code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
UpperCamelCase__: Any = datasets.logging.get_logger(__name__)
UpperCamelCase__: Union[str, Any] = "\\n@inproceedings{bleur... | 127 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch... | 127 | 1 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTe... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str ) -> int:
if not head:
return True
# split the list to two parts
UpperCAmelCase , UpperCAmelCase : str = head.next, head
while fast and fast.next:
... | 127 | 1 |
'''simple docstring'''
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.genera... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int , _lowerCAmelCase : Dict , _lowerCAmelCase : List[str] , _lowerCAmelCase : str , _lowerCAmelCase : Optional[int] , _lowerCAmelCase : List[Any] ) -> Union[str, Any]:
if index == r:
... | 127 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
UpperCamelCase__: Optional[int] = logging.get_logger(__name__)
def snake_case_ ( _lowerCAmelCase : Union[tf.Tensor, np.ndar... | 127 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
UpperCamelCase__: Any = datasets.logging.get_logger(__name__)
UpperCamelCase__: Union[str, Any] = "\\n@inproceedings{bleur... | 127 | 1 |
'''simple docstring'''
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCr... | 127 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class SCREAMING_SNAKE_CASE( unittest.TestCase ):
"""simple docstring"""
def A ( self : Tuple ) -> Optional[Any]:... | 127 | 1 |
'''simple docstring'''
import socket
def snake_case_ ( ) -> Optional[Any]:
UpperCAmelCase : str = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
UpperCAmelCase : Union[str, Any] = socket.gethostname()
UpperCAmelCase... | 127 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__: str = logging.get_lo... | 127 | 1 |
'''simple docstring'''
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
fr... | 127 |
'''simple docstring'''
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class SCREAMING_SNAKE_CASE:
"""simple docstring"""
def __init__( self : List[str] , __snake_case : Any ) -> Lis... | 127 | 1 |
'''simple docstring'''
import sys
UpperCamelCase__: List[str] = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"125406987471585238630507156932909632... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int ) -> list:
UpperCAmelCase : Union[str, Any] = int(_lowerCAmelCase )
if n_element < 1:
UpperCAmelCase : int = ValueError('''a should be a positive num... | 127 | 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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
Chann... | 127 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCamelCase__: str = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchm... | 127 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCamelCase__: List[Any] = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM ... | 127 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__: Tuple = 1.60_21E-19 # units = C
def snake_case_ ( _lowerCAmelCase : float , _lowerCAmelCase : float , _lowerCAmelCase : float , ) -> tuple[str, float]:
if (conductivity,... | 127 | 1 |
'''simple docstring'''
# 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.or... | 127 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transfor... | 127 | 1 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( _lowerCAmelCase : list[int] ) -> list[int]:
if len(_lowerCAmelCase ) == 0:
return array
UpperCAmelCase , UpperCAmelCase : Any = min(_lowerCA... | 127 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class SCREAMING_SNAKE_CASE( nn.Module ):
"""simple docstring""... | 127 | 1 |
'''simple docstring'''
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
UpperCamelCase__: int = logging.get_logger(__name__) # pylint: disable=... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : Any , _lowerCAmelCase : Optional[Any] , _lowerCAmelCase : Any , _lowerCAmelCase : Union[str, Any] ) -> Dict:
