code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from 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 __Upper... | 642 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
def lowercase__ ( lowerCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[int]:
'... | 642 | 1 |
"""simple docstring"""
from itertools import product
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> list[int]:
'''simple docstring'''
a__ : Optional[Any] = sides_number
a__ : Tuple = max_face_number * dice_number
a__ : A... | 642 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffus... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
__UpperCAmelCase = TypeVar('''T''')
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
return (position - 1) // 2
def... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int ) -> list[int]:
'''simple docstring'''
a__ : Tuple = [True] * limit
a__ : Tuple = False
a__ : int = False
a__ : Tuple = True
for i in range(3... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
__UpperCAmelCase = [True] * 100_0001
__UpperCAmelCase = 2
while i * i <= 100_0000:
if seive[i]:
for j in range(i * i, 100_0001, i):
__UpperCAmelCase = False
i += 1
def lowercase__ ( lowerCAmelCase__ ... | 642 |
"""simple docstring"""
__UpperCAmelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def lowercase__ ( lowerCAmelCase__ : Dict , lowerCAmelCase__ : Optional[in... | 642 | 1 |
"""simple docstring"""
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
__UpperCAmelCase = {
'''facebook/maskformer-swin-b... | 642 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __UpperCAmelCase ( unittest.TestCase , _UpperCamelCase ):
def UpperCAmelCase ( self : Dict ) -> List[Any]:
'''simple do... | 642 | 1 |
"""simple docstring"""
import math
import sys
def lowercase__ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
a__ : Dict = ""
try:
with open(lowerCAmelCase__ , "rb" ) as binary_file:
a__ : List[str] = binary_file.read()
... | 642 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
__UpperCAmelCase = False
class __UpperCAmelCase ( unittest.TestCase ... | 642 | 1 |
"""simple docstring"""
import heapq
def lowercase__ ( lowerCAmelCase__ : dict ) -> set[int]:
'''simple docstring'''
a__ : list[list] = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be fi... | 642 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__UpperCAmelCase = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''attn''': '... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import gcd
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int = 2 , lowerCAmelCase__ : int = 1 , lowerCAmelCase__ : int = 3 , ) -> int | None:
'''simp... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> tuple[int, int]:
'''simple docstring'''
if b == 0:
return (1, 0)
((a__) , (a__)) : List[Any] = extended_euclid(lowerCA... | 642 | 1 |
"""simple docstring"""
import socket
def lowercase__ ( ) -> Any:
'''simple docstring'''
a__ : int = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
a__ : Any = socket.gethostname()
a__ : Union[str, Any] = 1_2_3_1_2
sock.connect((host, port)... | 642 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__UpperCAmelCase = logging.get_logger(__name__)
clas... | 642 | 1 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
a__ : list[list[int]] = [[0 for _ in range(lowerCAmelCase__ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
a__ : List[str] = 1
for n in range(m + 1 ... | 642 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
a__ : Tuple = prime_factors(lowerCAmelCase__ )
if is_square_free(lowerCA... | 642 | 1 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi... | 642 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWater... | 642 | 1 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : int , ... | 642 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversat... | 642 | 1 |
"""simple docstring"""
import cva
import numpy as np
class __UpperCAmelCase :
def __init__( self : Any , a_ : float , a_ : int ) -> List[str]:
'''simple docstring'''
if k in (0.04, 0.06):
a__ : Any = k
a__ : Dict = window... | 642 |
"""simple docstring"""
from sklearn.metrics import matthews_corrcoef
import datasets
__UpperCAmelCase = '''
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It ... | 642 | 1 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__UpperCAmelCase = '''\
'''
__UpperCAmelCase = '''
Perplexity (PPL) is one of the most com... | 642 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_... | 642 | 1 |
"""simple docstring"""
__UpperCAmelCase = '''
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
__UpperCAmelCase = [{'''type''': '''code''', '''content''': INST... | 642 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __UpperCAmelCase ( _UpperCamelCase ):
# to overwrite a... | 642 | 1 |
"""simple docstring"""
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
__UpperCAmelCase = '''scheduler_config.json'''
class ... | 642 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 642 | 1 |
"""simple docstring"""
import math
