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 unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __lowercase ( unittest.TestCase ):
snake_case_ = JukeboxTokenizer
snake_case_ = {
""... | 65 |
"""simple docstring"""
from sklearn.metrics import fa_score
import datasets
__UpperCAmelCase = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
__UpperCAmelCase = '\nArgs... | 65 | 1 |
"""simple docstring"""
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformer... | 65 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_avail... | 65 | 1 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
__UpperCAmelCase = get_logger(__name__)
__UpperCAmelCase = r'\n Args:\n input_ids (`jnp.nda... | 65 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=__lowerCamelCase ):
snake_case_ = ["""onnx"""]
def __init__( self : int ,*A : List[str] ,**A : int ):
... | 65 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torc... | 65 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase__ : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [... | 65 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase = False ):
'''simple docstring'''
if not arr:
return 0
UpperCAmelCase__ : str = 0 if allow_empty_subarrays else float("""-inf""" ... | 65 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tenso... | 65 | 1 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTest... | 65 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
UpperCAmelCase__ : Union[str, Any] ... | 65 | 1 |
"""simple docstring"""
from itertools import permutations
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
UpperCAmelCase__ ... | 65 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase ( __UpperCamelCase = "isbn/0140328726" ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = olid.strip().... | 65 | 1 |
"""simple docstring"""
from collections import deque
from .hash_table import HashTable
class __lowercase ( __lowerCamelCase ):
def __init__( self : List[str] ,*A : Optional[Any] ,**A : Optional[int] ):
'''simple docst... | 65 |
"""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
... | 65 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_... | 65 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, lo... | 65 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from tra... | 65 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
... | 65 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__lowerCamelCase )
class __lowercase ( __lowerCamelCase ... | 65 |
"""simple docstring"""
import requests
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = {"""Content-Type""": """application/json"""}
UpperCAmelCase__ : Optional[Any] = requ... | 65 | 1 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase=None ):
'''simple docstring'''
UpperCAmel... | 65 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowercase ( __lowerCamelCase , unittest.TestC... | 65 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/re... | 65 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCAmelCase = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowe... | 65 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __lowercase ( __lowerCamelCase ):
def __init__( self : Optional[Any] ... | 65 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_util... | 65 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCAmelCase = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowe... | 65 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image... | 65 | 1 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
fro... | 65 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
... | 65 | 1 |
"""simple docstring"""
class __lowercase ( __lowerCamelCase ):
pass
class __lowercase ( __lowerCamelCase ):
pass
class __lowercase :
def __init__( self : Union[str, Any] ):
'''simple docstring'''
... | 65 |
"""simple docstring"""
from collections.abc import Callable
class __lowercase :
def __init__( self : Tuple ,A : Callable | None = None ):
'''simple docstring'''
# Stores actual heap items.
UpperCAmelCase__ : list = ... | 65 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__UpperCAmelCase = {
'configuration_mobilevit': ['MOBILEVIT_PRETRAINED_CONFIG_... | 65 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchF... | 65 | 1 |
"""simple docstring"""
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific no... | 65 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase ( __UpperCamelCase = 100 ):
'''simple docstring'''
return sum(int(__UpperCamelCase ) for x in str(factorial(__UpperCamelCase ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter t... | 65 | 1 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class __lowercase :
def __init__( self : int ):
'''simple docstring'''
UpperCAmelCase__ : Dict = """"""
Upper... | 65 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_availab... | 65 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __lowercase ( snake_case ):
"""simple docstring"""
... | 0 |
"""simple docstring"""
__UpperCAmelCase = frozenset(
[
'prompt',
'height',
'width',
'guidance_scale',
'negative_prompt',
'prompt_embeds',
'negative_prompt_embeds',
'cross_attention_kwargs',
]
)
