code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['em... | 430 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittest.TestCase ):
@pr... | 612 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_onnx_available,
is_torch... | 424 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_M... | 612 | 0 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : Any = """T5Config"""
class _low... | 385 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def __A(lowerCAmelCase ) -> Dict:
"""simple docstring"""
_UpperCamelCase = os.path.join(args.tf_model_dir , """parameters.json""" )
_UpperCamelC... | 612 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_availab... | 585 |
import warnings
from .generation import TFGenerationMixin
class lowerCAmelCase__ ( __lowercase ):
# warning at import time
warnings.warn(
"Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
"be removed in Transform... | 612 | 0 |
def _lowerCAmelCase ( A__ , A__ ):
lowercase__ = ''
for word_or_phrase in separated:
if not isinstance(A__ , A__ ):
raise Exception('join() accepts only strings to be joined' )
joined += word_or_phrase + separator
return joined.st... | 622 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 612 | 0 |
"""simple docstring"""
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
impo... | 355 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
from ... | 612 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common ... | 237 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers impo... | 612 | 0 |
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mas... | 202 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
IMA... | 612 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Union[str, Any] = (boundary[1] - boundary[0]) / steps
_lowerCAmelCase : int = boundary[0]
_lowerCAmelCase : Option... | 259 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("T")
lowerCamelCase__ = TypeVar("U")
class lowerCAmelCase__ ( Generic[T, U] ):
def __init__( self , a , a ) ... | 612 | 0 |
'''simple docstring'''
def __snake_case ( lowerCamelCase_ : List[str] ):
'''simple docstring'''
__magic_name__ = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def __snake_case ( lowerCamelCase_ : int = 5000 ):
'''simple docstring'''... | 664 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@req... | 612 | 0 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( a_ : Dict = "matrix.txt" ):
with open(os.path.join(os.path.dirname(a_ ) , a_ ) ) as in_file:
__a = in_file.read()
__a = [[int(a_ ) for... | 539 |
# Copyright 2023 The HuggingFace Inc. 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 app... | 612 | 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_v... | 430 |
from collections.abc import Sequence
def __A(lowerCAmelCase = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_UpperCamelCase = nums[0]
for i in range(1 , len(lowerCAmelCase ) ):
_U... | 612 | 0 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .r... | 424 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
import pprint
import requests
__lowerCamelCase : Optional[Any] = """https://zenquotes.io/api"""
def A__ ( ):
'''simple docstring'''
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def A__ ( ):
'''simple docstring'''
... | 385 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def A_ ( a ) -> Union[str, Any]:
'''simple docstring'''
raise NotImplementedError()
... | 612 | 0 |
'''simple docstring'''
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib imp... | 585 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers.ut... | 612 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
fr... | 622 |
def __A(lowerCAmelCase ) -> bool:
"""simple docstring"""
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
raise ValueError("""check_bouncy() accepts only integer arguments""" )
_UpperCamelCase = str(lowerCAmelCase )
_UpperCamelCase = """""".join(sort... | 612 | 0 |
"""simple docstring"""
def A_ ( snake_case__ , snake_case__ ) -> int:
return number | (1 << position)
def A_ ( snake_case__ , snake_case__ ) -> int:
return number & ~(1 << position)
def A_ ( snake_case__ , snake_case__ ) ... | 355 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( __lowercase ):
UpperCamelCase_ : int = (KDPMaDiscreteScheduler,)
UpperCamelCase_ : Optional[int... | 612 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class snake_case_ ( metaclass=__lowercase ):
__lowerCAmelCase = ["torch"]
def __init__( self , *a_ , **a_ ):
requires_backends(self , ["torch"] )
... | 237 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __A(lowerCAmelCase , lowerCAmelCase ) -> np.array:
"""simple docstring"""
_UpperCamelCase = F'{sampling_rate}'
_UpperCamelCase = """1"""
_UpperCam... | 612 | 0 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 202 |
import pprint
import requests
lowerCamelCase__ = "https://zenquotes.io/api"
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """... | 612 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def lowerCamelCase__ ( _lowerCamelCase = None ):
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
_lowerCAmelCase : str = nums[0... | 259 |
from __future__ import annotations
def __A(lowerCAmelCase , lowerCAmelCase ) -> list[list[int]]:
"""simple docstring"""
_UpperCamelCase = []
_UpperCamelCase = []
_UpperCamelCase = 0
_UpperCamelCase = sum(lowerCAmelCase )
create_st... | 612 | 0 |
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 | 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 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class _lowercase ( unittest.TestCase ):
'''simple docstring'''
def _a ( self ):
lowerCAmelCase_: ... | 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 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torc... | 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 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType
a : ... | 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 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 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 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
a : Optional[Any] = logging.get_logger(__name__)
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def __init__( self , *lowerCam... | 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 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class _lowercase ( enum.Enum ):
'''simp... | 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 math import factorial
def snake_case__ ( lowercase = 100 ):
return sum(map(lowercase , str(factorial(lowercase ) ) ) )
if __name__ == "__main__":
print(solution(int(input("""Enter the Number: """).strip()))) | 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 |
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
a : Optional[Any] = """▁""... | 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 os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[Any] = logging.get_logger(__name__)
a : Optional[Any] = {"""v... | 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 random
def snake_case__ ( lowercase ):
lowerCAmelCase_: Dict = num - 1
lowerCAmelCase_: Optional[Any] = 0
while s % 2 == 0:
lowerCAmelCase_: str = s // 2
t += 1