def lowercase__ ( ) -> None:
'''simple docstring'''
a__ : str = input("Enter message: " )
a__ : Any = int(input(F"Enter key [2-{len(lowerCAmelCase__ ) - 1}]: " ) )
a__ : Dict = input("Encryption/Decryption [e/d]: " ... | 642 |
"""simple docstring"""
import pytest
import datasets
# Import fixture modules as plugins
__UpperCAmelCase = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def lowercase__ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str... | 642 | 1 |
"""simple docstring"""
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pip... | 642 |
"""simple docstring"""
import functools
def lowercase__ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
'''simple docstring'''
a__ : Any = len(lowerCAmelCase__ )
a__ : Optional[int] = len(lowerCAmelCase__ )
@functools.cache
d... | 642 | 1 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
if not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ) or number < 0:
raise ValueError("Input must be a non-negative integer" )
a__ : Optional[Any] = 0
... | 642 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : str ) -> list[int]:
'''simple docstring'''
a__ : List[str] = [0 for i in range(len(lowerCAmelCase__ ) )]
# initialize interval's left pointer and right pointer
a__ , a__ : int = 0, 0
for i in ra... | 642 | 1 |
"""simple docstring"""
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
__UpperCAmel... | 642 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
__UpperCAmelCase = loggi... | 642 | 1 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__UpperCAmelCase = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''attn''': '... | 642 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( lowerCAmelCase__ : Union[str... | 642 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( lowerCAmelCase__ : Tuple , lowerCAmelCase__ : List[Any... | 642 |
"""simple docstring"""
import os
def lowercase__ ( ) -> Optional[Any]:
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase__ ) + "/p022_names.txt" ) as file:
a__ : Optional[int] = str(file.readlines()[0] )
a__ : Optional[int] = names.repla... | 642 | 1 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('''>=''', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch... | 642 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
def lowercase__ ( lowerCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[int]:
'... | 642 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effect... | 642 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffus... | 642 | 1 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : dict ) -> bool:
'''simple docstring'''
a__ : set[int] = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
a__ : set[int] = set()
return any(
node not in vis... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int ) -> list[int]:
'''simple docstring'''
a__ : Tuple = [True] * limit
a__ : Tuple = False
a__ : int = False
a__ : Tuple = True
for i in range(3... | 642 | 1 |
"""simple docstring"""
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
__UpperCAmelCase = models.Sequential()... | 642 |
"""simple docstring"""
__UpperCAmelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def lowercase__ ( lowerCAmelCase__ : Dict , lowerCAmelCase__ : Optional[in... | 642 | 1 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
__UpperCAmelCase = logging.getLogger(__name__)
class __UpperCAmelCase ( _UpperCamelCase ):
__lowerCamelCase : List[str] = "masked_bert"
def __init__( self ... | 642 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __UpperCAmelCase ( unittest.TestCase , _UpperCamelCase ):
def UpperCAmelCase ( self : Dict ) -> List[Any]:
'''simple do... | 642 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, l... | 642 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
__UpperCAmelCase = False
class __UpperCAmelCase ( unittest.TestCase ... | 642 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from a... | 642 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__UpperCAmelCase = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''attn''': '... | 642 | 1 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> tuple[int, int]:
'''simple docstring'''
if b == 0:
return (1, 0)
((a__) , (a__)) : List[Any] = extended_euclid(lowerCA... | 642 | 1 |
"""simple docstring"""
__UpperCAmelCase = [
'''Audio''',
'''Array2D''',
'''Array3D''',
'''Array4D''',
'''Array5D''',
'''ClassLabel''',
'''Features''',
'''Sequence''',
'''Value''',
'''Image''',
'''Translation''',
'''TranslationVariableLanguages''',
]
fro... | 642 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__UpperCAmelCase = logging.get_logger(__name__)
clas... | 642 | 1 |
"""simple docstring"""
import pytest
import datasets
# Import fixture modules as plugins
__UpperCAmelCase = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def lowercase__ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str... | 642 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
a__ : Tuple = prime_factors(lowerCAmelCase__ )
