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 |
|---|---|---|---|---|
import os
import unittest
from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _lower... | 613 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MA... | 613 | 1 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | 1 |
# Copyright 2021 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
#
# Unless required by applicabl... | 613 | class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 1 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 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, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a : int = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderConfig""", """VisionEncoderDecoder... | 613 | import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 613 | 1 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def snake_case__ ( lowercase , lowercase , lowercase , lowercase , lowercase = None , lowercase = None , lower... | 613 | from __future__ import annotations
def snake_case__ ( lowercase , lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | 1 |
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 accelerate import Accelerator, Distr... | 613 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | 1 |
a : int = 2_5_6
# Modulus to hash a string
a : str = 1_0_0_0_0_0_3
def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: List[Any] = len(lowercase )
lowerCAmelCase_: int = len(lowercase )
if p_len > t_len:
retu... | 613 | import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTesterM... | 613 | 1 |
from __future__ import annotations
def snake_case__ ( lowercase ):
if not nums:
raise ValueError("List is empty" )
return sum(lowercase ) / len(lowercase )
if __name__ == "__main__":
import doctest
doctest.testmod() | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | 1 |
import mpmath # for roots of unity
import numpy as np
class _lowercase :
'''simple docstring'''
def __init__( self , lowerCamelCase__=None , lowerCamelCase__=None ):
# Input as list
lowerCAmelCase_: str = list(poly_a or [0] )[:]
lower... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Union[str, Any] = logging.get_logger(__name__)
a : List[str] = {
"""andreasmadsen/efficient_m... | 613 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 1 |
import os
from pathlib import Path
def snake_case__ ( ):
from torch.utils.cpp_extension import load
lowerCAmelCase_: Optional[Any] = Path(lowercase ).resolve().parent.parent.parent / "kernels" / "deformable_detr"
lowerCAmelCase_: Optional[Any] = [
root / filename
f... | 613 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 1 |
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | 1 |
def snake_case__ ( lowercase , lowercase , lowercase ):
return round(float(moles / volume ) * nfactor )
def snake_case__ ( lowercase , lowercase , lowercase ):
return round(float((moles * 0.0821 * temperature) / (volume) ) )
def snake_case__ ( l... | 613 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | 1 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
a : Optional[int] = logging.getLogger(__name__)
def snake_case__ ( ):
lowerCAmelCase_: Optional[int] = argparse.ArgumentParser(
description="Prepare TF... | 613 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 1 |
def snake_case__ ( lowercase , lowercase ):
return x if y == 0 else greatest_common_divisor(lowercase , x % y )
def snake_case__ ( lowercase , lowercase ):
return (x * y) // greatest_common_divisor(lowercase , lowercase )
def snake_case__ ( lowercase = ... | 613 | from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | 1 |
from __future__ import annotations
a : Optional[Any] = """Muhammad Umer Farooq"""
a : Dict = """MIT"""
a : Tuple = """1.0.0"""
a : Optional[Any] = """Muhammad Umer Farooq"""
a : Dict = """contact@muhammadumerfarooq.me""... | 613 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 613 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : int = logging.get_logger(__name__)
a : int = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
'''simple ... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
a : List[Any] = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""SPEECHT5_PR... | 613 | from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Encoder, V... | 613 | import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available
... | 613 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : List[str] = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""InformerConfig""",
... | 613 | def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | 1 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_lza, require_zstan... | 613 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 1 |
from ....utils import logging
a : Union[str, Any] = logging.get_logger(__name__)
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def __init__( self , lowerCamelCase__ , lowerCamelCase__=None , lowerCamelCase__=2_048... | 613 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MA... | 613 | 1 |
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():
import torch
from ..models.a... | 613 | import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | 1 |
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - generate model_cards - useful... | 613 | class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 1 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
a : int = logging.get_logger(__name__)
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def __init__( self , *lowerCamelCase__ , ... | 613 | 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, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 1 |
def snake_case__ ( lowercase ):
if len(lowercase ) < 2:
return collection
def circle_sort_util(lowercase , lowercase , lowercase ) -> bool:
lowerCAmelCase_: Any = False
if low == high:
return swapped
lowerCAmelCase_: str ... | 613 | import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 613 | 1 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _lowercase ( unittest.TestCase ):
'''simple docstring'''
def _a ( self ):
debug_launcher(test_script.main )
def _... | 613 | from __future__ import annotations
