code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_A : str = get_tests_dir("""fixtures/spiece.model""... | 100 |
'''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 | 0 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_r... | 101 |
'''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 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__magic_name__ : Union[str, Any] = {"""configuration_vit_mae""": ["""V... | 102 |
'''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 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCAmelCase ( __SCREAMING_SNAKE_CASE ):
def __init__( self : List[str] ):
"""simple docstring"""
# test for the above condition
self.te... | 103 |
'''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 | 0 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(UpperCAmelCase_, UpperCAmelCase_ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise Value... | 104 |
'''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 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : Union[str, Any] = {'''configuration_sew''': ['''SEW_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWConfig''']}
try:
if not is_torch_available():
raise... | 105 |
'''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 | 0 |
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
__snake_case :Dict =logging.get_logger(__name__)
__snake_case :Any ={'vo... | 106 |
'''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 | 0 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_UpperCAmelCase : List[Any] = [
'''good first issue''',
'''feature request''',
'''wip''',
]
def _SCREAMING_SNAKE_CASE ( ):
_A = Github(os.environ['GITHUB_TOKEN'... | 107 |
'''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 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor,... | 108 |
'''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 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_t... | 109 |
'''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 | 0 |
from PIL import Image
def UpperCamelCase ( _a ) -> Image:
'''simple docstring'''
lowercase_ :Optional[int] = image.size
lowercase_ :int = 0
lowercase_ :Dict = image.load()
for i in range(... | 257 |
'''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 | 0 |
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __lowerCamelCase (UpperCAmelCase_... | 403 |
'''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 | 0 |
"""simple docstring"""
from statistics import mean, stdev
def __UpperCAmelCase ( __lowerCamelCase , __lowerCamelCase = 3 ) -> list:
lowercase__ : Optional[Any] = min(_lowerCAmelCase )
lowercase__ : Union[str, Any] = max... | 560 |
'''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 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase : Dict = {
"configuration_vision_text_dual_encoder": ["VisionTextDualEncoderConfig"],
"processing_... | 297 |
'''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 | 0 |
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
A_ : List[Any] = {
"Acehnese Arabic": "ace_Arab",
"Acehnese Latin": "ace_Latn",
"Mesopotamian Arabic": "acm_Arab",
"Ta'izzi-Adeni Arabic": "acq_Arab",
"Tuni... | 57 |
'''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 | 0 |
"""simple docstring"""
import json
import sys
def lowerCamelCase ( _snake_case ,_snake_case ):
with open(_lowerCAmelCase ,encoding='utf-8' ) as f:
UpperCAmelCase__ : int = json.load(_lowerCAmelCase )
UpperCAmelCase__ : List[str] = ['''<detail... | 110 |
'''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 | 0 |
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, TableTransformerConfig, TableTransformerForOb... | 592 |
'''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 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : str = logging.get_logg... | 262 |
'''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 | 0 |
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
_lowerCamelCase = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for I... | 6 |
'''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 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
a = TypeVar('''KT''')
a = TypeVar('''VT''')
class lowercase_ ( Generic[KT, VT] ):
'''simple docstring'''
def __init__( self : int... | 7 |
'''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 | 0 |
def lowercase__ ( _UpperCamelCase = 2_00) -> int:
"""simple docstring"""
UpperCamelCase = [1, 2, 5, 10, 20, 50, 1_00, 2_00]
UpperCamelCase = [0] * (pence + 1)
UpperCamelCase = 1 # base case: 1 way to make 0 pence
for coin ... | 280 |
'''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 | 0 |
from __future__ import annotations
from typing import Any
def UpperCamelCase ( _a ) -> int:
'''simple docstring'''
if not postfix_notation:
return 0
lowercase_ :Tuple = {'''+''', '''-''', '''*''', '''/'''}
lowercase... | 257 |
'''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 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase ( A__ ):
lowercase__ : List[str] = ["""image_processor""", """tokenizer"""]
lowercase__ : Optional[Any] = """Vi... | 403 |
'''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 | 0 |
"""simple docstring"""
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
... | 560 |
'''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 | 0 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import Backbone... | 297 |
'''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 | 0 |
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# 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
A_ : Optional[Any] = "."
# ... | 57 |
'''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 | 0 |
"""simple docstring"""
def lowerCamelCase ( _snake_case ):
UpperCAmelCase__ : Union[str, Any] = int(_lowerCAmelCase )
if n_element < 1:
UpperCAmelCase__ : int = ValueError('a should be a positive number' )
raise my_error
UpperCAmelCase_... | 110 |
'''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 | 0 |
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Co... | 592 |
'''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 | 0 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dic... | 262 |
'''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 | 0 |
from __future__ import annotations
from typing import Any
class UpperCamelCase_ :
def __init__( self :int , __A :int ) -> None:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = num_of_nodes
SCREAMING_SNAKE_CASE__ = []
... | 6 |
'''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 | 0 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data... | 7 |
'''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 | 0 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__magic_name__ : Optional[int] = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to wo... | 280 |
'''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 | 0 |
import numpy
# List of input, output pairs
SCREAMING_SNAKE_CASE : List[Any] = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
SCREAMING_SNAKE_CASE : Tuple = (((515, 22, 13), 555), ((61, 35, 49), 150))
S... | 257 |
'''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 | 0 |
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import... | 403 |
'''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 | 0 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import Squad... | 560 |
'''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 | 0 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Con... | 297 |
'''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 | 0 |
import argparse
import os
import re
A_ : Optional[Any] = "src/transformers"