# Return True if there is node that has not iterated.
UpperCAmelCase : List[Any... | 127 | 1 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...te... | 127 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: int = logging.get_logger(__name__)
# TODO Update this
UpperCamelCase__: Any ... | 127 | 1 |
'''simple docstring'''
from statistics import mean, stdev
def snake_case_ ( _lowerCAmelCase : list , _lowerCAmelCase : int = 3 ) -> list:
UpperCAmelCase : Optional[Any] = min(_lowerCAmelCase )
UpperCAmelCase : Union[str, Any] ... | 127 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: List[Any] = logging.get_logger(__name__)
UpperCamelCase__: str = {
"unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmer... | 127 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class SCREAMING_SNAKE_CASE:
"""simple docstring"""
lowerCamelCase__ = 42
lowerCamelCase__ = ... | 127 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def snake_case_ ( _lowerCAmelCase : float ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(_lowerCAmelCase , 0 , _lo... | 127 | 1 |
'''simple docstring'''
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
UpperCamelCase__: Optional[int] = {
"linear": PIL.Image.Re... | 127 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transforme... | 127 | 1 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransfor... | 127 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ..... | 127 | 1 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ... | 127 |
'''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format... | 127 | 1 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str , _lowerCAmelCase : str ) -> int:
if len(_lowerCAmelCase ) != len(_lowerCAmelCase ):
raise ValueError('''String lengths must match!''' )
UpperCAmelCase : List[str] ... | 127 | 1 |
'''simple docstring'''
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
UpperCamelCase__:... | 127 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( _lowerCAmelCase : list[int] ) -> int:
if not nums:
return 0
UpperCAmelCase : Tuple = nums[0]
UpperCAmelCase : List[str] = 0
... | 127 | 1 |
'''simple docstring'''
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase__: Optional[int] ... | 127 |
'''simple docstring'''
import re
def snake_case_ ( _lowerCAmelCase : str ) -> str:
if len(re.findall('''[ATCG]''' , _lowerCAmelCase ) ) != len(_lowerCAmelCase ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.make... | 127 | 1 |
'''simple docstring'''
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
... | 127 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch... | 127 | 1 |
'''simple docstring'''
# 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 bel... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str ) -> int:
if not head:
return True
# split the list to two parts
UpperCAmelCase , UpperCAmelCase : str = head.next, head
while fast and fast.next:
... | 127 | 1 |
'''simple docstring'''
import re
def snake_case_ ( _lowerCAmelCase : str ) -> str:
if len(re.findall('''[ATCG]''' , _lowerCAmelCase ) ) != len(_lowerCAmelCase ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.make... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int , _lowerCAmelCase : Dict , _lowerCAmelCase : List[str] , _lowerCAmelCase : str , _lowerCAmelCase : Optional[int] , _lowerCAmelCase : List[Any] ) -> Union[str, Any]:
if index == r:
... | 127 | 1 |
'''simple docstring'''
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
UpperCamelCase__: Optional[int] = 200
# Number of elements selected in every generation of evolution. The selection t... | 127 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
UpperCamelCase__: Any = datasets.logging.get_logger(__name__)
UpperCamelCase__: Union[str, Any] = "\\n@inproceedings{bleur... | 127 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 127 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class SCREAMING_SNAKE_CASE( unittest.TestCase ):
"""simple docstring"""
def A ( self : Tuple ) -> Optional[Any]:... | 127 | 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__: int = "sched... | 127 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__: str = logging.get_lo... | 127 | 1 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: int = logging.get_logger(__name__)
# TODO Update this
UpperCamelCase__: Any ... | 127 |
'''simple docstring'''
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class SCREAMING_SNAKE_CASE:
"""simple docstring"""
def __init__( self : List[str] , __snake_case : Any ) -> Lis... | 127 | 1 |
'''simple docstring'''
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_con... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int ) -> list:
UpperCAmelCase : Union[str, Any] = int(_lowerCAmelCase )
if n_element < 1:
UpperCAmelCase : int = ValueError('''a should be a positive num... | 127 | 1 |
'''simple docstring'''
UpperCamelCase__: int = 8.314462 # Unit - J mol-1 K-1
def snake_case_ ( _lowerCAmelCase : float , _lowerCAmelCase : float , _lowerCAmelCase : float ) -> float:
if moles < 0 or kelvin < 0 or volume < 0:
raise ... | 127 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCamelCase__: str = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchm... | 127 | 1 |
'''simple docstring'''
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... | 127 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__: Tuple = 1.60_21E-19 # units = C
def snake_case_ ( _lowerCAmelCase : float , _lowerCAmelCase : float , _lowerCAmelCase : float , ) -> tuple[str, float]:
if (conductivity,... | 127 | 1 |
'''simple docstring'''
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
a... | 127 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transfor... | 127 | 1 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
UpperCamelCase__: Dict = TypeVar("KT")
UpperCamelCase__: int = TypeVar("VT")
class SCREAMING_SNAKE_CASE( Generic[KT, VT] ):
... | 127 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class SCREAMING_SNAKE_CASE( nn.Module ):
"""simple docstring""... | 127 | 1 |
'''simple docstring'''
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Option... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : Any , _lowerCAmelCase : Optional[Any] , _lowerCAmelCase : Any , _lowerCAmelCase : Union[str, Any] ) -> Dict:
# Return True if there is node that has not iterated.
UpperCAmelCase : List[Any... | 127 | 1 |
'''simple docstring'''
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, Test... | 127 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: int = logging.get_logger(__name__)
# TODO Update this
UpperCamelCase__: Any ... | 127 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__: List[Any] = {
"configuration_convbert": ... | 127 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: List[Any] = logging.get_logger(__name__)
UpperCamelCase__: str = {
"unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmer... | 127 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 127 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def snake_case_ ( _lowerCAmelCase : float ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(_lowerCAmelCase , 0 , _lo... | 127 | 1 |
'''simple docstring'''
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_avail... | 127 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transforme... | 127 | 1 |
'''simple docstring'''
class SCREAMING_SNAKE_CASE:
"""simple docstring"""
def __init__( self : List[Any] , __snake_case : int ) -> Dict:
UpperCAmelCase : List[Any] = n
UpperCAmelCase : Di... | 127 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ..... | 127 | 1 |
'''simple docstring'''
from graphs.minimum_spanning_tree_kruskal import kruskal
def snake_case_ ( ) -> Union[str, Any]:
UpperCAmelCase : Tuple = 9
UpperCAmelCase : Union[str, Any] = [
[0, 1, 4],
[0, 7, 8],
... | 127 |
'''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format... | 127 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__: List[str] = logging.get_l... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str , _lowerCAmelCase : str ) -> int:
if len(_lowerCAmelCase ) != len(_lowerCAmelCase ):
raise ValueError('''String lengths must match!''' )
UpperCAmelCase : List[str] ... | 127 | 1 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str ) -> list:
UpperCAmelCase : str = [0] * len(_lowerCAmelCase )
for i in range(1 , len(_lowerCAmelCase ) ):
# use last results for better performance - dynamic p... | 127 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( _lowerCAmelCase : list[int] ) -> int:
if not nums:
return 0
UpperCAmelCase : Tuple = nums[0]
UpperCAmelCase : List[str] = 0
... | 127 | 1 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int = 50 ) -> int:
UpperCAmelCase : Dict = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
... | 127 |
'''simple docstring'''
import re
def snake_case_ ( _lowerCAmelCase : str ) -> str:
if len(re.findall('''[ATCG]''' , _lowerCAmelCase ) ) != len(_lowerCAmelCase ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.make... | 127 | 1 |
'''simple docstring'''
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
UpperCamelCase__: Optional[int] = Path(__file__).resolve().parents[3] / "src"
sys.path.insert(1, str(gi... | 127 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch... | 127 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: int = logging.get_logger(__name__)
UpperCamelCase__: Any = {
"sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/r... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str ) -> int:
if not head:
return True
# split the list to two parts
UpperCAmelCase , UpperCAmelCase : str = head.next, head
while fast and fast.next:
... | 127 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int , _lowerCAmelCase : Dict , _lowerCAmelCase : List[str] , _lowerCAmelCase : str , _lowerCAmelCase : Optional[int] , _lowerCAmelCase : List[Any] ) -> Union[str, Any]:
if index == r:
... | 127 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax impor... | 127 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
UpperCamelCase__: Any = datasets.logging.get_logger(__name__)
UpperCamelCase__: Union[str, Any] = "\\n@inproceedings{bleur... | 127 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, 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_a... | 127 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class SCREAMING_SNAKE_CASE( unittest.TestCase ):
"""simple docstring"""
def A ( self : Tuple ) -> Optional[Any]:... | 127 | 1 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int ) -> int:
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ):
raise TypeError('''only integers accepted as input''' )
else:
UpperCAmelCase : Optional[Any] ... | 127 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__: str = logging.get_lo... | 127 | 1 |
'''simple docstring'''
from manim import *
class SCREAMING_SNAKE_CASE( A__ ):
"""simple docstring"""
def A ( self : List[str] ) -> Dict:
UpperCAmelCase : Union[str, Any] = Rectangle(height=0.5 ,... | 127 |
'''simple docstring'''
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class SCREAMING_SNAKE_CASE:
"""simple docstring"""