def snake_case__ ( lowercase , lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | 1 |
import warnings
from .generation import TFGenerationMixin
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
# warning at import time
warnings.warn(
'Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will '
'be rem... | 613 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | 1 |
def snake_case__ ( lowercase , lowercase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod() | 613 | import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTesterM... | 613 | 1 |
from math import log
from scipy.constants import Boltzmann, physical_constants
a : Optional[int] = 3_0_0 # TEMPERATURE (unit = K)
def snake_case__ ( lowercase , lowercase , lowercase , ):
if donor_conc <= 0:
raise ValueError("Donor concentration should be p... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a : str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
a : str ... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 1 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def __init__( ... | 613 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 1 |
def snake_case__ ( lowercase = 1000 ):
lowerCAmelCase_: Dict = 2**power
lowerCAmelCase_: Any = 0
while n:
lowerCAmelCase_ , lowerCAmelCase_: List[Any] = r + n % 10, n // 10
return r
if __name__ == "__main__":
print(solution(int(str(input()).strip()))) | 613 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 1 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
a : str = logging.get_logger(__name__)
a : Optional[Any] = {"""vocab_file""": """vocab.json"... | 613 | def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | 1 |
def snake_case__ ( lowercase ):
if not isinstance(lowercase , lowercase ):
raise ValueError("multiplicative_persistence() only accepts integral values" )
if num < 0:
raise ValueError("multiplicative_persistence() does not accept negative values" )
lowerCAmelCase_: ... | 613 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | 1 |
import re
def snake_case__ ( lowercase ):
return [char.split() for char in re.split(r"[^ a-z A-Z 0-9 \s]" , str_ )]
def snake_case__ ( lowercase ):
lowerCAmelCase_: Optional[Any] = split_input(str_ )
return "".join(
["".join([char.capitalize() for char in sub_s... | 613 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 1 |
a : Tuple = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
a : Any = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
a : Dict = {
0: """Sunday""",
1: """Monday""",
2: """Tuesday""",
3: """Wednesday""",
4: """Thursday""",
5: """Friday""",
6: """Saturday"... | 613 | from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | 1 |
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,
iflatmap_unordered,
map_nested,
temp_... | 613 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 613 | 1 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
if is_torch_availa... | 613 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase_ ( lowerCamelCase ):
a__ = ['''image_processor''', '''tokenizer''']
a__ = '''CLIPImageProcessor'''
a__ = ('''XLM... | 0 | from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | 0 |
import datasets
from .evaluate import evaluate
__snake_case = '''\
@inproceedings{Rajpurkar2016SQuAD10,
title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},
author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
booktitle={EMNLP},
year={2016... | 1 | import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available
... | 613 | 0 |
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE_ ( _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 even numbers, all multiples... | 2 | def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLD... | 3 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCamelCase : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''... | 4 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MA... | 613 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=_SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowercase : str = ['''note_seq''']
def __init__( self , *_lowercase , **_lowe... | 5 | import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from transfor... | 6 | class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 0 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def _snake_case ( _snake_case : int ) -> datetime:
'''simple docstring'''
_A = year % 19
_A = year % 4
_A = year % 7
_A = math.floor(year / 1_00 )
... | 7 | 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, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
lowercase__ : int = '''https://www.indeed.co.in/jobs?q=mobile+app+development&l='''
def _lowerCAmelCase ( ... | 8 | import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 613 | 0 |
from ....utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def __init__( self : List[Any] , _snake_case : str , _snake_case : List[Any... | 9 | from __future__ import annotations
def snake_case__ ( lowercase , lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | 0 |
import os
def _snake_case ( __snake_case = "matrix.txt" ):
with open(os.path.join(os.path.dirname(__snake_case ) , __snake_case ) ) as in_file:
_UpperCamelCase = in_file.read()
_UpperCamelCase = [[int(__snake_case ) for cell in row.split('''... | 10 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | 0 |
'''simple docstring'''
from math import factorial
class __A :
'''simple docstring'''
def __init__(self , A , A ) -> str:
"""simple docstring"""
_a = real
if isinstance(A , A ):
_a = [1] * rank
else:... | 11 | import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTesterM... | 613 | 0 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
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 import ConfigT... | 12 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | 0 |
'''simple docstring'''
from functools import reduce
A__ : Union[str, Any] = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290... | 13 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 0 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
a__ = TypeVar('''T''')
a__ = Union[List[T], Tuple[T, ...]]