if is_square_free(lowerCA... | 642 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCAmelCase ( _UpperCamelCase ):
__lowerCamelCase : List[Any] = ["image_processor", "tokenizer"]
__lowerCamelCase ... | 642 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWater... | 642 | 1 |
"""simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __UpperCAmelCase ( unittest.TestCase ):
def UpperCAmelCase ... | 642 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversat... | 642 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''microsoft/f... | 642 |
"""simple docstring"""
from sklearn.metrics import matthews_corrcoef
import datasets
__UpperCAmelCase = '''
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It ... | 642 | 1 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.... | 642 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_... | 642 | 1 |
"""simple docstring"""
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowercase__ ( lowerCAmelCase__ : str = "laptop" ) -> DataFrame:
'''simple docstring'''
a__ : Union[str, Any] = F"https://www.amazon... | 642 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __UpperCAmelCase ( _UpperCamelCase ):
# to overwrite a... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : bool , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : float ) -> int:
... | 642 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 642 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 642 |
"""simple docstring"""
import pytest
import datasets
# Import fixture modules as plugins
__UpperCAmelCase = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def lowercase__ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str... | 642 | 1 |
"""simple docstring"""
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
f... | 642 |
"""simple docstring"""
import functools
def lowercase__ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
'''simple docstring'''
a__ : Any = len(lowerCAmelCase__ )
a__ : Optional[int] = len(lowerCAmelCase__ )
@functools.cache
d... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int ) -> list[int]:
'''simple docstring'''
a__ : Tuple = [True] * limit
a__ : Tuple = False
a__ : int = False
a__ : Tuple = True
for i in range(3... | 642 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : str ) -> list[int]:
'''simple docstring'''
a__ : List[str] = [0 for i in range(len(lowerCAmelCase__ ) )]
# initialize interval's left pointer and right pointer
a__ , a__ : int = 0, 0
for i in ra... | 642 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'''configuration_clipseg''': [
'''CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''CLIPSegConfig''',
'''CLIPSegT... | 642 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
__UpperCAmelCase = loggi... | 642 | 1 |
"""simple docstring"""
# Imports
import numpy as np
class __UpperCAmelCase :
def __init__( self : Any , a_ : List[Any]=None , a_ : Optional[int]=None , a_ : Tuple=None , a_ : List[str]=None , a_ : int=None ) -> List[str]:
'''simple docstring'''
... | 642 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( lowerCAmelCase__ : Union[str... | 642 | 1 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : Any , lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> List[Any]:
'''simple docstring'''
if height >= 1:
move_tower(height - 1 , l... | 642 |
"""simple docstring"""
import os
def lowercase__ ( ) -> Optional[Any]:
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase__ ) + "/p022_names.txt" ) as file:
a__ : Optional[int] = str(file.readlines()[0] )
a__ : Optional[int] = names.repla... | 642 | 1 |
"""simple docstring"""
__UpperCAmelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def lowercase__ ( lowerCAmelCase__ : Dict , lowerCAmelCase__ : Optional[in... | 642 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
def lowercase__ ( lowerCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[int]:
'... | 642 | 1 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowercase__ ( ) -> int:
'''simple docstring'''
a__ : Dict = ArgumentParser(
descrip... | 642 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffus... | 642 | 1 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : str ) -> list[int]:
'''simple docstring'''
a__ : List[str] = [0 for i in range(len(lowerCAmelCase__ ) )]
# initialize interval's left pointer and right pointer
a__ , a__ : int = 0, 0
for i in ra... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int ) -> list[int]:
'''simple docstring'''
a__ : Tuple = [True] * limit
a__ : Tuple = False
a__ : int = False
a__ : Tuple = True
for i in range(3... | 642 | 1 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowercase__ ( lowerCAmelCase__ : int ) -> Tuple:
'''simple docstring'''
a__ : int = [
"decoder.ver... | 642 |
"""simple docstring"""
__UpperCAmelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def lowercase__ ( lowerCAmelCase__ : Dict , lowerCAmelCase__ : Optional[in... | 642 | 1 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def lowercase__ ( lowerCAmelCase__ : np.ndarray , lowerCAmelCase__ : float ) -> np.ndarray:
'''simple docstring'''