def __init__( self : List[str] , __snake_case : Any ) -> Lis... | 127 | 1 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( _lowerCAmelCase : list[float] , _lowerCAmelCase : List[Any] ) -> Optional[Any]:
print(f"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(_lowerCAmelCase ... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int ) -> list:
UpperCAmelCase : Union[str, Any] = int(_lowerCAmelCase )
if n_element < 1:
UpperCAmelCase : int = ValueError('''a should be a positive num... | 127 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_confi... | 127 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCamelCase__: str = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchm... | 127 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ( _lowerCAmelCase : Tuple , _lowerCAmel... | 127 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__: Tuple = 1.60_21E-19 # units = C
def snake_case_ ( _lowerCAmelCase : float , _lowerCAmelCase : float , _lowerCAmelCase : float , ) -> tuple[str, float]:
if (conductivity,... | 127 | 1 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
cl... | 127 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transfor... | 127 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__: L... | 127 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class SCREAMING_SNAKE_CASE( nn.Module ):
"""simple docstring""... | 127 | 1 |
'''simple docstring'''
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
UpperCamelCase__: int = TypeVar("T")
def snake_case_ ( _lowerCAmelCase : int ) -> int:
return (position - 1) // 2
def snak... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : Any , _lowerCAmelCase : Optional[Any] , _lowerCAmelCase : Any , _lowerCAmelCase : Union[str, Any] ) -> Dict:
# Return True if there is node that has not iterated.
UpperCAmelCase : List[Any... | 127 | 1 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : Any , _lowerCAmelCase : Optional[Any] , _lowerCAmelCase : Any , _lowerCAmelCase : Union[str, Any] ) -> Dict:
# Return True if there is node that has not iterated.
UpperCAmelCase : List[Any... | 127 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: int = logging.get_logger(__name__)
# TODO Update this
UpperCamelCase__: Any ... | 127 | 1 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ..... | 127 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: List[Any] = logging.get_logger(__name__)
UpperCamelCase__: str = {
"unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmer... | 127 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCamelCase__: str = ... | 127 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def snake_case_ ( _lowerCAmelCase : float ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(_lowerCAmelCase , 0 , _lo... | 127 | 1 |
'''simple docstring'''
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gp... | 127 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transforme... | 127 | 1 |
'''simple docstring'''
# 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.or... | 127 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ..... | 127 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig... | 127 |
'''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format... | 127 | 1 |
'''simple docstring'''
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 ImageProcess... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str , _lowerCAmelCase : str ) -> int:
if len(_lowerCAmelCase ) != len(_lowerCAmelCase ):
raise ValueError('''String lengths must match!''' )
UpperCAmelCase : List[str] ... | 127 | 1 |
'''simple docstring'''
from math import isqrt
def snake_case_ ( _lowerCAmelCase : int ) -> list[int]:
UpperCAmelCase : str = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
... | 127 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( _lowerCAmelCase : list[int] ) -> int:
if not nums:
return 0
UpperCAmelCase : Tuple = nums[0]
UpperCAmelCase : List[str] = 0
... | 127 | 1 |
'''simple docstring'''
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# p... | 127 |
'''simple docstring'''
import re
def snake_case_ ( _lowerCAmelCase : str ) -> str:
if len(re.findall('''[ATCG]''' , _lowerCAmelCase ) ) != len(_lowerCAmelCase ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.make... | 127 | 1 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str ) -> int:
if not head:
return True
# split the list to two parts
UpperCAmelCase , UpperCAmelCase : str = head.next, head
while fast and fast.next:
... | 127 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch... | 127 | 1 |
'''simple docstring'''
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDa... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str ) -> int:
if not head:
return True
# split the list to two parts
UpperCAmelCase , UpperCAmelCase : str = head.next, head
while fast and fast.next:
... | 127 | 1 |
'''simple docstring'''