for _ in range(5 ):
lowerCAmelCase_: Dict = random.randrange(... | 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 ):
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive" )
lowerCAmelCase_: List[str] = str(bin(lowercase ) )[2:] # remove the leading "0b"
lowerCAmelCase_: List[str] = str(bin(lowerca... | 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
import math
def snake_case__ ( lowercase ):
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 of 3 are not primes
return False
# All 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 |
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFeature... | 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 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class _lowercase :
'''simple docstring'''
SCREAMING_SNAKE_CASE: Optional[Any] = None
def _a ( self ):
lowerCAmelCase_: Optional[int] ... | 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__ ( ):
lowerCAmelCase_: List[Any] = []
lowerCAmelCase_: Union[str, Any] = 1
while len(lowercase ) < 1E6:
constant.append(str(lowercase ) )
i += 1
lowerCAmelCase_: Optional[int] = "".join(lowercase )
return (
int(c... | 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 datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
a : Tuple = """\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},
title = {BLEU: a Method for Automati... | 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 |
a : Any = {
"""meter""": """m""",
"""kilometer""": """km""",
"""megametre""": """Mm""",
"""gigametre""": """Gm""",
"""terametre""": """Tm""",
"""petametre""": """Pm""",
"""exametre""": """Em""",
"""zettametre""": """Zm""",
"""yottametre""": """Ym""",
}
# Exponent ... | 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 |
# 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 | 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 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
a : Tuple = logging.getLogger(__name__)
if __name__ == "__main__":
a : ... | 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
class _lowercase :
'''simple docstring'''
def __init__( self , lowerCamelCase__=None ):
lowerCAmelCase_: Dict = data
lowerCAmelCase_: str = None
def __repr__( self ):
lowerCAmelCase_: ... | 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 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _lowercase ( unittest.TestCase , UpperCAmelCase__ ):
'''simple docstring'''
def _a ( self ):
lowerCAmelCase_: Dict = load_tool("text-classification" )... | 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_tokenizers_available, is_torch_available
a : Optional[int] = {
"""configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GraphormerConfig"""],
}
try:
if not is_tor... | 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 |
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def snake_case__ ( lowercase , lowercase , lowercase , lowercase=5 ):
# Adapted from https://github.com/pytorch/fairseq/blob/master/fairseq/models/roberta/hub_interface.py
assert masked_input.count("<... | 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 |
# 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
#
# Unless required by applicabl... | 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 warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : Optional[Any] = logging.get_logger(__name__)
a : int ... | 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 |
def snake_case__ ( lowercase ):
return str(lowercase ) == str(lowercase )[::-1]
def snake_case__ ( lowercase ):
return int(lowercase ) + int(str(lowercase )[::-1] )
def snake_case__ ( lowercase = 10000 ):
lowerCAmelCase_: str = []
for num in range(1 ... | 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 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, parse... | 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 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Dict = logging.get_logger(__name__)
a : Dict = {
"""google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
# See all PEGASUS models at htt... | 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 itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class _lowercase ( datasets.BuilderConfig ):
'''simple docstring'''
SCREAMING_SNAKE_CASE: Optional[da... | 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 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a : Tuple = re.compile(r"""\b(a|an|the)\b""", re.UNICODE)
a : Any = None
def snake_case__ ( ):
lowerCAmelCase_: Optional[int] = argparse.ArgumentPa... | 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 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a : Tuple = {"""configuration_opt""": ["""OPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """OPTCon... | 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 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : List[str] = logging.get_logger(__name__)
a : List[Any] = {
"""xlm-roberta-base""": """https:/... | 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 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class _lowercase ( ... | 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 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import ConfigMi... | 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 math
import qiskit
def snake_case__ ( lowercase = 1 , lowercase = 1 , lowercase = 1 ):
if (
isinstance(lowercase , lowercase )
or isinstance(lowercase , lowercase )
or isinstance(lowercase , lowercase )
):
raise Typ... | 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 |
import heapq
def snake_case__ ( lowercase ):
lowerCAmelCase_: list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Priority Queue
# heapq works with a min priority queue, so I used -1*len(v)... | 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 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 | 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 darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
a : List[str] = {
"""n_samples""": 6_4,
"""horizon""": 3_2,
"""num_inference_steps""": 2_0,
"""n_guide_steps""": 2, # can set to 0 for faster sampling, does not use value network
... | 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 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Optional[Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class _lowercase ( UpperCAmelC... | 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 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 | 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 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPanoramaPipeline,
UNeta... | 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 json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torc... | 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 __future__ import annotations
def snake_case__ ( lowercase , lowercase , lowercase , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("You cannot supply more or less than 2 values" )
elif electron_conc < 0:
raise ValueError("E... | 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 os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a : Optional[Any] = logging.get_logger(__name__)