# For applying gaussian function for each element in matrix.
a__ ... | 642 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __UpperCAmelCase ( unittest.TestCase , _UpperCamelCase ):
def UpperCAmelCase ( self : Dict ) -> List[Any]:
'''simple do... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def lowercase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
a__ : dict[int, int] = {}
a__ : int = 2
while True:
a__ : Tuple = factor_map.pop(... | 642 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
__UpperCAmelCase = False
class __UpperCAmelCase ( unittest.TestCase ... | 642 | 1 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def lowercase__ ( lowerCAmelCase__ : Any , lowerCAmelCase__ : Union[s... | 642 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__UpperCAmelCase = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''attn''': '... | 642 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __UpperCAmelCase ( _UpperCamelCase ):
def __init__( self : List[Any] , *a_ : Option... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> tuple[int, int]:
'''simple docstring'''
if b == 0:
return (1, 0)
((a__) , (a__)) : List[Any] = extended_euclid(lowerCA... | 642 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCamelCase )
class __UpperCAmelCase ( _UpperCamelCase ):
__lowerCamelCas... | 642 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__UpperCAmelCase = logging.get_logger(__name__)
clas... | 642 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCAmelCase = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG... | 642 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
a__ : Tuple = prime_factors(lowerCAmelCase__ )
if is_square_free(lowerCA... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
class __UpperCAmelCase :
def __init__( self : Optional[Any] , a_ : int ) -> None:
'''simple docstring'''
a__ : Union[str, Any] = value
a__ : Node |... | 642 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWater... | 642 | 1 |
"""simple docstring"""
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class __UpperCAmelCase ( tf.keras.optimizers.schedul... | 642 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversat... | 642 | 1 |
"""simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__UpperCAmelCase = '''<<<<<<< This should probably be modified because it mentions: '''
__Uppe... | 642 |
"""simple docstring"""
from sklearn.metrics import matthews_corrcoef
import datasets
__UpperCAmelCase = '''
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It ... | 642 | 1 |
"""simple docstring"""
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __UpperCAmelCase :
def __init__( self : List[Any] , a_ : Dict ) -> str:
'''simple docstring'''
a__ : Dict = data
a__ : List... | 642 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_... | 642 | 1 |
"""simple docstring"""
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
__UpperCAmelCase = '''▁'''
__UpperCAmelCase = {'''vocab_file''': ... | 642 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __UpperCAmelCase ( _UpperCamelCase ):
# to overwrite a... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowercase__ ( lowerCAmelCase__ : str ) -> None:
'''simple docstring'''
a__ , a__ : Optional[Any] = analyze_text(lowerCAmelCase... | 642 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 642 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image... | 642 |
"""simple docstring"""
import pytest
import datasets
# Import fixture modules as plugins
__UpperCAmelCase = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def lowercase__ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str... | 642 | 1 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_t... | 642 |
"""simple docstring"""
import functools
def lowercase__ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
'''simple docstring'''
a__ : Any = len(lowerCAmelCase__ )
a__ : Optional[int] = len(lowerCAmelCase__ )
@functools.cache
d... | 642 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetim... | 642 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : str ) -> list[int]:
'''simple docstring'''
a__ : List[str] = [0 for i in range(len(lowerCAmelCase__ ) )]
# initialize interval's left pointer and right pointer
a__ , a__ : int = 0, 0
for i in ra... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[list[str]] , lowerCAmelCase__ : int , ) ... | 642 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
__UpperCAmelCase = loggi... | 642 | 1 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : int ) -> str:
'''simple docstring'''
if isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise TypeError("'float' object cannot be interpreted as an integer" )
if isinstance(lowerCAmelCase__ ... | 642 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( lowerCAmelCase__ : Union[str... | 642 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart... | 642 |
"""simple docstring"""
import os
def lowercase__ ( ) -> Optional[Any]:
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase__ ) + "/p022_names.txt" ) as file:
a__ : Optional[int] = str(file.readlines()[0] )
a__ : Optional[int] = names.repla... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
