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a__ ( lowerCamelCase_ ):
_SCREAMING_SNAKE_CASE : int = ["""image_processor""", """tokenizer"""]
_SCREAMING_SNAKE_CASE : Tuple ... | 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 math
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : int = 1_00 ):
'''simple docstring'''
lowerCAmelCase = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase = int(math.pow(sum(range(1 , n + 1 ) ... | 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 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase : List[str] = TypeVar('T')
lowerCamelCase : Optional[Any] = TypeVar('U')
class snake_case__ ( Generic[T, U] ):
def __init__( sel... | 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 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,
ControlNetModel,
DDIMScheduler,
... | 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 |
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
__lowerCAmelCase : Dict = logging.get_logger(__name__)
__lowerCAmelCase : List[Any] = ... | 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 __future__ import annotations
from random import random
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self , UpperCamelCase = None) -> List[Any]:
UpperCamelCase__ : Optional[int] = value
UpperCamelCase__ : Optional[... | 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 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('3.8'):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
A = ''
i... | 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 math import sqrt
def A ( snake_case__ : int = 100_0000 ) -> Union[str, Any]:
'''simple docstring'''
__snake_case = 0
__snake_case = 0
__snake_case = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides ... | 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 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 GenerationTesterMixin
from ...tes... | 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 |
from collections import deque
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : Dict , __lowercase : str , __lowercase : int , __lowercase : int ):
"""simple docstring"""
s... | 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 typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLI... | 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'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case = {
'configuration_longformer': [
'LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP... | 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 json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin,... | 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 collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 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 json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils impor... | 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 binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
__lowerCAmelCase : int = {
# 1536-bit
5: {
'prime': int(
... | 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 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase__ : int = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerConfig''',
... | 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 |
from math import pi, sqrt, tan
def lowerCamelCase ( UpperCamelCase : float ) -> Any:
if side_length < 0:
raise ValueError('surface_area_cube() only accepts non-negative values' )
return 6 * side_length**2
def lowerCamelCase ( UpperCamelCase : float... | 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 |
def A ( snake_case__ : int = 10**12 ) -> Tuple:
'''simple docstring'''
__snake_case = 1
__snake_case = 0
__snake_case = 1
__snake_case = 1
while numerator <= 2 * min_total - 1:
prev_numerator += 2 * numerator
numerator +... | 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 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase : int = {
"""configuration_mobilenet_v2""": [
"""MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""MobileNetV2Config""",
... | 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 inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuratio... | 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 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 ...... | 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'''
from __future__ import annotations
_snake_case = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def _A ( snake_case , snake_case , snake_case , snake_case , snake_case , ) -> List... | 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 logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,... | 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 json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impor... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Tuple = logging.get_logger(__name__)
lowerCAmelCase_ : Optional[Any] = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingfa... | 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 |
import torch
from transformers import AutoModel
class UpperCAmelCase_ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self : Tuple , UpperCamelCase__ : List[str]="sayef/fsner-bert-base-uncased" ) -> Union[str, Any]:
... | 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 __future__ import annotations
from collections.abc import Generator
def _lowercase ( ) -> Dict:
UpperCamelCase__ : int = {}
UpperCamelCase__ : Optional[int] = 2
while True:
UpperCamelCase__ : List[str] = factor_map.pop(SCREAMING_SNAKE_CASE__ , ... | 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 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 ... | 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 argparse
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 accelerate import Acceler... | 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 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 load_numpy, ski... | 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 os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin... | 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 argparse
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_war... | 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 argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
Bi... | 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"""
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_co... | 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 |
def lowercase__( A , A ):
assert x is not None
assert y is not None
snake_case__ : str = len(SCREAMING_SNAKE_CASE__ )
snake_case__ : Dict = len(SCREAMING_SNAKE_CASE__ )
# declaring the array for storing the dp values
sna... | 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 Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
r... | 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 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 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 logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets import load... | 604 | from __future__ import annotations
import math
A_ = "2020.9.26"
A_ = "xcodz-dot, cclaus, dhruvmanila"
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase )-> tuple[float, float]:
"""simple docs... | 604 | 1 |
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
A_ = get_tests_dir("fixtures/spiece.model")
@re... | 604 | from __future__ import annotations
import os
from collections.abc import Mapping
A_ = tuple[int, int]
class __lowercase :
def __init__( self : Dict , __lowerCamelCase : set[int] , __lowerCamelCase : Mapping[EdgeT, int] ) -> None:
... | 604 | 1 |
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,
ConditionalDetrForSegmen... | 604 | def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def __UpperCAmelCase ( )-> None:
"""simple docstring"""
... | 604 | 1 |
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 (
MaxLengthCriteria,
... | 604 | import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __UpperCAmelCase ( )-> List[Any]:
"""simple docstring"""
... | 604 | 1 |
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> float:
"""simple docstring"""
_validate_point(UpperCAmelCase )
_validate_point(UpperCAmelCase )
if len(UpperCAmelCase ) != len(UpperCAmelCase ):
raise ValueError('''... | 604 | import gc
import threading
import time
import psutil
import torch
class __lowercase :
def __init__( self : List[str] ) -> List[str]:
'''simple docstring'''
lowercase = psutil.Process()
lowercase = False
def... | 604 | 1 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_... | 604 | import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMSchedul... | 604 | 1 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
A_ = logging.get_logger(__name__)
A_ = {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_f... | 604 | import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"vocab_file": "vocab.json",
"merges_file": "merges.txt",
"to... | 604 | 1 |
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
A_ = "."