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class SCREAMING_SNAKE_CASE:
"""simple docstring"""
def __init__( self : List[str] , __snake_case : Any ) -> Lis... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int , _lowerCAmelCase : Dict , _lowerCAmelCase : List[str] , _lowerCAmelCase : str , _lowerCAmelCase : Optional[int] , _lowerCAmelCase : List[Any] ) -> Union[str, Any]:
if index == r:
... | 127 | 1 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class SCREAMING_SNAKE_CASE( nn.Module ):
"""simple docstring""... | 127 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
UpperCamelCase__: Any = datasets.logging.get_logger(__name__)
UpperCamelCase__: Union[str, Any] = "\\n@inproceedings{bleur... | 127 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase__: Dict = {
"configuration_vision_text_dual_encod... | 127 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class SCREAMING_SNAKE_CASE( unittest.TestCase ):
"""simple docstring"""
def A ( self : Tuple ) -> Optional[Any]:... | 127 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE... | 127 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__: str = logging.get_lo... | 127 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE:
"""simple docstring"""
def __init__( self : int , __snake_case : int ) -> None:
UpperCAmelCase : Lis... | 127 |
'''simple docstring'''
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class SCREAMING_SNAKE_CASE:
"""simple docstring"""
def __init__( self : List[str] , __snake_case : Any ) -> Lis... | 127 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
UpperCamelCase__: List[str] = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE( A__ ):
"""simple docstring"""
... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int ) -> list:
UpperCAmelCase : Union[str, Any] = int(_lowerCAmelCase )
if n_element < 1:
UpperCAmelCase : int = ValueError('''a should be a positive num... | 127 | 1 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def snake_case_ ( _lowerCAmelCase : Any="ro" , _lowerCAmelCase : Tuple="en" , _lowerCAmelCase : Union[str, Any]="wmt16" , _lowerCAmelCase : Tuple=None ) -> None:
try:
... | 127 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCamelCase__: str = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchm... | 127 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: Dict = logging.get_logger(__name__)
UpperCamelCase__: List[str] = {
"microsoft/unispeech-sat-base-... | 127 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__: Tuple = 1.60_21E-19 # units = C
def snake_case_ ( _lowerCAmelCase : float , _lowerCAmelCase : float , _lowerCAmelCase : float , ) -> tuple[str, float]:
if (conductivity,... | 127 | 1 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class SCREAMING_SNAKE_CASE( unittest.TestCase ):
"""simple docstring"""
def A ( self : Tuple ) -> Optional[Any]:... | 127 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transfor... | 127 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__: int = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
... | 127 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class SCREAMING_SNAKE_CASE( nn.Module ):
"""simple docstring""... | 127 | 1 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : Any , _lowerCAmelCase : Optional[Any] , _lowerCAmelCase : Any , _lowerCAmelCase : Union[str, Any] ) -> Dict:
# Return True if there is node that has not iterated.
UpperCAmelCase : List[Any... | 127 | 1 |
'''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_... | 127 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: int = logging.get_logger(__name__)
# TODO Update this
UpperCamelCase__: Any ... | 127 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE( metaclass=A__ ):
"""simple docstring"""
lowerCamelCase__ = ["""sentencepiece"""]
def __init__( self : Any , *... | 127 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: List[Any] = logging.get_logger(__name__)
UpperCamelCase__: str = {
"unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmer... | 127 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...o... | 127 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def snake_case_ ( _lowerCAmelCase : float ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(_lowerCAmelCase , 0 , _lo... | 127 | 1 |
'''simple docstring'''
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noq... | 127 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transforme... | 127 | 1 |
'''simple docstring'''
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'''... | 127 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ..... | 127 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def snake_case_ ( _lowerCAmelCase : list ) -> int:
if not postfix_notation:
return 0
UpperCAmelCase : Tuple = {'''+''', '''-''', '''*''', '''/'... | 127 |
'''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format... | 127 | 1 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int = 1000000 ) -> int:
UpperCAmelCase : Any = set(range(3 , _lowerCAmelCase , 2 ) )
primes.add(2 )
for p in range(3 , _lowerCAmelCase , 2 ):
if p not ... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str , _lowerCAmelCase : str ) -> int:
if len(_lowerCAmelCase ) != len(_lowerCAmelCase ):
raise ValueError('''String lengths must match!''' )
UpperCAmelCase : List[str] ... | 127 | 1 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__: str = logging.get_lo... | 127 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( _lowerCAmelCase : list[int] ) -> int:
if not nums:
return 0
UpperCAmelCase : Tuple = nums[0]
UpperCAmelCase : List[str] = 0
... | 127 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
UpperCamelCase__: Optional[Any] = TypeVar("T")
class SCREAMING_SNAKE_CASE( Generic[T] ):
"""simple docstring"... | 127 |
'''simple docstring'''
import re
def snake_case_ ( _lowerCAmelCase : str ) -> str:
if len(re.findall('''[ATCG]''' , _lowerCAmelCase ) ) != len(_lowerCAmelCase ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.make... | 127 | 1 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing... | 127 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch... | 127 | 1 |
'''simple docstring'''
import numpy
# List of input, output pairs
UpperCamelCase__: List[Any] = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
UpperCamelCase__: Tuple = (((515, 22, 13), 555), (... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str ) -> int:
if not head:
return True
# split the list to two parts
UpperCAmelCase , UpperCAmelCase : str = head.next, head
while fast and fast.next:
... | 127 | 1 |
'''simple docstring'''
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def snake_case_ ( _lowerCAmelCase : Opt... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int , _lowerCAmelCase : Dict , _lowerCAmelCase : List[str] , _lowerCAmelCase : str , _lowerCAmelCase : Optional[int] , _lowerCAmelCase : List[Any] ) -> Union[str, Any]:
if index == r:
... | 127 | 1 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : str , _lowerCAmelCase : str ) -> int:
if len(_lowerCAmelCase ) != len(_lowerCAmelCase ):
raise ValueError('''String lengths must match!''' )
UpperCAmelCase : List[str] ... | 127 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
UpperCamelCase__: Any = datasets.logging.get_logger(__name__)
UpperCamelCase__: Union[str, Any] = "\\n@inproceedings{bleur... | 127 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__: Dict = {
"configuration_llama... | 127 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class SCREAMING_SNAKE_CASE( unittest.TestCase ):
"""simple docstring"""
def A ( self : Tuple ) -> Optional[Any]:... | 127 | 1 |
'''simple docstring'''
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def... | 127 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__: str = logging.get_lo... | 127 | 1 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_... | 127 |
'''simple docstring'''
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class SCREAMING_SNAKE_CASE:
"""simple docstring"""
def __init__( self : List[str] , __snake_case : Any ) -> Lis... | 127 | 1 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int ) -> list:
UpperCAmelCase : Union[str, Any] = int(_lowerCAmelCase )
if n_element < 1:
UpperCAmelCase : int = ValueError('''a should be a positive num... | 127 |
'''simple docstring'''
def snake_case_ ( _lowerCAmelCase : int ) -> list:
UpperCAmelCase : Union[str, Any] = int(_lowerCAmelCase )
if n_element < 1:
UpperCAmelCase : int = ValueError('''a should be a positive num... | 127 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMi... | 127 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCamelCase__: str = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchm... | 127 | 1 |
'''simple docstring'''
from statistics import mean
import numpy as np
def snake_case_ ( _lowerCAmelCase : list , _lowerCAmelCase : list , _lowerCAmelCase : list , _lowerCAmelCase : int ) -> list:
UpperCAmelCase : str = 0
# Num... | 127 |
'''simple docstring'''
from __future__ import annotations
UpperCamelCase__: Tuple = 1.60_21E-19 # units = C
def snake_case_ ( _lowerCAmelCase : float , _lowerCAmelCase : float , _lowerCAmelCase : float , ) -> tuple[str, float]:
if (conductivity,... | 127 | 1 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torcha... | 127 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transfor... | 127 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def snake_case_ ( _lowerCAmelCase : Sequence[float] , _lowerCAmelCase : bool = False ) -> float:
if not arr:
return 0
UpperCAmelCase : str = 0 if allow_empty_suba... | 127 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class SCREAMING_SNAKE_CASE( nn.Module ):
"""simple docstring""... | 127 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.