__UpperCAmelCase = ... | 65 | 0 |
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
__snake_case = logging.getLogger(__name__)
if is_torch_tpu_available(c... | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import Au... | 65 | 0 |
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def SCREAMING_SNAKE_CASE_ ( _sna... | 2 |
"""simple docstring"""
from sklearn.metrics import fa_score
import datasets
__UpperCAmelCase = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
__UpperCAmelCase = '\nArgs... | 65 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
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 Backbo... | 3 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_avail... | 65 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : Sequence[float] , _UpperCAmelCase : float ):
return sum(c * (x**i) for i, c in enumerate(_UpperCAmelCase ) )
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : Sequence[flo... | 4 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=__lowerCamelCase ):
snake_case_ = ["""onnx"""]
def __init__( self : int ,*A : List[str] ,**A : int ):
... | 65 | 0 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_lowercase = logging.get_log... | 5 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase__ : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [... | 65 | 0 |
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
_lowerCamelCase = logging.get_logger(__name__)
def SCREAMIN... | 6 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tenso... | 65 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class lowercase_ :
'''simple docstring'''
def __init__( self : Dict , _UpperCAmelCase : int = 6 ):
_A = None
_A = None
self.create_linked_list(_UpperCAmelC... | 7 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
UpperCAmelCase__ : Union[str, Any] ... | 65 | 0 |
'''simple docstring'''
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : Optional[int] = set_counts
__A : Optional[int] = max(_UpperCAmelCase)
... | 8 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase ( __UpperCamelCase = "isbn/0140328726" ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = olid.strip().... | 65 | 0 |
def A ( __UpperCamelCase ) -> str:
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 9 |
"""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
... | 65 | 0 |
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
def _snake_case ( __snake_case ):
if isinstance(__snake_case , np.ndarray ):
return list(tensor.shape )
... | 10 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, lo... | 65 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowercase_ = {
"google/tapas-base-finetuned-sqa": (
"https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"
),
"google/tapas-base-finetuned-wtq": (
"https://huggingface.... | 11 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
... | 65 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDependencyNo... | 12 |
"""simple docstring"""
import requests
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = {"""Content-Type""": """application/json"""}
UpperCAmelCase__ : Optional[Any] = requ... | 65 | 0 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import... | 13 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowercase ( __lowerCamelCase , unittest.TestC... | 65 | 0 |
a__ = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 1000000,
"gigajoule": 1000000000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 3600000,
"newtonmeter": 1.0,
"calorie_nutr": 4186.8,
"kilocalorie_nutr": 4186800.00,
"electronvolt": 1.6... | 14 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCAmelCase = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowe... | 65 | 0 |
import math
from collections.abc import Callable
def UpperCamelCase ( __magic_name__ : Callable[[float], float] , __magic_name__ : float , __magic_name__ : float ) -> float:
"""simple docstring"""
lowercase__ = xa
lowercase_... | 15 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_util... | 65 | 0 |
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 16 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image... | 65 | 0 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
UpperCAmelCase_ : List[str] = lo... | 17 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
... | 65 | 0 |
'''simple docstring'''
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.preproce... | 18 |
"""simple docstring"""
from collections.abc import Callable
class __lowercase :
def __init__( self : Tuple ,A : Callable | None = None ):
'''simple docstring'''
# Stores actual heap items.
UpperCAmelCase__ : list = ... | 65 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_a = {
"""configuration_blenderbot""": [
... | 19 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchF... | 65 | 0 |
def _lowercase( __a : list[int] ):
a__ =len(__a )
for i in range(__a ):
for j in range(i + 1 , __a ):
if numbers[j] < numbers[i]:
a__ , a__ =numbers[j], numbers[i]
return numbers
... | 20 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase ( __UpperCamelCase = 100 ):
'''simple docstring'''
return sum(int(__UpperCamelCase ) for x in str(factorial(__UpperCamelCase ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter t... | 65 | 0 |
