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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__UpperCAmelCase = {'''configuration_encoder_decoder''': ['''EncoderDecoderConfig''']}
try:
i... | 642 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __lowerCamelCase :
"""simple docstring"""
a = 42
a = None
a = None
A : Optional[Any] = na... | 128 | 0 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
__SCREAMING_SNAKE_CASE = TypeVar('_T')
class a__ ( Generic[_T] ):
def __init__( self :Optional[Any] , _lowerCamelCase :Iterable[_T] | None = None ):
... | 357 |
'''simple docstring'''
import socket
def lowerCAmelCase__ ( ):
_A : Dict = socket.socket(socket.AF_INET ,socket.SOCK_STREAM )
_A : List[Any] = socket.gethostname()
_A : List[str] = 12312
sock.connect((host, port... | 128 | 0 |
def __lowerCAmelCase ( __magic_name__ , __magic_name__ ):
_lowercase: int = len(__magic_name__ )
print("The following activities are selected:" )
# The first activity is always selected
_lowercase: Optional[int] = 0
print(__magic_name__ , end="," ... | 226 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 ...te... | 128 | 0 |
from __future__ import annotations
def A__ ( SCREAMING_SNAKE_CASE_ : list[int] , SCREAMING_SNAKE_CASE_ : int ) -> Optional[int]:
"""simple docstring"""
if len(SCREAMING_SNAKE_CASE_ ) == 0:
return False
_UpperCAmelCase = len(SCREAMI... | 32 |
'''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, UNetaDConditionModel
f... | 128 | 0 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase ( a_ ):
... | 313 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, 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_... | 128 | 0 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase_ : Dict = tuple[int, int, int]
UpperCAmelCase_ : Dict = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
UpperCAmelCase_ : ... | 255 |
'''simple docstring'''
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_availa... | 128 | 0 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __lowerCAmelCase ( ):
__lowerCAmelCase = {
'repo_name': ['test_repo1', 'test_repo2', 'test_repo3'],
'path': ['test_1... | 367 |
'''simple docstring'''
import re
def lowerCAmelCase__ ( lowerCamelCase : str ):
if len(re.findall('[ATCG]' ,lowerCamelCase ) ) != len(lowerCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' ,'TAGC' ) )
if _... | 128 | 0 |
from pathlib import Path
import json
import tempfile
from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES
UpperCAmelCase_ : List[Any] = '''tiny-wmt19-en-ru'''
# Build
# borrowed from a test
UpperCAme... | 17 |
'''simple docstring'''
from math import factorial
def lowerCAmelCase__ ( lowerCamelCase : int ,lowerCamelCase : int ,lowerCamelCase : float ):
if successes > trials:
raise ValueError('successes must be lower or equal to trials' )
if trials < 0 or ... | 128 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase ( _lowerCAmelCase : list ) -> Tuple:
if len(_lowerCAmelCase ) == 0:
return []
_UpperCAmelCase : Dict = min(_lowerCAmelCase ), max(_lowerCAmelCase )
_UpperCAmel... | 238 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version impor... | 128 | 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... | 231 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from .... | 128 | 0 |
'''simple docstring'''
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_vis... | 111 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
A : List[Any] = False
try:
A : ... | 128 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def lowercase__ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> Tuple:
'''simple docstring'''
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
a__ : Dict = ... | 642 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def lowerCAmelCase__ ( lowerCamelCase : str ,lowerCamelCase : Union[str, Any] ,lowerCamelCase : Tuple ,lowerCamelCase : str ):
_A : Union[str, Any] =... | 128 | 0 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
__SCREAMING_SNAKE_CASE = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel... | 357 |
'''simple docstring'''
def lowerCAmelCase__ ( lowerCamelCase : int ,lowerCamelCase : float ,lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase__ ( lowerCamelCase : float ,lowerCamelCase : float ,lowerCa... | 128 | 0 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffusers.s... | 226 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(a_ ) ... | 128 | 0 |
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
UpperCAmelCase_ = HUGGINGFACE_HUB_CACHE
UpperCAmelCase_ = '''config.json'''
UpperCAmelCase_ = '''diffusion_pytorch_model.bin'''
UpperCAmelCase_ = '''diffusion_flax_model.msgpack'''
Upp... | 32 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase : str ,lowerCamelCase : list[str] | None = None ):
_A : str = word_bank or []
# create a table
_A : int = len(lowerCamelCase ) + 1
... | 128 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __lowercase ( a_ ):
_... | 313 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