a__ = Union[T, List[T], Dict[str, T]]
a__ = Union[str, bytes, os.PathLike]
| 14 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 0 |
from __future__ import annotations
class A :
'''simple docstring'''
def __init__(self : Union[str, Any] , _UpperCAmelCase : int = 0 ) -> List[Any]:
"""simple docstring"""
lowercase__ = key
def lowerCa... | 15 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
... | 16 | def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | 0 |
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( _lowercase , unittest.TestCase ):
_lo... | 17 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelera... | 18 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 0 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def lowerCamelCase__ ( __snake_case ) -> Union[str, Any]:
"""simple docstring"""
def decorator(__snake_case ):
_UpperCamelCase = get... | 19 | from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | 0 |
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase_ (lowercase__ ... | 20 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 613 | 0 |
from typing import List
from .keymap import KEYMAP, get_character
def lowerCAmelCase_ ( lowerCamelCase ):
def decorator(lowerCamelCase ):
__magic_name__ : str =getattr(lowerCamelCase , """handle_key""" , [] )
handle += [key]
s... | 21 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_snake_case : Optional[int] = {
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE... | 22 | from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | 0 |
from ...configuration_utils import PretrainedConfig
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
A_ = """bert-generation"""
def __init__( self , _UpperCAmelCase=50358 , _UpperCAmelCase=1024 , _UpperCAmelCase=24 , _Uppe... | 23 | import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available
... | 613 | 0 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def _UpperCamelCase (_l... | 24 | def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | 0 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def lowerCamelCase__ ( _a = True , *_a , **_a):
if not is_tqdm_available():
raise ImportError("Accelerate's `tqdm` module requires `tqdm` to be insta... | 25 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 0 |
'''simple docstring'''
def _a ( _lowerCamelCase , _lowerCamelCase ) -> int:
"""simple docstring"""
while a != 0:
__snake_case , __snake_case : str = b % a, a
return b
def _a ( _lo... | 26 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MA... | 613 | 0 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_availab... | 27 | import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | 0 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class _a ... | 28 | class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
A_ = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}
try:
if not is_torch_availab... | 29 | 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, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 0 |
from __future__ import annotations
import math
__a = '2020.9.26'
__a = 'xcodz-dot, cclaus, dhruvmanila'
def lowerCamelCase__ ( _lowercase , _lowercase , _lowercase , _lowercase , _lowercase ):
'''simple docstring'''
if not all(isinstance(... | 30 | import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 613 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase__ : List[str] = {
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE... | 31 | from __future__ import annotations
def snake_case__ ( lowercase , lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | 0 |
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
UpperCAmelCase_ = logging... | 32 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | 0 |
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 __magic_name__ (unittest.TestCase ):
'''simple docstring'''
... | 33 | import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTesterM... | 613 | 0 |
"""simple docstring"""
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_C... | 34 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a_ :Optional[Any] = logging.get_logger(__name__)
a_ :Dict = {
'SenseTime/deformable-detr': 'https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 35 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
__lowercase : Dict = {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''... | 36 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 0 |
from __future__ import annotations
def UpperCamelCase_ ( __a , __a ) -> float:
a__ : Tuple = sorted(numsa + numsa )
a__, a__ : str = divmod(len(__a ) , 2 )
if mod == 1:
return all_numbers[div]
else:
return (all_num... | 37 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_... | 38 | def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: list[list[str]] = [[] for _ in range(lowercase )]
lowerCAmelCase_: Optional[Any] = key - 1
if key <= 0:
raise ValueError("Height of grid can't be 0 or negative" )
if key == 1 or len(lowercase ... | 613 | 0 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Da... | 39 | import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,
... | 613 | 0 |
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def UpperCamelCase ( snake_case__ : Union[dict, list, tuple, torch.Tensor] ) ... | 40 | import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def snake_case__ ( lowercase , l... | 613 | 0 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
lowerCAmelCase__ = '''\
@inproceedings{popovic-2015-chrf,
title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",