# Pattern that looks at the indentation in a line.
A_ : Union[str, Any] = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
A_ : ... | 57 |
'''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 | 0 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 110 |
'''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 | 0 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, requi... | 592 |
'''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 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
__lowerCAmelCase : Any = {
"microsoft/markuplm-base": "https://huggingface.co/mic... | 262 |
'''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 | 0 |
import argparse
import os
import re
import packaging.version
_lowerCamelCase = "examples/"
_lowerCamelCase = {
"examples": (re.compile(R'^check_min_version\(\"[^\"]+\"\)\s*$', re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R'^__version__\s+=\s+\"([^\"]+)\"\s... | 6 |
'''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 | 0 |
"""simple docstring"""
from __future__ import annotations
a = 1.60_21e-19 # units = C
def _snake_case ( _snake_case : float , _snake_case : float , _snake_case : float , ) -> tuple[str, float]:
'''simple docstring'''
... | 7 |
'''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 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : int = logging.get_logger(__name__)
__magic_name__ : Any = {
"sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json",
... | 280 |
'''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 | 0 |
from pathlib import Path
import fire
from tqdm import tqdm
def UpperCamelCase ( _a="ro" , _a="en" , _a="wmt16" , _a=None ) -> None:
'''simple docstring'''
try:
import datasets
except (ModuleNotFoundError, ImportError):
... | 257 |
'''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 | 0 |
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
_lowerCamelCase : int = "scheduler_config.json"
class lowercas... | 403 |
'''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 | 0 |
"""simple docstring"""
import socket
def __UpperCAmelCase ( ) -> Optional[Any]:
lowercase__ : str = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
lowercase__ : Union[str, Any] = socket.gethostname()
lowercase__ : ... | 560 |
'''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 | 0 |
def SCREAMING_SNAKE_CASE ( snake_case_ : str ):
snake_case__ : str = [0] * len(_lowerCAmelCase )
for i in range(1 , len(_lowerCAmelCase ) ):
# use last results for better performance - dynamic programming
snake_case__ : List[str] = prefix_result[i - 1]
while j > 0 ... | 297 |
'''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 | 0 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def snake_cas... | 57 |
'''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 | 0 |
"""simple docstring"""
from __future__ import annotations
UpperCamelCase__ = "#"
class a :
def __init__( self ):
UpperCAmelCase__ : dict = {}
def __snake_case ( self , UpperCamelCase_ ):
UpperCAmelCase__ : T... | 110 |
'''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 | 0 |
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 FeatureExtractionMixin, TensorType
snake_case_ ... | 592 |
'''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 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase__ : str , UpperCamelCase__ : list[str] | None = None ):
"""simple docstring"""
__UpperCAmelCase = word_bank or []
# create a table
__UpperCAmelCase ... | 262 |
'''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 | 0 |
_lowerCamelCase = [0, 2, 4, 6, 8]
_lowerCamelCase = [1, 3, 5, 7, 9]
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int , UpperCamelCase__: int , UpperCamelCase__: list[int] , UpperCamelCase__: int ):
if remaining_length == 0:
if digit... | 6 |
'''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 | 0 |
"""simple docstring"""
def _snake_case ( _snake_case : int ) -> bool:
'''simple docstring'''
_A = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 7 |
'''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 | 0 |
def lowercase__ ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase) -> Union[str, Any]:
"""simple docstring"""
if index == r:
for j in range(_lowerCAmel... | 280 |
'''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 | 0 |
class UpperCamelCase :
'''simple docstring'''
def __init__( self , UpperCamelCase_ ):
lowercase_ :List[Any] = n
lowercase_ :Dict = [None] * self.n
lowercase_ :List[Any] = 0 # index of the fi... | 257 |
'''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 | 0 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
_lowerCamelCase : List[str] = 0B101_100_111_110_110_010_010_000_011_110_11... | 403 |
'''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 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 560 |
'''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 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
__lowerCamelCase : Union[str, Any] = logging.get_logger(__name... | 297 |
'''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 | 0 |
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],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
... | 57 |
'''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 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase ( _snake_case ):
return [ord(_lowerCAmelCase ) - 96 for elem in plain]
def lowerCamelCase ( _snake_case ):
return "".join(chr(elem + 96 ) for elem in encoded )
def lowerCamelCase ( ):
UpperCAmel... | 110 |
'''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 | 0 |
def lowerCamelCase__ ( snake_case_ : Dict ) -> str:
__snake_case = 1
__snake_case = 2
while i * i <= n:
__snake_case = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1... | 592 |
'''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 | 0 |
'''simple docstring'''
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
__lowerCAmelCase : Union[str, Any] ... | 262 |
'''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 | 0 |
from math import isqrt
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int ):
SCREAMING_SNAKE_CASE__ = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , _lowerCAmelCase , _lowerCAmel... | 6 |
'''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 | 0 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker... | 7 |
'''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 | 0 |
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_available():
import t... | 280 |
'''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 | 0 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
SCREAMING_SNAKE_CASE : int = object()
# For specifying empty leaf dict `{}`
SCREAMING_SNAKE_CASE : Any ... | 257 |
'''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 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCamelCase : int = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvai... | 403 |