from sklearn.metrics import matthews_corrcoef
import datasets
UpperCAmelCase_ : Dict = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It take... | 21 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_availab... | 65 | 0 |
'''simple docstring'''
from math import factorial
_snake_case : Optional[int] = {str(d): factorial(d) for d in range(10)}
def snake_case_ (UpperCamelCase : int ):
'''simple docstring'''
return sum(DIGIT_FACTORIAL[d] for d in str(UpperCamelCase ... | 22 |
"""simple docstring"""
__UpperCAmelCase = frozenset(
[
'prompt',
'height',
'width',
'guidance_scale',
'negative_prompt',
'prompt_embeds',
'negative_prompt_embeds',
'cross_attention_kwargs',
]
)
__UpperCAmelCase = ... | 65 | 0 |
def _snake_case (__lowercase):
UpperCamelCase_ = [0] * len(__lowercase)
UpperCamelCase_ = []
UpperCamelCase_ = [1] * len(__lowercase)
for values in graph.values():
for i in values:
indegree[i] += 1
for i in range(len(__lowercase)):
... | 23 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import Au... | 65 | 0 |
'''simple docstring'''
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _UpperCamelCase (_lowerCamelCase : List[str] , _lowerCamelCase : Any , _lowerCamelCas... | 24 |
"""simple docstring"""
from sklearn.metrics import fa_score
import datasets
__UpperCAmelCase = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
__UpperCAmelCase = '\nArgs... | 65 | 0 |
a_ = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def lowerCamelCase__ ( ):
SCREAMING_SNAKE_CASE : Union[str, Any] = input("Enter message: ")
SCREAMING_SNAKE_CASE : Dict = input("Enter key [alphanumeric]: ")
SCREAMING_SNAKE_CASE : str = input("Encrypt/Decrypt [e/d]: "... | 25 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_avail... | 65 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class _A ( _... | 26 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=__lowerCamelCase ):
snake_case_ = ["""onnx"""]
def __init__( self : int ,*A : List[str] ,**A : int ):
... | 65 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
f... | 27 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase__ : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [... | 65 | 0 |
'''simple docstring'''
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
UpperCamelCase_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
UpperCamelCase_ = [ord(letter) for lette... | 28 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tenso... | 65 | 0 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
fr... | 29 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
UpperCAmelCase__ : Union[str, Any] ... | 65 | 0 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
__a = ... | 30 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase ( __UpperCamelCase = "isbn/0140328726" ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = olid.strip().... | 65 | 0 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 |
"""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
... | 65 | 0 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ... | 32 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, lo... | 65 | 0 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class __... | 33 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
... | 65 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE_ = {
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
... | 34 |
"""simple docstring"""
import requests
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = {"""Content-Type""": """application/json"""}
UpperCAmelCase__ : Optional[Any] = requ... | 65 | 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
a_ :Tuple = object()
# For specifying empty leaf dict `{}`
a_ :str = object()
def a ( A__ , A__ ... | 35 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowercase ( __lowerCamelCase , unittest.TestC... | 65 | 0 |
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
__lowercase : Any = logging.get_logger(__name__)
__lowercase : str = {
'''... | 36 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCAmelCase = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowe... | 65 | 0 |
def UpperCamelCase_ ( __a ) -> list[int]:
a__ : str = len(__a )
for i in range(__a ):
for j in range(i + 1 , __a ):
if numbers[j] < numbers[i]:
a__, a__ : List[Any] = numbers[j], numbers[i]
return n... | 37 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_util... | 65 | 0 |
'''simple docstring'''
import sys
import turtle
def UpperCamelCase__ ( __magic_name__ : tuple[float, float] , __magic_name__ : tuple[float, float] ) -> tuple[float, float]:
'''simple docstring'''
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def Upp... | 38 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image... | 65 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelC... | 39 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
... | 65 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
__UpperCAmelCase = {'''configuration_vit''': ['''VIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTConfig''',... | 40 |
"""simple docstring"""
from collections.abc import Callable
class __lowercase :
def __init__( self : Tuple ,A : Callable | None = None ):
'''simple docstring'''