__UpperCAmelCase = tuple[int, int, int]
__UpperCAmelCase = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
__UpperCAmelCase = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
# ------------------... | 642 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
def lowercase__ ( lowerCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[int]:
'... | 642 | 1 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowercase__ ( ) -> Tuple:
'''simple docstring'''
a__ : List[Any] = {
"repo_name": ["test_repo1", "tes... | 642 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffus... | 642 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingface.co/facebook/s2t-small-librispeech-asr/r... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int ) -> list[int]:
'''simple docstring'''
a__ : Tuple = [True] * limit
a__ : Tuple = False
a__ : int = False
a__ : Tuple = True
for i in range(3... | 642 | 1 |
"""simple docstring"""
def lowercase__ ( ) -> int:
'''simple docstring'''
for n in range(1 , 1_0_0_0_0_0_0 ):
yield n * (n + 1) // 2
def lowercase__ ( lowerCAmelCase__ : List[str] ) -> str:
'''simple docstring'''
a__ : Tuple = 1
... | 642 |
"""simple docstring"""
__UpperCAmelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def lowercase__ ( lowerCAmelCase__ : Dict , lowerCAmelCase__ : Optional[in... | 642 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_visi... | 642 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __UpperCAmelCase ( unittest.TestCase , _UpperCamelCase ):
def UpperCAmelCase ( self : Dict ) -> List[Any]:
'''simple do... | 642 | 1 |
"""simple docstring"""
from copy import deepcopy
class __UpperCAmelCase :
def __init__( self : List[Any] , a_ : list[int] | None = None , a_ : int | None = None ) -> None:
'''simple docstring'''
if arr is None and size is not None:
a__ : Op... | 642 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
__UpperCAmelCase = False
class __UpperCAmelCase ( unittest.TestCase ... | 642 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCAmelCase = {'''configuration_reformer''': ['''REFORMER_PRETRAINED_CONFI... | 642 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__UpperCAmelCase = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''attn''': '... | 642 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> tuple[int, int]:
'''simple docstring'''
if b == 0:
return (1, 0)
((a__) , (a__)) : List[Any] = extended_euclid(lowerCA... | 642 | 1 |
"""simple docstring"""
class __UpperCAmelCase ( _UpperCamelCase ):
pass
class __UpperCAmelCase ( _UpperCamelCase ):
pass
class __UpperCAmelCase :
def __init__( self : int ) -> Dict:
'''simple docstring'''
a__ : Opti... | 642 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__UpperCAmelCase = logging.get_logger(__name__)
clas... | 642 | 1 |
"""simple docstring"""
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transfor... | 642 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
a__ : Tuple = prime_factors(lowerCAmelCase__ )
if is_square_free(lowerCA... | 642 | 1 |
"""simple docstring"""
from math import pow, sqrt
def lowercase__ ( *lowerCAmelCase__ : float ) -> bool:
'''simple docstring'''
a__ : List[Any] = len(lowerCAmelCase__ ) > 0 and all(value > 0.0 for value in values )
return result
def lowercase__ ( ... | 642 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWater... | 642 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
__UpperCAmelCase = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSp... | 642 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversat... | 642 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test im... | 642 |
"""simple docstring"""
from sklearn.metrics import matthews_corrcoef
import datasets
__UpperCAmelCase = '''
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It ... | 642 | 1 |
"""simple docstring"""
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
... | 642 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_... | 642 | 1 |
"""simple docstring"""
import random
from .binary_exp_mod import bin_exp_mod
def lowercase__ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : int=1_0_0_0 ) -> Any:
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
return n == ... | 642 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __UpperCAmelCase ( _UpperCamelCase ):
# to overwrite a... | 642 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging... | 642 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 642 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def lowercase__ ( lower... | 642 |
"""simple docstring"""
import pytest
import datasets
# Import fixture modules as plugins
__UpperCAmelCase = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def lowercase__ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str... | 642 | 1 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
__UpperCAmelCase = '''\
@misc{wu2016googles,
title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation}... | 642 |
"""simple docstring"""
import functools
def lowercase__ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
'''simple docstring'''
a__ : Any = len(lowerCAmelCase__ )
a__ : Optional[int] = len(lowerCAmelCase__ )
@functools.cache
