code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def lowerCamelCase__ ():
_SCREAMING_SNAKE_CASE : List[str] = [randint(-1000, 1000 ) for i in range(10 )]
_SCREAMING_SNAKE_CASE : Union[str... | 325 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class lowerCAmelCase__( __lowercase , __lowercase ... | 325 | 1 |
from timeit import timeit
def lowerCamelCase__ (__lowerCamelCase ):
if number < 0:
raise ValueError("the value of input must not be negative" )
_SCREAMING_SNAKE_CASE : str = 0
while number:
number &= number - 1
result += 1
return... | 325 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Tuple = [0 for i in range(r + 1 )]
# nc0 = 1
_SCREAMING_SNAKE_CASE : Optional[int] = 1
for i in range(1, n + 1 ):
# to compute current row from pre... | 325 | 1 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forwar... | 325 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
UpperCamelCase__ =logging.getLogger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstri... | 325 | 1 |
import inspect
import unittest
from transformers import MobileNetVaConfig
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_configuration_common import ConfigTester
from ..... | 325 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class lowerCAmelCase__( __lowercase ... | 325 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class lowerCAmelCase__( __l... | 325 |
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 logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ... | 325 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase__ ={
'configuration_xlm': ['XLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'XLMConfig', 'XLMOnnxConfig'],
'tokenization_xlm': ['XLMTokenizer'],
}
try:
... | 325 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase__ =logging.get_logger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
def __init__( self , *__lowerCamelCase ... | 325 | 1 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowerCamelCase__ (__lowerCamelCase = "laptop" ):
_SCREAMING_SNAKE_CASE : Tuple = f"""https://www.amazon.in/laptop/s?k={product}"""
_SCREAMING_SNAKE_CASE ... | 325 |
import numpy as np
import datasets
UpperCamelCase__ ='\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof. P.... | 325 | 1 |
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say tha... | 325 |
from __future__ import annotations
import math
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
if len(__lowerCamelCase ) == 0:
... | 325 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_encodec': [
'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
'EncodecConfig',
],
'feature_extraction_encodec': ['E... | 325 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCamelCase__ ='src/di... | 325 | 1 |
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class lowerCAmelCase__( __lowercase , u... | 325 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 325 | 1 |
from __future__ import annotations
UpperCamelCase__ =10
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Tuple = 1
_SCREAMING_SNAKE_CASE : str = max(__lowerCamelCase )
while placement <= max_digit:
# declare and ... | 325 |
from timeit import timeit
def lowerCamelCase__ (__lowerCamelCase ):
if number < 0:
raise ValueError("the value of input must not be negative" )
_SCREAMING_SNAKE_CASE : str = 0
while number:
number &= number - 1
result += 1
return... | 325 | 1 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
UpperCamelCase__ =datasets.logging.get_logger(__name__)
UpperCamelCase__ ='\\n@InProceedings{moosavi2019minimum,\n author = { N... | 325 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftFormerOnnxConfig',... | 325 | 1 |
from __future__ import annotations
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[Any] = 0.00
_SCREAMING_SNAKE_CASE : List[str] = 0
for resistor in resistors:
if resistor <= 0:
_SCREAMING_SNAKE_CASE ... | 325 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
UpperCamelCase__ =np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (... | 325 | 1 |
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,
... | 325 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutp... | 325 | 1 |
# 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 b... | 325 |
from __future__ import annotations
import typing
from collections import Counter
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : typing.Counter[int] = Counter()
for base in range(1, max_perimeter + 1 ):
for perpendicular in range(__lower... | 325 | 1 |
import os
import unittest
from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeni... | 325 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# ===== initialization =====
_SCREAMING_SNAKE_CASE : List[Any] = Mock(... | 325 | 1 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...... | 325 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import ... | 325 | 1 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <... | 325 |
from maths.prime_check import is_prime
def lowerCamelCase__ (__lowerCamelCase ):
if not isinstance(__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[str] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(__l... | 325 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class lowerCAmelCase__( __lowercase ):
... | 325 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCamelCase__ (__lowerCamelCase ):
return DownloadCommand(args.model, args.cache_dir, args.force, args.trust_remote_code )
class lowerCAmelCase__( __lowercase ):
'''simp... | 325 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING... | 325 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Config... | 325 | 1 |
import math
def lowerCamelCase__ (__lowerCamelCase ):