'''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 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORME... | 560 |
'''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 | 0 |
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
__lowerCamelCase : str = logging.get_logger(__name__)
__lowerCamelCase : Optional[in... | 297 |
'''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 | 0 |
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 transformers import AutoProcessor, BlipaProc... | 57 |
'''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 | 0 |
"""simple docstring"""
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def lowerCamelCase ( _snake_case ,_snake_case ,_snake_case ):
if not arr:
return None, None, 0
if low == high:... | 110 |
'''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 | 0 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
snake_case_ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'
... | 592 |
'''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 | 0 |
'''simple docstring'''
from __future__ import annotations
class A :
def __init__( self : Dict , __a : int = 0 ) -> Optional[Any]:
__UpperCAmelCase = key
def snake_case__ ( self : Union[str, An... | 262 |
'''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 | 0 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( A__ ):
def __init__( self :List[str] , *__A :List[str] , **__A :Any ) -> N... | 6 |
'''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 | 0 |
"""simple docstring"""
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
a = "src/transformers"
# This is to make sure the transformers module i... | 7 |
'''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 | 0 |
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_available():
import jax... | 280 |
'''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 | 0 |
SCREAMING_SNAKE_CASE : int = 8.31_44_62 # Unit - J mol-1 K-1
def UpperCamelCase ( _a , _a , _a ) -> float:
'''simple docstring'''
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter posit... | 257 |
'''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 | 0 |
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 __lowerCamelCase (UpperCAmelCase__ : Tuple , UpperCAmelCase__ : int , UpperC... | 403 |
'''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 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class __A ( ... | 560 |
'''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 | 0 |
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 transformers.utils import cached_property
from ...tes... | 297 |
'''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 | 0 |
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.schedulers.scheduling_utils import SchedulerMixin
from diffusers.utils import Ba... | 57 |
'''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 | 0 |
"""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__ = {
"linear": PIL.Image.Resampling.BILINEAR,
"bilinear": PIL.Image.... | 110 |
'''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 | 0 |
def lowerCamelCase__ ( snake_case_ : int ) -> int:
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ):
raise TypeError('''only integers accepted as input''' )
else:
__snake_case = str(abs(_lowerCAmelCase ) )
__snake_case = [l... | 592 |
'''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 | 0 |
'''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 import FlaxSchedulerM... | 262 |
'''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 | 0 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoModelWithLMHead,
... | 6 |
'''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 | 0 |
"""simple docstring"""
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... | 7 |
'''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 | 0 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixi... | 280 |
'''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 | 0 |
import copy
import importlib.metadata
import json
import os
from dataclasses import dataclass
from typing import Any, Dict, Union
from packaging import version
from ..utils import is_torch_available, logging
if is_torch_available():
import torch
SCREAMING_SNAKE_CASE : Any = ... | 257 |
'''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 | 0 |
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
class lowercase ( A__ ):
... | 403 |
'''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 | 0 |
"""simple docstring"""
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
lowerCAmelCase_ = logging.get_logger(__name__)
class __A :
... | 560 |
'''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 | 0 |
def SCREAMING_SNAKE_CASE ( snake_case_ : str ):
if not head:
return True
# split the list to two parts
snake_case__ : str = head.next, head
while fast and fast.next:
snake_case__ : Optional[Any] = fast.next.next
snake_case__ : Dict = slow.next
snake_case__ ... | 297 |
'''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 | 0 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ ) -> Optional[int]:
UpperCamelCase_: Any = OmegaCo... | 57 |
'''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 | 0 |
"""simple docstring"""
def lowerCamelCase ( _snake_case ,_snake_case ,_snake_case ,_snake_case ):
# Return True if there is node that has not iterated.
UpperCAmelCase__ : List[Any] = [False] * len(_lowerCAmelCase )
UpperCAmelCase__ : Tuple = []... | 110 |
'''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 | 0 |
import re
def lowerCamelCase__ ( snake_case_ : str ) -> str:
if len(re.findall('''[ATCG]''' , _lowerCAmelCase ) ) != len(_lowerCAmelCase ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '''TAGC''' ... | 592 |
'''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 | 0 |
'''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''':... | 262 |
'''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 | 0 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self :Tuple ) -> Optional[Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = [
... | 6 |
'''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 | 0 |
"""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
a = "http://www.mocksite.co... | 7 |
'''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 | 0 |
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
__magic_name__ : Tuple = {
"facebook/maskformer-swi... | 280 |
'''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 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datas... | 257 |
'''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 | 0 |
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
_lowerCamelCase : str = logging.get_logger(__name__)
_lowerCa... | 403 |
'''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 | 0 |
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