# Stores actual heap items.
UpperCAmelCase__ : list = ... | 65 | 0 |
'''simple docstring'''
lowerCAmelCase__ = range(2, 20 + 1)
lowerCAmelCase__ = [10**k for k in range(ks[-1] + 1)]
lowerCAmelCase__ = {}
def _A ( A__ , A__ , A__ , A__ ):
"""simple docstring"""
__lowercase = sum(a_i[j] for j in range... | 41 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchF... | 65 | 0 |
'''simple docstring'''
def _UpperCamelCase ( __UpperCamelCase = 10_00 ) -> int:
return sum(e for e in range(3 ,__UpperCamelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f'''{solution() = }''')
| 42 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase ( __UpperCamelCase = 100 ):
'''simple docstring'''
return sum(int(__UpperCamelCase ) for x in str(factorial(__UpperCamelCase ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter t... | 65 | 0 |
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class _a ( datasets.BuilderConfig ):
_lowercase : Optional[datasets.Features] ... | 43 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_availab... | 65 | 0 |
'''simple docstring'''
UpperCAmelCase_ : Dict = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'... | 44 |
"""simple docstring"""
__UpperCAmelCase = frozenset(
[
'prompt',
'height',
'width',
'guidance_scale',
'negative_prompt',
'prompt_embeds',
'negative_prompt_embeds',
'cross_attention_kwargs',
]
)
__UpperCAmelCase = ... | 65 | 0 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"nielsr/canine-s": 2_048,
}
# Unicode defines 1,114,112 total “codepoints”
UpperCam... | 45 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import Au... | 65 | 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 IFWatermar... | 46 |
"""simple docstring"""
from sklearn.metrics import fa_score
import datasets
__UpperCAmelCase = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
__UpperCAmelCase = '\nArgs... | 65 | 0 |
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
SCREAMING_SNAKE_CASE__ = (
'''This metric will be removed ... | 47 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_avail... | 65 | 0 |
'''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, RandomResizedCrop, Resize, ToTensor
from ac... | 48 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=__lowerCamelCase ):
snake_case_ = ["""onnx"""]
def __init__( self : int ,*A : List[str] ,**A : int ):
... | 65 | 0 |
"""simple docstring"""
def lowercase__ ( snake_case_ :int , snake_case_ :Union[str, Any] ):
print('''\nThe shortest path matrix using Floyd Warshall algorithm\n''' )
for i in range(snake_case_ ):
for j in range(snake_case_ ):
if dist[i][j] != float('''inf''' ... | 49 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase__ : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [... | 65 | 0 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from... | 50 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tenso... | 65 | 0 |
'''simple docstring'''
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def __snake_case ( SCREAMING_SNAKE_CASE_ : Optional[int] , SCREAMING_SNAKE_CASE_ : Tuple=7 ) -> Dict:
"""simple docstring"""
UpperCA... | 51 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
UpperCAmelCase__ : Union[str, Any] ... | 65 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'''roberta-base''': '''... | 52 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase ( __UpperCamelCase = "isbn/0140328726" ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = olid.strip().... | 65 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class _UpperCAmelCase ... | 53 |
"""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
... | 65 | 0 |
from __future__ import annotations
def a__ ( lowercase__ , lowercase__ = None ):
'''simple docstring'''
UpperCAmelCase_ =word_bank or []
# create a table
UpperCAmelCase_ =len(lowercase__ ) + 1
UpperCAmelCase_ ... | 54 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, lo... | 65 | 0 |
def UpperCAmelCase ( a_ = "The quick brown fox jumps over the lazy dog" , ) -> bool:
"""simple docstring"""
__A = set()
# Replace all the whitespace in our sentence
__A = input_str.replace(" " , "" )
for alpha in input_str:
if... | 55 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
... | 65 | 0 |
'''simple docstring'''
def _a (lowercase__ : int , lowercase__ : int ) -> float:
"""simple docstring"""
return base * power(lowercase__ , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print("Raise base to the power of exponent usi... | 56 |
"""simple docstring"""
import requests
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = {"""Content-Type""": """application/json"""}
UpperCAmelCase__ : Optional[Any] = requ... | 65 | 0 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switc... | 57 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowercase ( __lowerCamelCase , unittest.TestC... | 65 | 0 |
"""simple docstring"""
__lowerCAmelCase : dict[tuple[int, int, int], int] = {}
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : int , __UpperCamelCase : int ):
'''simple docstring'''
... | 58 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCAmelCase = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowe... | 65 | 0 |
__A = "\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/transformers.git\n... | 59 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_util... | 65 | 0 |
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_available():
from .tokenization_barthez import... | 60 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image... | 65 | 0 |
from __future__ import annotations
from collections import deque
class __lowerCamelCase :
"""simple docstring"""
def __init__( self : Any , SCREAMING_SNAKE_CASE__ : list[str] ) -> Optional[int]:
lowerCAmelCase__ = []
self.a... | 61 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
... | 65 | 0 |
def lowerCamelCase__ ( lowercase = 50 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Dict = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - ... | 62 |
"""simple docstring"""
from collections.abc import Callable
class __lowercase :
def __init__( self : Tuple ,A : Callable | None = None ):
'''simple docstring'''