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
... | 325 |
from math import isqrt, loga
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[Any] = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2, __lowerCamelCase, __lo... | 325 | 1 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
UpperCamelCase__ =(
'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 6S 9D TH AD',
'KS 8D 4... | 325 |
from math import factorial
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Pleas... | 325 | 1 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class lowerCAmelCase__:
'''simple docstring'''
__snake_case = 42
__snake_case = None... | 325 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class lowerCAmelCase__( __lowercase , __lowercase ... | 325 | 1 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive" )
_SCREAMING_SNAKE_CASE : List[Any] = str(bin(__lowerCamelCase ) )[2:] # remove the leading "0b"
_SCREAMING_SNAKE... | 325 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Tuple = [0 for i in range(r + 1 )]
# nc0 = 1
_SCREAMING_SNAKE_CASE : Optional[int] = 1
for i in range(1, n + 1 ):
# to compute current row from pre... | 325 | 1 |
UpperCamelCase__ ='\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
UpperCamelCase__ =[{'type': 'code', 'content': INSTALL_CONTENT}]
UpperCamelCase__ ={
... | 325 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
UpperCamelCase__ =logging.getLogger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstri... | 325 | 1 |
UpperCamelCase__ ={
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : ... | 325 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class lowerCAmelCase__( __lowercase ... | 325 | 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
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={'vocab_file': 's... | 325 |
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 logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ... | 325 | 1 |
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallback,
TrainingArgum... | 325 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase__ =logging.get_logger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
def __init__( self , *__lowerCamelCase ... | 325 | 1 |
import math
def lowerCamelCase__ (__lowerCamelCase ):
assert isinstance(__lowerCamelCase, __lowerCamelCase ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 325 |
import numpy as np
import datasets
UpperCamelCase__ ='\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof. P.... | 325 | 1 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
assert x is not None
assert y is not None
_SCREAMING_SNAKE_CASE : Tuple = len(__lowerCamelCase )
_SCREAMING_SNAKE_CASE : Union[str, Any] = len(__lowerCamelCase )
# declaring the... | 325 |
from __future__ import annotations
import math
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
if len(__lowerCamelCase ) == 0:
... | 325 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCamelCase__ ={}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
els... | 325 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCamelCase__ ='src/di... | 325 | 1 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRe... | 325 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 325 | 1 |
import doctest
from collections import deque
import numpy as np
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self ) -> None:
_SCREAMING_SNAKE_CASE : str = [2, 1, 2, -1]
_SCREAMING_SNAKE_CASE : Tuple ... | 325 |
from timeit import timeit
def lowerCamelCase__ (__lowerCamelCase ):
if number < 0:
raise ValueError("the value of input must not be negative" )
_SCREAMING_SNAKE_CASE : str = 0
while number:
number &= number - 1
result += 1
return... | 325 | 1 |
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class lowerCAmelCase__( __lowercase ):
... | 325 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftFormerOnnxConfig',... | 325 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMA... | 325 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
UpperCamelCase__ =np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (... | 325 | 1 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
UpperCamelCase__ ={
'n_samples': 64,
'horizon': 32,
'num_inference_steps': 20,
'n_guide_steps': 2, # can set to 0 for faster sampling, does not use value network
'scale_grad_by_std': T... | 325 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutp... | 325 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'roberta-base': 'https://huggingface.co/roberta-ba... | 325 |
from __future__ import annotations
import typing
from collections import Counter
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : typing.Counter[int] = Counter()
for base in range(1, max_perimeter + 1 ):
for perpendicular in range(__lower... | 325 | 1 |
from __future__ import annotations
def lowerCamelCase__ (__lowerCamelCase ):
if not nums:
return 0
_SCREAMING_SNAKE_CASE : str = nums[0]
_SCREAMING_SNAKE_CASE : str = 0
for num in nums[1:]:
_SCREAMING_SNAKE_CASE , ... | 325 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# ===== initialization =====
_SCREAMING_SNAKE_CASE : List[Any] = Mock(... | 325 | 1 |
from __future__ import annotations
from random import choice
def lowerCamelCase__ (__lowerCamelCase ):
return choice(__lowerCamelCase )
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = random_piv... | 325 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import ... | 325 | 1 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmel... | 325 |
from maths.prime_check import is_prime
def lowerCamelCase__ (__lowerCamelCase ):