author = "Popovi{\'c}, Maja",
book... | 41 | from math import isqrt
def snake_case__ ( lowercase ):
lowerCAmelCase_: List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , lowercase , lowercase ):
lowerCAmelCas... | 613 | 0 |
'''simple docstring'''
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
A_ = 0
A_ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0,... | 42 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 613 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase = logging.get_logger(__name__)
lowerCAmelCase = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'
),
#... | 43 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Any = logging.get_logger(__name__)
a : List[str] = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowercase ( Upper... | 613 | 0 |
'''simple docstring'''
UpperCAmelCase_ : List[Any] = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
UpperC... | 44 | from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] ... | 613 | 0 |
def A ( lowercase__ : int ) -> bool:
return str(lowercase__ ) == str(lowercase__ )[::-1]
def A ( lowercase__ : int ) -> int:
return int(lowercase__ ) + int(str(lowercase__ )[::-1] )
def A ( lowercase__ : int = 1_0000 ) -> int:
UpperCamelCase__ :int = ... | 45 | import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_available
... | 613 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_( _lowerCamelCase ) -> bool:
'''simple docstring'''
return len(set(_lowerCamelCase ) ) == len(_lowerCamelCase )
if __name__ == "__main__":
import doctest
doctest.testmod(... | 46 | def snake_case__ ( lowercase , lowercase ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
import doctest
doctest.testm... | 613 | 0 |
def UpperCAmelCase__ ( lowerCamelCase_ : list ):
if len(lowerCamelCase_ ) <= 1:
return lst
__a : str = 1
while i < len(lowerCamelCase_ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
__a , __a ... | 47 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 0 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 48 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MA... | 613 | 0 |
"""simple docstring"""
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
_lowercase : str = '\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and ... | 49 | import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
a : List[str] = False
class _lowercase ( unittest.TestCase ):
... | 613 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
f... | 50 | class _lowercase :
'''simple docstring'''
def __init__( self ):
lowerCAmelCase_: dict[str, TrieNode] = {} # Mapping from char to TrieNode
lowerCAmelCase_: str = False
def _a ( self , lowerCamelCase__ ):
for word in ... | 613 | 0 |
'''simple docstring'''
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassi... | 51 | 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, TimestepEmbedding, Timesteps
from .modeling_utils import Mo... | 613 | 0 |
"""simple docstring"""
A = {
"joule": 1.0,
"kilojoule": 1_000,
"megajoule": 1_000_000,
"gigajoule": 1_000_000_000,
"wattsecond": 1.0,
"watthour": 3_600,
"kilowatthour": 3_600_000,
"newtonmeter": 1.0,
"calorie_nutr": 4_186.8,
"kilocalorie... | 52 | import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ...utils import Te... | 613 | 0 |
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_snake_case : Tuple = get_tests_d... | 53 | from __future__ import annotations
def snake_case__ ( lowercase , lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case__ ( lowercase , lowercase , lowercase ):
... | 613 | 0 |
from ... import PretrainedConfig
__lowercase : List[str] ={
"""sijunhe/nezha-cn-base""": """https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json""",
}
class A ( __lowercase ):
_snake_case =NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
_snake_case... | 54 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : List[str] = {
"""xlm-mlm-en-2048""": """https://hugg... | 613 | 0 |
from ...configuration_utils import PretrainedConfig
SCREAMING_SNAKE_CASE :Optional[int] = {
'google/tapas-base-finetuned-sqa': (
'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
),
'google/tapas-base-finetuned-wtq': (
'https://huggingface.... | 55 | import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTesterM... | 613 | 0 |
'''simple docstring'''
from math import factorial
_a : dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def _a (lowercase__ : int ) -> int:
"""simple docstring"""
if not isinstance(lowercase__ , lowercase__ ):
rai... | 56 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json""",... | 613 | 0 |
from abc import ABC, abstractmethod
from typing import List, Optional
class _lowerCAmelCase( UpperCAmelCase_ ):
"""simple docstring"""
def __init__( self ):
# test for the above condition
self.test()
de... | 57 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Any = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowercase ( UpperCAmelCase__ ):
... | 613 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 58 | def snake_case__ ( lowercase ):
lowerCAmelCase_: Union[str, Any] = [1]
lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_: int = 0, 0, 0
lowerCAmelCase_: Union[str, Any] = ugly_nums[ia] * 2
lowerCAmelCase_: str = ugly_nums[ia] * 3
lowerCAmelCase_... | 613 | 0 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
log... | 59 | import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def snake_case__ ( lowercase ):
return Envi... | 613 | 0 |
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