A : Optional[int] = logging.get_logger(__na... | 128 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
UpperCAmelCase_ : str = logging.get_logger(__name__)
class __UpperCAmelCase ( a_ ):
'''simple docstring'''
def __init__( s... | 255 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __lowerCamelCase ( pl.LightningModule ):
"""simple docstring"""
def __init__( self : List[... | 128 | 0 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils impo... | 367 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_to... | 128 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils im... | 17 |
'''simple docstring'''
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default... | 128 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy a... | 238 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase : list ):
if not nums:
raise ValueError('List is empty' )
return sum(lowerCamelCase ) / len(lowerCamelCase )
if __name__ == "__main__":
import doctest
doc... | 128 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _UpperCAmelCase ( a_ ):
@staticmethod
@abstractmethod
def A ( A : ArgumentParser ) -> int:
raise NotImplementedError()
... | 231 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def lowerCAmelCase__ ( lowerCamelCase : Callable[[int | float], int | float] ,lowerCamelCase : int | float ,lowerCamelCase : int | float ,lowerCamelCase : int = 100 ,):
... | 128 | 0 |
'''simple docstring'''
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...gen... | 111 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def lowerCAmelCase__ ( lowerCamelCase : list[int] ,lowerCamelCase : list[int] ,lowerCamelCase : int ):
_A : Optional[Any] = [0] * no_of_processes
_A : Li... | 128 | 0 |
"""simple docstring"""
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__UpperCAmelCase = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input(''... | 642 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __lowerCamelCase :
"""simple docstring"""
a = 42
a = None
a = None
A : Optional[Any] = na... | 128 | 0 |
"""simple docstring"""
import os
from math import logaa
def A_ ( __lowercase = "base_exp.txt" ):
UpperCamelCase_ : float =0
UpperCamelCase_ : Dict =0
for i, line in enumerate(open(os.path.join(os.path.dirname(__lowercase ) , __lowercase ) ) ):
UpperCamelCase_ : ... | 357 |
'''simple docstring'''
import socket
def lowerCAmelCase__ ( ):
_A : Dict = socket.socket(socket.AF_INET ,socket.SOCK_STREAM )
_A : List[Any] = socket.gethostname()
_A : List[str] = 12312
sock.connect((host, port... | 128 | 0 |
_SCREAMING_SNAKE_CASE : List[str] = '''2.13.1'''
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse('3.7'):
raise ImportWarning(
'To use `datasets`, Python>=3.7 is required, and the current version of Pytho... | 226 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 ...te... | 128 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCamelCase ( a_ ):
__A : Optional[int] = """ClapFeatureExtractor"""
__A : Union[str, Any] = ("""RobertaTokenizer""", """RobertaTokenizerFast""")
... | 32 |
'''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, UNetaDConditionModel
f... | 128 | 0 |
from __future__ import annotations
import math
def A ( snake_case__ : float , snake_case__ : int ) -> Optional[Any]:
'''simple docstring'''
__snake_case = u
for i in range(1 , snake_case__ ):
__snake_case = temp * (u - i)
retur... | 313 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, 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_... | 128 | 0 |
"""simple docstring"""
from pathlib import Path
import fire
def _lowerCAmelCase(a : str , a : str , a : int ) -> Tuple:
_SCREAMING_SNAKE_CASE =Path(a )
_SCREAMING_SNAKE_CASE =Path(a )
dest_dir.mkdir(exist_ok=a )
for path in src_dir.iterdir... | 255 |
'''simple docstring'''
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_availa... | 128 | 0 |
def __lowerCAmelCase ( __snake_case ):
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 367 |
'''simple docstring'''
import re
def lowerCAmelCase__ ( lowerCamelCase : str ):
if len(re.findall('[ATCG]' ,lowerCamelCase ) ) != len(lowerCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' ,'TAGC' ) )
if _... | 128 | 0 |
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, TensorType
UpperCAmelCase_ : int = ... | 17 |
'''simple docstring'''
from math import factorial
def lowerCAmelCase__ ( lowerCamelCase : int ,lowerCamelCase : int ,lowerCamelCase : float ):
if successes > trials:
raise ValueError('successes must be lower or equal to trials' )
if trials < 0 or ... | 128 | 0 |
"""simple docstring"""
def UpperCamelCase ( _lowerCAmelCase : int, _lowerCAmelCase : int ) -> Optional[int]:
return int((input_a, input_a).count(0 ) != 0 )
def UpperCamelCase ( ) -> List[Any]:
assert nand_gate(0, 0 ) == 1
assert nand_... | 238 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version impor... | 128 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepa... | 231 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from .... | 128 | 0 |
