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'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image... | 8 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : str = {
'''configuration_convbert''': ... | 8 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 1 |
'''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,
)
lowercase__ : ... | 8 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ ... | 8 | 1 |
'''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
lowercase__ : List[str] = TypeVar('''T''')
clas... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int = 50 ) -> int:
__A : Optional[Any] = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in ... | 8 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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_configura... | 8 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin,... | 8 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 8 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[Any] = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
... | 8 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS... | 8 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.nu... | 8 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : int , __snake_case : int ) -> list[list[int]]:
__A : list[list[int]] = []
create_all_state(1 , __snake_case , __snake_... | 8 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 1 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
l... | 8 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ : Optional[int] = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMCon... | 8 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Optional[Any] ) -> Optional[Any]: # noqa: E741
__A : Tuple = len(__snake_case )
__A : Optional[int] = 0
__A : str = [0] * n
__A : int = [Fals... | 8 | 1 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def _lowerCAmelCase ( __snake_case : str = "AAPL" ) -> str:
__A : Optional[Any] = f'https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'
__A : Optional[int] =... | 8 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 1 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 | 1 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
fr... | 8 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tup... | 8 | 1 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
l... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
lowercase__ : str = 0
lowercase__ : Optional[Any] = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are fr... | 8 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingf... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __snake_case : int ) -> int:
if number != int(__snake_case ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueE... | 8 | 1 |
'''simple docstring'''
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_co... | 8 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 | 1 |
'''simple docstring'''
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, Test... | 8 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 | 1 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from ... | 8 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int , __snake_case : int , __snake_case : int ) -> float:
__A : Dict = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of s... | 8 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[int] = logging.get_logger(__name__)
lowercase__ : str = {
'''microsoft/trocr-base-handwritten''': (
'''https:... | 8 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 | 1 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE (a__ ):
lowerCAmelCase = ['''image_processor''', '''tokenizer''']
lowerCAmelCase = '''AutoIma... | 8 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 1 |
'''simple docstring'''
lowercase__ : Tuple = '''Alexander Joslin'''
import operator as op
from .stack import Stack
def _lowerCAmelCase ( __snake_case : str ) -> int:
__A : Any = {'*': op.mul, '/': op.truediv, '+': op.add,... | 8 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 1 |
'''simple docstring'''
import math
def _lowerCAmelCase ( __snake_case : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all e... | 8 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ ... | 8 | 1 |
'''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, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UN... | 8 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 | 1 |
'''simple docstring'''
import random
def _lowerCAmelCase ( __snake_case : int ) -> bool:
__A : Tuple = num - 1
__A : Optional[Any] = 0
while s % 2 == 0:
__A : Optional[int] = s // 2
t += ... | 8 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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_configura... | 8 | 1 |
'''simple docstring'''
import re
def _lowerCAmelCase ( __snake_case : str ) -> bool:
__A : Dict = re.compile(r'^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$' )
if match := re.search(__snake_case , __snake_case ):
return match... | 8 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 8 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[Any] = {
'''hugging... | 8 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS... | 8 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowercase__ : int = (3, 9, -11, 0, 7, 5, 1, -1)
lowercase__ : List[str] = (4, 6, 2, 0, 8, 10, 3, -2)
@datac... | 8 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 1 |
'''simple docstring'''
lowercase__ : str = tuple[float, float, float]
lowercase__ : Dict = tuple[float, float, float]
def _lowerCAmelCase ( __snake_case : Pointad , __snake_case : Pointad ) -> Vectorad:
_... | 8 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 1 |
'''simple docstring'''
class SCREAMING_SNAKE_CASE :
def __init__( self):
'''simple docstring'''
__A : Union[str, Any] = {}
def SCREAMING_SNAKE_CASE ( self):
'''simple docstring'''
... | 8 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Optional[Any] ) -> Optional[Any]: # noqa: E741
__A : Tuple = len(__snake_case )
__A : Optional[int] = 0
__A : str = [0] * n
__A : int = [Fals... | 8 | 1 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class SCREAMING_SNAKE_CASE (unittest.TestCase ... | 8 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : list[list[int]] , __snake_case : int , __snake_case : int , __snake_case : set ) -> int:
__A ,__A : str = len(__snake_case ), len(grid[0] )
... | 8 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 | 1 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowercase__ : Dict = log... | 8 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 | 1 |
'''simple docstring'''
from math import pi
def _lowerCAmelCase ( __snake_case : int , __snake_case : int ) -> float:
return 2 * pi * radius * (angle / 3_60)
if __name__ == "__main__":
print(arc_length(90, 10)) | 8 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tup... | 8 | 1 |
'''simple docstring'''
import heapq
def _lowerCAmelCase ( __snake_case : dict ) -> set[int]:
__A : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will ... | 8 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
l... | 8 | 1 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowercase__ : Any = parse(importlib.metadata.version('''torch'''))
def _lowerCAmelCase ... | 8 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingf... | 8 | 1 |
'''simple docstring'''
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
... | 8 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __snake_case : int ) -> int:
if number != int(__snake_case ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueE... | 8 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 0 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 | 0 |
def _A ( _lowercase , _lowercase ) -> int:
"""simple docstring"""
return abs(_lowercase ) if a == 0 else greatest_common_divisor(b % a , _lowercase )
def _A ( _lowercase , _lowercase ) -> int:
"""simple docstring"""
while y: # --... | 1 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 | 0 |
def SCREAMING_SNAKE_CASE_ ( _snake_case :list[int] , _snake_case :list[int] , _snake_case :int ) -> bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(_snake_case ) )
def SCREAMING_SNAKE_CASE_ ( _snake_case :... | 2 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int , __snake_case : int , __snake_case : int ) -> float:
__A : Dict = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of s... | 8 | 0 |
'''simple docstring'''
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatm... | 3 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase : str = {
'''configuration_deberta''': ['''DEBERTA_PRETRAINE... | 4 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 0 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_availab... | 5 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 0 |
class UpperCamelCase_ :
def __init__( self :Optional[int] , __A :str = "" , __A :bool = False ) -> None:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = {}
# A node will be a leaf if the tree contains its word
SCREAM... | 6 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ ... | 8 | 0 |
"""simple docstring"""
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
'split_dict' , [
SplitDict(),
SplitDict({'train': SplitInfo(name='train' , num_bytes=13_37 , num_examples... | 7 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 | 0 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import loggin... | 9 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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_configura... | 8 | 0 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers... | 10 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 8 | 0 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
if not isinstance(__A , __A):
raise ValueError('''multiplicative_persistence() only accepts integral values''')
if num < 0:
raise ValueError('''multiplicative_persistence() does not accep... | 11 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS... | 8 | 0 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is... | 12 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.... | 13 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 0 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from ... | 14 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 0 |
import math
A : List[Any] = 1_0
A : Union[str, Any] = 7
A : List[str] = BALLS_PER_COLOUR * NUM_COLOURS
def UpperCamelCase ( __magic_name__ : int = 20 ) -> str:
"""simple docstring"""
lowercase__ = math.comb(_... | 15 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Optional[Any] ) -> Optional[Any]: # noqa: E741
__A : Tuple = len(__snake_case )
__A : Optional[int] = 0
__A : str = [0] * n
__A : int = [Fals... | 8 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : str = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
),
... | 16 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 0 |
UpperCAmelCase_ : Optional[int] = {
0: '''0''',
1: '''1''',
2: '''2''',
3: '''3''',
4: '''4''',
5: '''5''',
6: '''6''',
7: '''7''',
8: '''8''',
9: '''9''',
10: '''a''',
11: '''b''',
12: '''c''',
13: '''d''',
14: '''e''',
15: '''f''',
}
def ... | 17 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 | 0 |
'''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960... | 18 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from... | 19 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tup... | 8 | 0 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_s... | 20 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
l... | 8 | 0 |
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class __A ( UpperCamelCase__ ... | 21 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingf... | 8 | 0 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class A ( nn.Module ):
lowercase_ = 42
lowe... | 22 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __snake_case : int ) -> int:
if number != int(__snake_case ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueE... | 8 | 0 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
snake_case__ : List[str] = logging.get_logger(__name__)... | 23 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import pi, sqrt
def _UpperCamelCase (_lowerCamelCase : float , _lowerCamelCase : float )-> tuple:
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be... | 24 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 | 0 |
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_mask
from ...test_pipeline_mixin ... | 25 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int , __snake_case : int , __snake_case : int ) -> float:
__A : Dict = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of s... | 8 | 0 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def _a ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ... | 26 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
f... | 27 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"junn... | 28 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class __lowerCamelCase ( lowerCAmelCase ):
a__: Tuple = 'SpeechT5FeatureExtractor'
a__: List[str] = 'SpeechT5Tokenizer'
def __init__( self , UpperCAmelCase , UpperC... | 29 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ ... | 8 | 0 |
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase__ ( _lowercase , _lowercase , _lowercase ):
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = x
UpperCAmelCase_ : List[str] = y
for step in range(_lowercase ): # ... | 30 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 | 0 |
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 (
FlaxForcedBOSTo... | 31 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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_configura... | 8 | 0 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 32 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 8 | 0 |
import os
from datetime import datetime as dt
from github import Github