if not isinstance(__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[str] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(__l... | 325 | 1 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Tuple = [0 for i in range(r + 1 )]
# nc0 = 1
_SCREAMING_SNAKE_CASE : Optional[int] = 1
for i in range(1, n + 1 ):
# to compute current row from pre... | 325 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCamelCase__ (__lowerCamelCase ):
return DownloadCommand(args.model, args.cache_dir, args.force, args.trust_remote_code )
class lowerCAmelCase__( __lowercase ):
'''simp... | 325 | 1 |
import numpy
# List of input, output pairs
UpperCamelCase__ =(
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
UpperCamelCase__ =(((515, 22, 13), 555), ((61, 35, 49), 150))
UpperCamelCase__ =[2, 4, 1, 5]
UpperCamelCase__ ... | 325 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Config... | 325 | 1 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,
get_imag... | 325 |
from math import isqrt, loga
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[Any] = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2, __lowerCamelCase, __lo... | 325 | 1 |
def lowerCamelCase__ (__lowerCamelCase ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod() | 325 |
from math import factorial
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Pleas... | 325 | 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 SequenceFe... | 325 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class lowerCAmelCase__( __lowercase , __lowercase ... | 325 | 1 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
UpperCamelCase__ =['small', 'medium', 'large']
UpperCamelCase__ ='lm_head.decoder.weight'
UpperCamelCase__ ='lm_head.weight'
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
... | 325 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Tuple = [0 for i in range(r + 1 )]
# nc0 = 1
_SCREAMING_SNAKE_CASE : Optional[int] = 1
for i in range(1, n + 1 ):
# to compute current row from pre... | 325 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=__lowercase )
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
__snake_... | 325 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
UpperCamelCase__ =logging.getLogger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstri... | 325 | 1 |
import re
from filelock import FileLock
try:
import nltk
UpperCamelCase__ =True
except (ImportError, ModuleNotFoundError):
UpperCamelCase__ =False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', quiet=True)
def lowe... | 325 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class lowerCAmelCase__( __lowercase ... | 325 | 1 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_swit... | 325 |
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 logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ... | 325 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'junnyu/roformer_chinese_small': 'https://huggingf... | 325 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase__ =logging.get_logger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
def __init__( self , *__lowerCamelCase ... | 325 | 1 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
UpperCamelCase__ =get_logger(__name__)
class lowerCAmelCase__( enum.Enum ):
'''simple docstring'''
__snake_case = 'all_checks'... | 325 |
import numpy as np
import datasets
UpperCamelCase__ ='\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof. P.... | 325 | 1 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, ... | 325 |
from __future__ import annotations
import math
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
if len(__lowerCamelCase ) == 0:
... | 325 | 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 i... | 325 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCamelCase__ ='src/di... | 325 | 1 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils impor... | 325 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 325 | 1 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
cla... | 325 |
from timeit import timeit
def lowerCamelCase__ (__lowerCamelCase ):
if number < 0:
raise ValueError("the value of input must not be negative" )
_SCREAMING_SNAKE_CASE : str = 0
while number:
number &= number - 1
result += 1
return... | 325 | 1 |
from __future__ import annotations
import math
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
if len(__lowerCamelCase ) == 0:
... | 325 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftFormerOnnxConfig',... | 325 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ ={'processing_layoutxlm': ['LayoutXLMProcessor']}
try:
if ... | 325 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
UpperCamelCase__ =np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (... | 325 | 1 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__( unittest.TestCase ):
... | 325 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutp... | 325 | 1 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
def __init__( self , __lowerCamelCase ... | 325 |
from __future__ import annotations
import typing
from collections import Counter
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : typing.Counter[int] = Counter()
for base in range(1, max_perimeter + 1 ):
for perpendicular in range(__lower... | 325 | 1 |
from numpy import exp, pi, sqrt
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase = 0.0, __lowerCamelCase = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod() | 325 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# ===== initialization =====
_SCREAMING_SNAKE_CASE : List[Any] = Mock(... | 325 | 1 |
from collections.abc import Iterable
from typing import Any
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self , __lowerCamelCase = None ) -> Union[str, Any]:
_SCREAMING_SNAKE_CASE : List[Any] = value
_SC... | 325 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import ... | 325 | 1 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Fla... | 325 |
from maths.prime_check import is_prime
def lowerCamelCase__ (__lowerCamelCase ):
if not isinstance(__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[str] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(__l... | 325 | 1 |
from math import isqrt
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2, __lowerCamelCase, __lo... | 325 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCamelCase__ (__lowerCamelCase ):
return DownloadCommand(args.model, args.cache_dir, args.force, args.trust_remote_code )
class lowerCAmelCase__( __lowercase ):
'''simp... | 325 | 1 |
from collections import defaultdict
from math import gcd
def lowerCamelCase__ (__lowerCamelCase = 1500000 ):
_SCREAMING_SNAKE_CASE : defaultdict = defaultdict(__lowerCamelCase )
_SCREAMING_SNAKE_CASE : Any = 2
while 2 * euclid_m * (euclid_m + 1) <... | 325 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Config... | 325 | 1 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
__snake_case = 'EncodecFeatureExtractor'
__snake_case = ... | 325 |
from math import isqrt, loga
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[Any] = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2, __lowerCamelCase, __lo... | 325 | 1 |
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self ) -> Union[str, Any]:
_SCREAMING_SNAKE_CASE : int = ""
_SCREAMING_SNAKE_CASE : Dict = ""
_SCREAMING_SNAKE_CASE : Optional[int] ... | 325 |
from math import factorial
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Pleas... | 325 | 1 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCAmelCase__:
'''simple docstring'''
@property
def ... | 325 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class lowerCAmelCase__( __lowercase , __lowercase ... | 325 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_roberta': ['ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Robe... | 325 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Tuple = [0 for i in range(r + 1 )]
# nc0 = 1
_SCREAMING_SNAKE_CASE : Optional[int] = 1
for i in range(1, n + 1 ):
# to compute current row from pre... | 325 | 1 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
... | 325 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
UpperCamelCase__ =logging.getLogger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstri... | 325 | 1 |
from __future__ import annotations
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
if nth_term == "":
return [""]
_SCREAMING_SNAKE_CASE : Optional[int] = int(__lowerCamelCase )
_SCREAMING_SNAKE_CASE : List[str] = int(__low... | 325 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class lowerCAmelCase__( __lowercase ... | 325 | 1 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ =OrderedDict(
[
# ... | 325 |
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 logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ... | 325 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_funnel': ['FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FunnelConfig'],
'convert_... | 325 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase__ =logging.get_logger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
def __init__( self , *__lowerCamelCase ... | 325 | 1 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
if index == r:
for j in range(__lowerCamelCase ):
print(data[j], end=" " )
print(" " )
return
#... | 325 |
import numpy as np
import datasets
UpperCamelCase__ ='\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof. P.... | 325 | 1 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCamelCase__ ='src/di... | 325 |
from __future__ import annotations
import math
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
if len(__lowerCamelCase ) == 0:
... | 325 | 1 |
from math import factorial
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Pleas... | 325 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCamelCase__ ='src/di... | 325 | 1 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
UpperCamelCase__ =logging.getLogger(__name__)
@dataclass
class lowerCAmelCase__( __lowercase ):
'''simp... | 325 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 325 | 1 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : int = len(__lowerCamelCase )
_SCREAMING_SNAKE_CASE : int = len(__lowerCamelCase )
_SCREAMING_SNAKE_CASE : int = (
first_str_length if first... | 325 |
from timeit import timeit
def lowerCamelCase__ (__lowerCamelCase ):
if number < 0:
raise ValueError("the value of input must not be negative" )
_SCREAMING_SNAKE_CASE : str = 0
while number:
number &= number - 1
result += 1
return... | 325 | 1 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCamelCase__ (__lowerCamelCase ):
return DownloadCommand(args.model, args.cache_dir, args.force, args.trust_remote_code )
class lowerCAmelCase__( __lowercase ):
'''simp... | 325 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftFormerOnnxConfig',... | 325 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
),
}
cl... | 325 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
UpperCamelCase__ =np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (... | 325 | 1 |
import numpy as np
import datasets
UpperCamelCase__ ='\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof. P.... | 325 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutp... | 325 | 1 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
UpperCamelCase__ =logging.get_logger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
def __init__( self , *__lowerCamelCase , **__lo... | 325 |