if __name__ == "__main__":
A_ = os.path.join(REPO_PATH, "utils/documentation_tests.txt")
A_ = []
A_ ... | 604 | import numpy as np
def __UpperCAmelCase ( UpperCAmelCase )-> np.array:
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def __UpperCAmelCase ( UpperCAmelCase )-> np.array:
"""simple do... | 604 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"facebook/vit-mae-base": "https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json",
# See all ViT MAE models at https://huggingface.co/models?filter=vi... | 604 | 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
from ...tes... | 604 | 1 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.... | 604 | 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,
ConditionalDetrForSegmen... | 604 | 1 |
def __UpperCAmelCase ( UpperCAmelCase )-> List[Any]:
"""simple docstring"""
lowercase ,lowercase = [], []
while len(UpperCAmelCase ) > 1:
lowercase ,lowercase = min(UpperCAmelCase ), max(UpperCAmelCase )
sta... | 604 | import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets import load... | 604 | 1 |
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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
... | 604 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
if not is_torch_available():
... | 604 | 1 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
A_ = 10
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase ... | 604 | import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = "▁"
A_ = {"vocab_file": "vocab.txt", ... | 604 | 1 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTes... | 604 | from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_te... | 604 | 1 |
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> Optional[int]:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(UpperCAmelCase, int(b / 2 ) ) * actual_power(UpperCAmelCase, int(b / 2 ... | 604 | A_ = 256
# Modulus to hash a string
A_ = 1000003
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> bool:
"""simple docstring"""
lowercase = len(UpperCAmelCase )
lowercase = len(UpperCAmelCase ... | 604 | 1 |
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase )-> int:
"""simple docstring"""
if len(UpperCAmelCase ) != len(UpperCAmelCase ):
raise ValueError('''The length of profit and weight must be same.''' )
if max_wei... | 604 | import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_... | 604 | 1 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fai... | 604 | import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class __lowercase ( _A , unittest.TestCase ... | 604 | 1 |
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def __UpperCAmelCase ( )-> None:
"""simple docstring"""
... | 604 | import argparse
from collections import defaultdict
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase )-> List[Any]:
"""simple docstring"""
lowercase = f'{file}_{class_name}_{test_name... | 604 | 1 |
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
A_ = "Usage of script: script_name <size_of_canvas:int>"
A_ = [0] * 100 + [1] * 10
random.shuffle(choice)
def __UpperCAmelCase ( UpperCAm... | 604 | import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class __lowercase ( unittest.TestCase ):
... | 604 | 1 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 604 | def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> str:
"""simple docstring"""
return "\n".join(
f'{number} * {i} = {number * i}' for i in range(1, number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication_ta... | 604 | 1 |
from __future__ import annotations
import math
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> float:
"""simple docstring"""
lowercase = u
for i in range(1, UpperCAmelCase ):
lowercase = temp * (u - i... | 604 | def __UpperCAmelCase ( UpperCAmelCase = 50 )-> int:
"""simple docstring"""
lowercase = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2, 5 ):
for tile_start i... | 604 | 1 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class ... | 604 | import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"vocab_file": "vocab.txt",
"merges_file": "bpe.codes",
}
A_ ... | 604 | 1 |
from __future__ import annotations
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase )-> tuple[float, list[float]]:
"""simple docstring"""
lowercase = list(range(len(UpperCAmelCase ) ) )
lowercase ... | 604 | from __future__ import annotations
import math
A_ = "2020.9.26"
A_ = "xcodz-dot, cclaus, dhruvmanila"
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase )-> tuple[float, float]:
"""simple docs... | 604 | 1 |
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 TokenizerTesterMixin