lowerCamelCase__ : int = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""w... | 33 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS... | 8 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
'... | 34 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 0 |
def a ( A__ , A__ , A__ ) -> int:
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
SCREAMING_SNAKE_CASE__ : Tuple = _modexpt(A__ , exponent // 2 , A__ ) % modulo_value
... | 35 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 0 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_logger... | 36 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 0 |
def UpperCamelCase_ ( __a ) -> list[int]:
a__ : str = len(__a )
for i in range(__a ):
for j in range(i + 1 , __a ):
if numbers[j] < numbers[i]:
a__, a__ : List[Any] = numbers[j], numbers[i]
return n... | 37 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Optional[Any] ) -> Optional[Any]: # noqa: E741
__A : Tuple = len(__snake_case )
__A : Optional[int] = 0
__A : str = [0] * n
__A : int = [Fals... | 8 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
A_ : Optional[Any] = "\\n\n"
A_ : int = "\nPerplexity (PPL) is one of the most common m... | 38 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 0 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , S... | 39 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 | 0 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__UpperCAmelCase = '''src/di... | 40 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : str , __snake_case : str ) -> int:
if len(__snake_case ) != len(__snake_case ):
raise ValueError('String lengths must match!' )
__A : Optional[Any] = 0
... | 8 | 0 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _A ( ):
"""simple docstring"""
__lowercase = ArgumentParser(
description=(
'''... | 41 |
'''simple docstring'''
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tup... | 8 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase__ )
class UpperCAmelCase ( UpperCAmelCase__ ):
'''simple docstring'''... | 42 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
l... | 8 | 0 |
from __future__ import annotations
def _a ( SCREAMING_SNAKE_CASE ): # This function is recursive
"""simple docstring"""
lowercase__ = len(SCREAMING_SNAKE_CASE )
# If the array contains only one element, we return it (it's the stop condition of
# recursion)
if array_length ... | 43 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingf... | 8 | 0 |
'''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
fr... | 44 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( __snake_case : int ) -> int:
if number != int(__snake_case ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueE... | 8 | 0 |
UpperCamelCase = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def A ( lowercase__ : bytes ) -> bytes:
# Make sure the supplied data is a bytes-like object
if not isinstance(lowercase__ , lowercase__ ):
UpperCamelCase__ :Dict = f"""a bytes-like obje... | 45 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __snake_case : list[int] , __snake_case : list[int] , __snake_case : int ) -> tuple[float, list[float]]:
__A : int = list(range(len(__snake... | 8 | 0 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> float:
'''simple docstring'''
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
re... | 46 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 | 0 |
from datetime import datetime
import requests
def UpperCAmelCase__ ( lowerCamelCase_ : str ):
__a : Dict = 'https://downloadgram.net/wp-json/wppress/video-downloader/video?url='
__a : Dict = requests.get(base_url + url ).json... | 47 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int , __snake_case : int , __snake_case : int ) -> float:
__A : Dict = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of s... | 8 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class A :
def __init__( self : Dict , __magic_name__ : Collection[float] | None = None ):
"""simple docstring"... | 48 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 8 | 0 |
"""simple docstring"""
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitesp... | 49 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 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_warmup, set_seed
from... | 50 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int ) -> bool:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect number or ... | 8 | 0 |
'''simple docstring'''
def __snake_case ( SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ) -> float:
"""simple docstring"""
UpperCAmelCase = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
... | 51 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ ... | 8 | 0 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
A = TypeVar('''KEY''')
A = TypeVar('''VAL''')
@dataclass(frozen=_UpperCamelCase , slots=_UpperCamelCase )
class ... | 52 |
'''simple docstring'''
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase=None , _UpperCAmelCase=None):
'''simple docstring'''
__A : List[Any] ... | 8 | 0 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common... | 53 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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_configura... | 8 | 0 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_model... | 54 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 8 | 0 |
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def UpperCAmelCase ( a_ , a_ , a_=1_0_2_4 , a_=1_0_2_4 , a_=False , **a_ ) -> Union[str, Any]:
... | 55 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS... | 8 | 0 |
'''simple docstring'''
import os
from typing import Dict, List, Tuple, TypeVar, Union
_a : str = TypeVar("T")
_a : Dict = Union[List[T], Tuple[T, ...]]
_a : str = Union[T, List[T], Dict[str, T]]
_a : Union[str, Any] = Union[str, bytes, os.Pat... | 56 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCAmelCase ( __snake_case : str , __snake_case : str , **__snake_case : List[Any] ) -> Any:
__A : Optiona... | 8 | 0 |
from math import log
from scipy.constants import Boltzmann, physical_constants
A_ : Tuple = 300 # TEMPERATURE (unit = K)
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , ) -> float:
if donor_conc... | 57 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase__ : Any = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-fi... | 8 | 0 |
"""simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.a... | 58 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A = {
"configuration_funnel": ["FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP", "FunnelConfig"],
"convert_funn... | 59 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : Optional[Any] ) -> Optional[Any]: # noqa: E741
__A : Tuple = len(__snake_case )
__A : Optional[int] = 0
__A : str = [0] * n
__A : int = [Fals... | 8 | 0 |
from sklearn.metrics import matthews_corrcoef
import datasets
lowerCAmelCase_ = '''
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It takes
into account true ... | 60 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.