d... | 642 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
fr... | 642 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : str ) -> list[int]:
'''simple docstring'''
a__ : List[str] = [0 for i in range(len(lowerCAmelCase__ ) )]
# initialize interval's left pointer and right pointer
a__ , a__ : int = 0, 0
for i in ra... | 642 | 1 |
"""simple docstring"""
import fire
from utils import calculate_rouge, save_json
def lowercase__ ( lowerCAmelCase__ : Union[str, Any] , lowerCAmelCase__ : int , lowerCAmelCase__ : Optional[Any]=None , **lowerCAmelCase__ : Dict ) -> Dict:
''... | 642 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
__UpperCAmelCase = loggi... | 642 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __UpperCAmelCase ( _UpperCamelCase , unittest.TestCase ):
__low... | 642 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( lowerCAmelCase__ : Union[str... | 642 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : bool , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : float ) -> int:
... | 642 |
"""simple docstring"""
import os
def lowercase__ ( ) -> Optional[Any]:
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase__ ) + "/p022_names.txt" ) as file:
a__ : Optional[int] = str(file.readlines()[0] )
a__ : Optional[int] = names.repla... | 642 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''Salesforce/blip-vqa-base''': '''https://huggingface.co/Salesfor... | 642 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
def lowercase__ ( lowerCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[int]:
'... | 642 | 1 |
"""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
from transformers ... | 642 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffus... | 642 | 1 |
"""simple docstring"""
from math import sqrt
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
a__ : Optional[int] = 0
for i in range(1 , int(sqrt(lowerCAmelCase__ ) + 1 ) ):
if n % i == 0 and i != sqrt(lowerCAmelCase__ ... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int ) -> list[int]:
'''simple docstring'''
a__ : Tuple = [True] * limit
a__ : Tuple = False
a__ : int = False
a__ : Tuple = True
for i in range(3... | 642 | 1 |
"""simple docstring"""
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, ... | 642 |
"""simple docstring"""
__UpperCAmelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def lowercase__ ( lowerCAmelCase__ : Dict , lowerCAmelCase__ : Optional[in... | 642 | 1 |
"""simple docstring"""
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def lowercase__ ( lowerCAmelCase__ : Union[str, Any] ) -> Tuple:
'''simple docstring'''
if not is_accelerate_availabl... | 642 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __UpperCAmelCase ( unittest.TestCase , _UpperCamelCase ):
def UpperCAmelCase ( self : Dict ) -> List[Any]:
'''simple do... | 642 | 1 |
"""simple docstring"""
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def lowercase__ ( lowerCAmelCase__ : Dict ) -> List[str]:
'''simple docstring'''
a__ : Tuple = {}
a__ : Optional[int] = job["started_at"... | 642 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
__UpperCAmelCase = False
class __UpperCAmelCase ( unittest.TestCase ... | 642 | 1 |
"""simple docstring"""
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def lowercase__ ( lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Optional[int]=1 ) -> Optional[int]:
'''simple docstring'''
i... | 642 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__UpperCAmelCase = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''attn''': '... | 642 | 1 |
"""simple docstring"""
import argparse
from collections import defaultdict
import yaml
__UpperCAmelCase = '''docs/source/en/_toctree.yml'''
def lowercase__ ( lowerCAmelCase__ : str ) -> int:
'''simple docstring'''
a__ : Any = defaultdict(lowerCAmelCase__ )... | 642 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> tuple[int, int]:
'''simple docstring'''
if b == 0:
return (1, 0)
((a__) , (a__)) : List[Any] = extended_euclid(lowerCA... | 642 | 1 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversat... | 642 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__UpperCAmelCase = logging.get_logger(__name__)
clas... | 642 | 1 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : int ) -> float:
'''simple docstring'''
if principal <= 0:
raise Exception("Principal borrowed must be > 0" )
if rate_per_annum < 0... | 642 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowercase__ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
a__ : Tuple = prime_factors(lowerCAmelCase__ )
if is_square_free(lowerCA... | 642 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCAmelCase ( _UpperCamelCase ):
__lowerCamelCase : Dict = ["image_processor", "tokenizer"]
__lowerCamelCase : D... | 642 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWater... | 642 | 1 |
"""simple docstring"""
import argparse
from collections import defaultdict
def lowercase__ ( lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Any , lowerCAmelCase__ : Dict , lowerCAmelCase__ : int , lowerCAmelCase__ : Tuple ) -> Tuple:
... | 642 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversat... | 642 | 1 |
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