'''simple docstring'''
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokeniz... | 111 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
A : List[Any] = False
try:
A : ... | 128 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__... | 642 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def lowerCAmelCase__ ( lowerCamelCase : str ,lowerCamelCase : Union[str, Any] ,lowerCamelCase : Tuple ,lowerCamelCase : str ):
_A : Union[str, Any] =... | 128 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE = {
'''configuration_xmod''': [
'''XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XmodConfig''',
'''XmodOnnxConfi... | 357 |
'''simple docstring'''
def lowerCAmelCase__ ( lowerCamelCase : int ,lowerCamelCase : float ,lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase__ ( lowerCamelCase : float ,lowerCamelCase : float ,lowerCa... | 128 | 0 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
_SCREAMING_SNAKE_CASE : List[str] = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kad... | 226 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(a_ ) ... | 128 | 0 |
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCAmelCase_ = 3_00 # TEMPERATURE (unit = K)
def A__ ( SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float , ) -> Tuple:
"... | 32 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase : str ,lowerCamelCase : list[str] | None = None ):
_A : str = word_bank or []
# create a table
_A : int = len(lowerCamelCase ) + 1
... | 128 | 0 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' , ['default', 0, 100 * 2**20, 900 * 2**20] )
def A ( sn... | 313 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
A : Optional[int] = logging.get_logger(__na... | 128 | 0 |
"""simple docstring"""
from __future__ import annotations
import requests
def _lowerCAmelCase(a : str ) -> Optional[int]:
_SCREAMING_SNAKE_CASE =f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(a ).json()
def _l... | 255 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __lowerCamelCase ( pl.LightningModule ):
"""simple docstring"""
def __init__( self : List[... | 128 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class _UpperCamelCase (a_ ):
def __init__( self , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> Any:
... | 367 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_to... | 128 | 0 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import... | 17 |
'''simple docstring'''
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default... | 128 | 0 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 238 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase : list ):
if not nums:
raise ValueError('List is empty' )
return sum(lowerCamelCase ) / len(lowerCamelCase )
if __name__ == "__main__":
import doctest
doc... | 128 | 0 |
"""simple docstring"""
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version impo... | 231 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def lowerCAmelCase__ ( lowerCamelCase : Callable[[int | float], int | float] ,lowerCamelCase : int | float ,lowerCamelCase : int | float ,lowerCamelCase : int = 100 ,):
... | 128 | 0 |
'''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __magic_name__ :
"""simple docstring"""
pass
| 111 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def lowerCAmelCase__ ( lowerCamelCase : list[int] ,lowerCamelCase : list[int] ,lowerCamelCase : int ):
_A : Optional[Any] = [0] * no_of_processes
_A : Li... | 128 | 0 |
"""simple docstring"""
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import Padd... | 642 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __lowerCamelCase :
"""simple docstring"""
a = 42
a = None
a = None
A : Optional[Any] = na... | 128 | 0 |
"""simple docstring"""
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp... | 357 |
'''simple docstring'''
import socket
def lowerCAmelCase__ ( ):
_A : Dict = socket.socket(socket.AF_INET ,socket.SOCK_STREAM )
_A : List[Any] = socket.gethostname()
_A : List[str] = 12312
sock.connect((host, port... | 128 | 0 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_SCREAMING_SNAKE_CASE : Tuple = HfApi()
_SCREAMING_SNAKE_CASE : int = {}
# fmt: off
_SCREAMING_SNAKE_CASE : Dict = torch.tensor([
-0.7515, -1.6883, 0.2420, ... | 226 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 ...te... | 128 | 0 |
import os
import platform
import sys
UpperCAmelCase_ = '''3'''
print("Python version:", sys.version)
print("OS platform:", platform.platform())
print("OS architecture:", platform.machine())
try:
import torch
print("Torch version:", torch.__version__)
print("Cuda available:", torch.cuda.is... | 32 |
'''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, UNetaDConditionModel
f... | 128 | 0 |
def A ( snake_case__ : int ) -> Dict:
'''simple docstring'''