from __future__ import annotations
import typing
from collections import Counter
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : typing.Counter[int] = Counter()
for base in range(1, max_perimeter + 1 ):
for perpendicular in range(__lower... | 325 | 1 |
import requests
from bsa import BeautifulSoup
def lowerCamelCase__ (__lowerCamelCase = "https://www.worldometers.info/coronavirus" ):
_SCREAMING_SNAKE_CASE : List[Any] = BeautifulSoup(requests.get(__lowerCamelCase ).text, "html.parser" )
_SCREAMING_SNAKE_CASE : ... | 325 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# ===== initialization =====
_SCREAMING_SNAKE_CASE : List[Any] = Mock(... | 325 | 1 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase=False ):
if isinstance(__lowerCamelCase, __lowerCamelCase ) and isinstance(__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : str = len(set_a.intersection(__lowerCamelCas... | 325 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import ... | 325 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_mobilebert': [
'MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mobi... | 325 |
from maths.prime_check import is_prime
def lowerCamelCase__ (__lowerCamelCase ):
if not isinstance(__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[str] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(__l... | 325 | 1 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
f... | 325 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCamelCase__ (__lowerCamelCase ):
return DownloadCommand(args.model, args.cache_dir, args.force, args.trust_remote_code )
class lowerCAmelCase__( __lowercase ):
'''simp... | 325 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_... | 325 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Config... | 325 | 1 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import... | 325 |
from math import isqrt, loga
def lowerCamelCase__ (__lowerCamelCase ):
_SCREAMING_SNAKE_CASE : List[Any] = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2, __lowerCamelCase, __lo... | 325 | 1 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
W... | 325 |
from math import factorial
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Pleas... | 325 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'edbeeching/decision-transformer-gym-hopper-medium': (
'https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/... | 325 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class lowerCAmelCase__( __lowercase , __lowercase ... | 325 | 1 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...ima... | 325 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Tuple = [0 for i in range(r + 1 )]
# nc0 = 1
_SCREAMING_SNAKE_CASE : Optional[int] = 1
for i in range(1, n + 1 ):
# to compute current row from pre... | 325 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__lowercase )
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
__snake_case = field(d... | 325 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
UpperCamelCase__ =logging.getLogger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstri... | 325 | 1 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutp... | 325 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ={
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class lowerCAmelCase__( __lowercase ... | 325 | 1 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 325 |
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 logging
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ... | 325 | 1 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"kwargs, expected", [
({"num_shards": 0, "max_num_jobs": 1}, []),
({"num_shards": 10, "max_num_jobs": 1}, [range(10 )]),
({"num_... | 325 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase__ =logging.get_logger(__name__)
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
def __init__( self , *__lowerCamelCase ... | 325 | 1 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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, prep... | 325 |
import numpy as np
import datasets
UpperCamelCase__ ='\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt was introduced by Prof. P.... | 325 | 1 |
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase = 10**-10 ):
_SCREAMING_SNAKE_CASE : int = a
while True:
_... | 325 |
from __future__ import annotations
import math
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase, __lowerCamelCase ):
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
if len(__lowerCamelCase ) == 0:
... | 325 | 1 |
from math import pi
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10)) | 325 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCamelCase__ ='src/di... | 325 | 1 |
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class lowerCAmelCase__( __lowercase ):
'''simple docstring'''
def UpperCamelCase_ ( self , __lowerCamelCase ) -> List[Any]:
wit... | 325 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 325 | 1 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase=(), __lowerCamelCase=None, __lowerCamelCase="no", __l... | 325 |
from timeit import timeit
def lowerCamelCase__ (__lowerCamelCase ):
if number < 0:
raise ValueError("the value of input must not be negative" )
_SCREAMING_SNAKE_CASE : str = 0
while number:
number &= number - 1
result += 1
return... | 325 | 1 |
from torch import nn
class lowerCAmelCase__( nn.Module ):
'''simple docstring'''
def __init__( self , __lowerCamelCase , __lowerCamelCase ) -> Tuple:
super().__init__()
_SCREAMING_SNAKE_CASE : List[Any] = cla... | 325 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftFormerOnnxConfig',... | 325 | 1 |
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