a : Union[str, Any] ... | 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 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterM... | 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
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a : int = {
"""configuration_bridgetower""": [
"""BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BridgeTowerConfig""",
"""Bridge... | 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 |
def snake_case__ ( lowercase ):
if not isinstance(lowercase , lowercase ):
lowerCAmelCase_: List[str] = F'''Input value of [number={number}] must be an integer'''
raise TypeError(lowercase )
if number < 0:
return False
lowerCAmelCase_: Optional[int] ... | 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 collections import defaultdict
from math import ceil, sqrt
def snake_case__ ( lowercase = 1000000 , lowercase = 10 ):
lowerCAmelCase_: defaultdict = defaultdict(lowercase )
for outer_width in range(3 , (t_limit // 4) + 2 ):
if outer_width * outer_width > t_... | 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 manim import *
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def _a ( self ):
lowerCAmelCase_: List[str] = Rectangle(height=0.5 , width=0.5 )
lowerCAmelCase_: List[str] = Rectangle(height=0.4_6 , ... | 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 |
import argparse
import os
import re
import packaging.version
a : Optional[int] = """examples/"""
a : Dict = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.compile(r"""^_... | 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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a : List[Any] = {
"""configuration_roberta_prelayernorm""": [
"""ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_AR... | 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 |
import torch
from diffusers import DiffusionPipeline
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def __init__( self , lowerCamelCase__ , lowerCamelCase__ ):
super().__init__()
self.register_modules(unet=lowerCamelCase__ , ... | 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
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
a : Tuple = False
class _lowercase ( unittest.TestCase ):
'''simple docstring'''
... | 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 |
class _lowercase : # Public class to implement a graph
'''simple docstring'''
def __init__( self , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
lowerCAmelCase_: int = row
lowerCAmelCase_: Optional[Any] = co... | 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 ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
lowerCAmelCase_: List[Any] = len(lowercase )
lowerCAmelCase_: Optional[int] = max(lowercase )
lowerCAmelC... | 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 sklearn.metrics import recall_score
import datasets
a : Any = """
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where TP is the true positives and FN is the false negatives.
... | 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 unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, require_t... | 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 ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy_torch_and... | 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 itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
a : Any = (
"""4S 3H 2C 7S 5H""",
"""9D 8H 2C 6S 7H""",
"""2D 6D 9D TH 7D""",
"""TC 8C 2S JH 6C""",
"""JH 8S TH AH QH""",
"""TS KS 5S 9S AC""",
"""KD 6... | 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 logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, TokenC... | 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 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
... | 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 gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
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 as jnp
from flax.jax_utils import re... | 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 |
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_collator,... | 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
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
a : Dict = 1.054571817e-34 # unit of ℏ : J * s
a : str = 3e8 # unit of c : m * s^-1
def snake_case__ ( lowercase ,... | 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 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 | 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 itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFeatureE... | 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 pathlib import Path
import fire
from tqdm import tqdm
def snake_case__ ( lowercase="ro" , lowercase="en" , lowercase="wmt16" , lowercase=None ):
try:
import datasets
except (ModuleNotFoundError, ImportError):
raise ImportError("run pip install datasets" )
... | 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 |
import argparse
import json
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 Accele... | 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 |
from __future__ import annotations
from typing import Any
class _lowercase :
'''simple docstring'''
def __init__( self , lowerCamelCase__ ):
lowerCAmelCase_: Dict = num_of_nodes
lowerCAmelCase_: list[list[int]] = []
lowerCAmelCase_: ... | 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 |
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def __init__( self , lowerCamelCase__ , 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 __future__ import annotations
from decimal import Decimal
from numpy import array
def snake_case__ ( lowercase ):
lowerCAmelCase_: str = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works for 2x2 matrices
if len(lowercase ) =... | 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 |
class _lowercase :
'''simple docstring'''
def __init__( self , lowerCamelCase__ ):
lowerCAmelCase_: Optional[Any] = size
lowerCAmelCase_: List[str] = [0] * size
lowerCAmelCase_: str = [0] * size
@staticmethod
de... | 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 __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 | 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 Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutputWithP... | 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 inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...test_c... | 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 math
def snake_case__ ( lowercase , lowercase ):
lowerCAmelCase_: List[Any] = len(lowercase )
lowerCAmelCase_: Union[str, Any] = int(math.floor(math.sqrt(lowercase ) ) )
lowerCAmelCase_: Tuple = 0
while arr[min(lowercase , l... | 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 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
a : List[Any]... | 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 |
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 | 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 dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase__ )
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
# `task` is not a ClassVar since we want it ... | 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 |
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