__snake_case = [1]
__snake_case = 0, 0, 0
__snake_case = ugly_nums[ia] * 2
__snake_case = ugly_nums[ia] * 3
__snake_case = ugly_nums[ia] * 5
for _ in ran... | 313 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, 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_... | 128 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
... | 255 |
'''simple docstring'''
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_availa... | 128 | 0 |
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
class _UpperCamelCase (a_ ):
snake_case_ = """philschmid/bart-large-cnn-samsum"""
snake_case_ = (
"""This is a tool that summarizes an English text. It takes an input `text` ... | 367 |
'''simple docstring'''
import re
def lowerCAmelCase__ ( lowerCamelCase : str ):
if len(re.findall('[ATCG]' ,lowerCamelCase ) ) != len(lowerCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' ,'TAGC' ) )
if _... | 128 | 0 |
def __SCREAMING_SNAKE_CASE ( a__ : List[Any] ) -> Tuple:
__A : Any = []
__A : str = []
__A : Optional[int] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priority of each operator
__A : List[Any] = len(a__ ... | 17 |
'''simple docstring'''
from math import factorial
def lowerCAmelCase__ ( lowerCamelCase : int ,lowerCamelCase : int ,lowerCamelCase : float ):
if successes > trials:
raise ValueError('successes must be lower or equal to trials' )
if trials < 0 or ... | 128 | 0 |
"""simple docstring"""
def UpperCamelCase ( _lowerCAmelCase : list ) -> List[str]:
_UpperCAmelCase : int = len(_lowerCAmelCase )
for _ in range(_lowerCAmelCase ):
for i in range(_ % 2, arr_size - 1, 2 ):
if arr[i + 1] < arr[i]:
_U... | 238 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version impor... | 128 | 0 |
"""simple docstring"""
from typing import Dict
from .base import GenericTensor, Pipeline
class _UpperCAmelCase ( a_ ):
def A ( self : Optional[Any] , A : Dict=None , A : str=None , A : Tuple=None , **A : List[Any]... | 231 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from .... | 128 | 0 |
'''simple docstring'''
def _lowercase (SCREAMING_SNAKE_CASE = 100_0000 ):
'''simple docstring'''
__A : Tuple = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
... | 111 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
A : List[Any] = False
try:
A : ... | 128 | 0 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __UpperCAmelCase ( a_ ):
def __init__( ... | 642 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def lowerCAmelCase__ ( lowerCamelCase : str ,lowerCamelCase : Union[str, Any] ,lowerCamelCase : Tuple ,lowerCamelCase : str ):
_A : Union[str, Any] =... | 128 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__SCREAMING_SNAKE_CASE = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/er... | 357 |
'''simple docstring'''
def lowerCAmelCase__ ( lowerCamelCase : int ,lowerCamelCase : float ,lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase__ ( lowerCamelCase : float ,lowerCamelCase : float ,lowerCa... | 128 | 0 |
class A :
'''simple docstring'''
def __init__( self : str):
_lowercase: dict[str, TrieNode] = {} # Mapping from char to TrieNode
_lowercase: Optional[Any] = False
def UpperCAmelCase__ ( self : Dict ... | 226 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(a_ ) ... | 128 | 0 |
def A__ ( SCREAMING_SNAKE_CASE_ : Any ) -> Optional[int]:
"""simple docstring"""
_UpperCAmelCase = 0
_UpperCAmelCase = len(SCREAMING_SNAKE_CASE_ )
for i in range(n - 1 ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE_ ... | 32 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase : str ,lowerCamelCase : list[str] | None = None ):
_A : str = word_bank or []
# create a table
_A : int = len(lowerCamelCase ) + 1
... | 128 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffusion.modeling_robert... | 313 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
A : Optional[int] = logging.get_logger(__na... | 128 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
"""Salesforce/blip-vqa-base""": """https://huggingface.co/Salesfor... | 129 |
"""simple docstring"""
def _A ( __lowercase = 200_0000 ):
"""simple docstring"""
lowerCamelCase__ = [0 for i in range(n + 1 )]
lowerCamelCase__ = 1
lowerCamelCase__ = 1
for i in range(2 , int(n**0.5 ) ... | 129 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
"""configuration_time_series_transformer""": [
"""TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""TimeSeri... | 129 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
while second != 0:
lowerCamelCase__ = first & second
first ^= second
lowerCamelCase__ = c << 1
return first
... | 129 | 1 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run... | 129 |
"""simple docstring"""
from __future__ import annotations
def _A ( __lowercase ):
"""simple docstring"""
if len(__lowercase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i <= 0 for i in nums ):
... | 129 | 1 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__magic_name__ = pytest.mark.integration
@pytest.mark.parametrize("""p... | 129 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE , unittest.TestCase )... | 129 | 1 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert... | 129 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 129 | 1 |