A_... | 604 | from __future__ import annotations
import os
from collections.abc import Mapping
A_ = tuple[int, int]
class __lowercase :
def __init__( self : Dict , __lowerCamelCase : set[int] , __lowerCamelCase : Mapping[EdgeT, int] ) -> None:
... | 604 | 1 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,... | 604 | def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def __UpperCAmelCase ( )-> None:
"""simple docstring"""
... | 604 | 1 |
import logging
from transformers import PretrainedConfig
A_ = logging.getLogger(__name__)
A_ = {
"bertabs-finetuned-cnndm": "https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json",
}
class __lowercase ( ... | 604 | import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __UpperCAmelCase ( )-> List[Any]:
"""simple docstring"""
... | 604 | 1 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_te... | 604 | import gc
import threading
import time
import psutil
import torch
class __lowercase :
def __init__( self : List[str] ) -> List[str]:
'''simple docstring'''
lowercase = psutil.Process()
lowercase = False
def... | 604 | 1 |
import argparse
import datetime
def __UpperCAmelCase ( UpperCAmelCase )-> str:
"""simple docstring"""
lowercase = {
'''0''': '''Sunday''',
'''1''': '''Monday''',
'''2''': '''Tuesday''',
'''3''': '''Wednesday'... | 604 | import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMSchedul... | 604 | 1 |
def __UpperCAmelCase ( UpperCAmelCase )-> float:
"""simple docstring"""
return 10 - x * x
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> float:
"""simple docstring"""
if equation(Up... | 604 | import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"vocab_file": "vocab.json",
"merges_file": "merges.txt",
"to... | 604 | 1 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
... | 604 | import numpy as np
def __UpperCAmelCase ( UpperCAmelCase )-> np.array:
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def __UpperCAmelCase ( UpperCAmelCase )-> np.array:
"""simple do... | 604 | 1 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...t... | 604 | 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
from ...tes... | 604 | 1 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"vocab_file": "vocab.json",
"merges_file": "merges.txt",
"to... | 604 | 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,
ConditionalDetrForSegmen... | 604 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
A_ = {"processing_wav2vec2_with_lm": ["Wav2Vec2ProcessorWithLM"]}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
A_ = _LazyModule(__name__, globals()[... | 604 | import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets import load... | 604 | 1 |
def __UpperCAmelCase ( )-> Tuple:
"""simple docstring"""
lowercase = 0
for i in range(1, 1001 ):
total += i**i
return str(UpperCAmelCase )[-10:]
if __name__ == "__main__":
print(solution())
| 604 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
if not is_torch_available():
... | 604 | 1 |
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class __lowercase ... | 604 | import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = "▁"
A_ = {"vocab_file": "vocab.txt", ... | 604 | 1 |
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_flax_available():
... | 604 | from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_te... | 604 | 1 |
def __UpperCAmelCase ( UpperCAmelCase )-> int:
"""simple docstring"""
lowercase = len(UpperCAmelCase )
lowercase = len(matrix[0] )
lowercase = min(UpperCAmelCase, UpperCAmelCase )
for row in range(UpperC... | 604 | A_ = 256
# Modulus to hash a string
A_ = 1000003
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase )-> bool:
"""simple docstring"""
lowercase = len(UpperCAmelCase )
lowercase = len(UpperCAmelCase ... | 604 | 1 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"google/umt5-small": "https://huggingface.co/google/umt5-small/resolve/main/config.json",
... | 604 | import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_... | 604 | 1 |
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase )-> int:
"""simple docstring"""
... | 604 | import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class __lowercase ( _A , unittest.TestCase ... | 604 | 1 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
A_ = logging.get_logger(__name__)
class __lowercase ( _A ):
def __init__( self : str , *__lowerCamelCase : Dict , **__lowerCamelCa... | 604 | import argparse
from collections import defaultdict
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase )-> List[Any]:
"""simple docstring"""
lowercase = f'{file}_{class_name}_{test_name... | 604 | 1 |
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