# Stores actual heap items.
UpperCAmelCase__ : list = ... | 65 | 0 |
class a :
"""simple docstring"""
def __init__( self : List[str] ) -> None:
__UpperCAmelCase : dict[str, TrieNode] = {} # Mapping from char to TrieNode
__UpperCAmelCase : List[str] = False
def UpperCAmel... | 63 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchF... | 65 | 0 |
from math import pi, sqrt, tan
def A__ ( snake_case_ : float ):
if side_length < 0:
raise ValueError('''surface_area_cube() only accepts non-negative values''' )
return 6 * side_length**2
def A__ ( snake_case_ : float , snake_case_ : float , s... | 64 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase ( __UpperCamelCase = 100 ):
'''simple docstring'''
return sum(int(__UpperCamelCase ) for x in str(factorial(__UpperCamelCase ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter t... | 65 | 0 |
import functools
from typing import Any
def __magic_name__ ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> bool:
# Validation
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) or len(SCREAMING_SNAKE_CASE ) == 0:
raise Value... | 66 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_availab... | 65 | 0 |
from __future__ import annotations
from collections import deque
class A_ :
"""simple docstring"""
def __init__( self : str ,__A : list[str] ) -> List[str]:
_lowercase = []
self.... | 67 |
"""simple docstring"""
__UpperCAmelCase = frozenset(
[
'prompt',
'height',
'width',
'guidance_scale',
'negative_prompt',
'prompt_embeds',
'negative_prompt_embeds',
'cross_attention_kwargs',
]
)
__UpperCAmelCase = ... | 65 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt models at https://huggingface.co/models?filter=cvt
}
class _A... | 68 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import Au... | 65 | 0 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
a : int = log... | 69 |
"""simple docstring"""
from sklearn.metrics import fa_score
import datasets
__UpperCAmelCase = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
__UpperCAmelCase = '\nArgs... | 65 | 0 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversati... | 70 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_avail... | 65 | 0 |
'''simple docstring'''
def a__ ( _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : bool = False ) -> str:
"""simple docstring"""
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
UpperCAmelCase_ : str = F'''Expec... | 71 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=__lowerCamelCase ):
snake_case_ = ["""onnx"""]
def __init__( self : int ,*A : List[str] ,**A : int ):
... | 65 | 0 |
'''simple docstring'''
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('''socket.socket''' )
@patch('''builtins.open''' )
def UpperCamelCase ( lowercase_ : int , lowercase_ : List[str] ) -> Dict:
'''simple docstring'''
lowerc... | 72 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase__ : Optional[int] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [... | 65 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _snake_case ( A__ ):
@staticmethod
@abstractmethod
def SCREAMING_SNAKE_CASE__ ( a) -> Union[str, Any]:
raise NotImplementedError()
@abstractmethod
def SCREAMING_SNAKE_CASE_... | 73 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tenso... | 65 | 0 |
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 __UpperCamelCase ( unittest.TestCase ):
"""simp... | 74 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
UpperCAmelCase__ : Union[str, Any] ... | 65 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ = {
'''configuration_electra''': [''... | 75 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase ( __UpperCamelCase = "isbn/0140328726" ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = olid.strip().... | 65 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare... | 76 |
"""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
... | 65 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A = logging.get_logger(__name__)
A = {
"""facebook/convnextv2-tiny-1k-224""": """... | 77 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, lo... | 65 | 0 |
'''simple docstring'''
import qiskit
def lowerCAmelCase_ ( snake_case_ : int , snake_case_ : int ) -> qiskit.result.counts.Counts:
'''simple docstring'''
UpperCAmelCase_ = qiskit.Aer.get_backend("aer_simulator" )
# Create a Quantu... | 78 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
... | 65 | 0 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
... | 79 |
"""simple docstring"""
import requests
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
'''simple docstring'''
UpperCAmelCase__ : Tuple = {"""Content-Type""": """application/json"""}
UpperCAmelCase__ : Optional[Any] = requ... | 65 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=_lowerCAmelCase )
class __UpperCamelCase ( _lowerCAmelCase ):
__snake_case :str = field(default='au... | 80 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowercase ( __lowerCamelCase , unittest.TestC... | 65 | 0 |
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