"""simple docstring"""
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
... | 129 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 129 | 1 |
"""simple docstring"""
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = set()
# edges = list of graph's edges
lowerCamelCase__ = get_edges(__lowercase )
# While there are still elements in edges list, take an ar... | 129 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__magic_name__ = 3
def _A ( __lowercase ):
"""simple docstring"""
print("""Generating primitive root of p""" )
while True:... | 129 | 1 |
"""simple docstring"""
from graphs.minimum_spanning_tree_kruskal import kruskal
def _A ( ):
"""simple docstring"""
lowerCamelCase__ = 9
lowerCamelCase__ = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
... | 129 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _A ( __lowercase , __lowercase=None ):
"""simple docstring"""
lowerCamelCase__ = No... | 129 | 1 |
"""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_available():
from .tok... | 129 |
"""simple docstring"""
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = set()
# edges = list of graph's edges
lowerCamelCase__ = get_edges(__lowercase )
# While there are still elements in edges list, take an ar... | 129 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__magic_name__ = {"""configuration_unispeech""": ["""UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP""", ... | 129 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorT... | 129 | 1 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
__magic_name__ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
__magic_name__ = [ord(letter) for letter in string.... | 129 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's eas... | 129 | 1 |
"""simple docstring"""
from math import factorial
def _A ( __lowercase = 20 ):
"""simple docstring"""
lowerCamelCase__ = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
lowerCamelCase__ = n // ... | 129 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 129 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
"""configuration_trajectory_transformer""": [
"""TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Trajector... | 129 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _A ( __lowercase , __lowercase , __lowercase = None ):
"""simple docstring"""
if version.parse(hfh.__version__... | 129 | 1 |
"""simple docstring"""
import torch
def _A ( ):
"""simple docstring"""
if torch.cuda.is_available():
lowerCamelCase__ = torch.cuda.device_count()
else:
lowerCamelCase__ = 0
print(f"""Successfully ran on {num_gp... | 129 |
"""simple docstring"""
from importlib import import_module
from .logging import get_logger
__magic_name__ = get_logger(__name__)
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Dict , SCREAMING_SNAKE_CASE_ : Tuple , SCREAMING_SNAKE_CASE_ : int=None ... | 129 | 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 ):
def ... | 129 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transfo... | 129 | 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, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils... | 129 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 129 | 1 |
"""simple docstring"""
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
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = ... | 129 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=_SCREAMING_SNAKE_CASE ):
snake_case = ["speech"]
def __init__( self : Optional[int] , *SCREAMING_SNAKE_CASE_ : Tuple , **SCREAMING_SNAKE_... | 129 | 1 |
"""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()
__magic_name__ = logging.get_logger(... | 129 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_A... | 129 | 1 |
"""simple docstring"""
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... | 129 |
"""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_available():
from .tok... | 129 | 1 |
"""simple docstring"""
def _A ( __lowercase = 1000 ):
"""simple docstring"""
lowerCamelCase__ = 2**power
lowerCamelCase__ = str(__lowercase )
lowerCamelCase__ = list(__lowercase )
lowerCamelCase__ = ... | 129 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 129 | 1 |
"""simple docstring"""
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_configurati... | 129 |
"""simple docstring"""
__magic_name__ = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def _A ( __lowercase , __lowercase , __lowercase , __lowercase ... | 129 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kand... | 129 |
"""simple docstring"""
def _A ( __lowercase = 10 , __lowercase = 22 ):
"""simple docstring"""
lowerCamelCase__ = range(1 , __lowercase )
lowerCamelCase__ = range(1 , __lowercase )
return sum(
... | 129 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 129 |
"""simple docstring"""
def _A ( __lowercase = 200_0000 ):
"""simple docstring"""
lowerCamelCase__ = [0 for i in range(n + 1 )]
lowerCamelCase__ = 1
lowerCamelCase__ = 1
for i in range(2 , int(n**0.5 ) ... | 129 | 1 |
"""simple docstring"""
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _A ( __lowerc... | 129 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
while second != 0:
lowerCamelCase__ = first & second
first ^= second
lowerCamelCase__ = c << 1
return first
... | 129 | 1 |
"""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
__magic_name__ = ... | 129 |
"""simple docstring"""
from __future__ import annotations
def _A ( __lowercase ):
"""simple docstring"""
if len(__lowercase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i <= 0 for i in nums ):
... | 129 | 1 |
"""simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def _A ( __lowercase , __lowercase , __lowercase = 1 , __lowercase = 1 , __lowercase = 1.0e4 , __lowercase = False , __lowercase = 1.0 , ):
... | 129 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE , unittest.TestCase )... | 129 | 1 |
"""simple docstring"""
from importlib import import_module
from .logging import get_logger
__magic_name__ = get_logger(__name__)
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Dict , SCREAMING_SNAKE_CASE_ : Tuple , SCREAMING_SNAKE_CASE_ : int=None ... | 129 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 129 | 1 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorT... | 129 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 129 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
... | 129 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__magic_name__ = 3
def _A ( __lowercase ):
"""simple docstring"""
print("""Generating primitive root of p""" )
while True:... | 129 | 1 |
"""simple docstring"""
import heapq
import sys
import numpy as np
__magic_name__ = tuple[int, int]
class SCREAMING_SNAKE_CASE__ :
def __init__( self : int ):
lowerCamelCase__ = []
lowerCamelCase__ = set()
def __... | 129 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _A ( __lowercase , __lowercase=None ):
"""simple docstring"""
lowerCamelCase__ = No... | 129 | 1 |
"""simple docstring"""
from string import ascii_uppercase
__magic_name__ = {str(ord(c) - 55): c for c in ascii_uppercase}
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
if isinstance(__lowercase , __lowercase ):
r... | 129 |
"""simple docstring"""
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = set()
# edges = list of graph's edges
lowerCamelCase__ = get_edges(__lowercase )
# While there are still elements in edges list, take an ar... | 129 | 1 |
"""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_available():
from .tok... | 129 |
"""simple docstring"""
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorT... | 129 | 1 |
"""simple docstring"""
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
fr... | 129 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's eas... | 129 | 1 |
"""simple docstring"""
import os
import string
import sys
__magic_name__ = 1 << 8
__magic_name__ = {
"""tab""": ord("""\t"""),
"""newline""": ord("""\r"""),
"""esc""": 27,
"""up""": 65 + ARROW_KEY_FLAG,
"""down""": 66 + ARROW_KEY_FLAG,
"""right""": 67 + ARROW_KEY... | 129 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 129 | 1 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import pa... | 129 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _A ( __lowercase , __lowercase , __lowercase = None ):
"""simple docstring"""
if version.parse(hfh.__version__... | 129 | 1 |
"""simple docstring"""
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = [0] * len(__lowercase )
lowerCamelCase__ = []
lowerCamelCase__ = []
lowerCamelCase__ = 0
for values in g... | 129 |
"""simple docstring"""
from importlib import import_module
from .logging import get_logger
__magic_name__ = get_logger(__name__)
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Dict , SCREAMING_SNAKE_CASE_ : Tuple , SCREAMING_SNAKE_CASE_ : int=None ... | 129 | 1 |
"""simple docstring"""
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
return base * power(__lowercase , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print("""Raise base to the power of exponent using recursion...""")
__m... | 129 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transfo... | 129 | 1 |
"""simple docstring"""
from collections import defaultdict
def _A ( __lowercase ):
"""simple docstring"""
lowerCamelCase__ = 1
lowerCamelCase__ = True
for v in tree[start]:
if v not in visited:
ret +=... | 129 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 129 | 1 |
"""simple docstring"""
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch... | 129 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=_SCREAMING_SNAKE_CASE ):
snake_case = ["speech"]
def __init__( self : Optional[int] , *SCREAMING_SNAKE_CASE_ : Tuple , **SCREAMING_SNAKE_... | 129 | 1 |
"""simple docstring"""
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_ut... | 129 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_A... | 129 | 1 |
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