code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import math
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> list:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = [True] * n
SCREAMING_SNAKE_CASE_ : List[str] = False
SCREAMING_SNAKE_CASE_ : Optional[Any] ... | 717 |
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 Conversation
UpperCam... | 685 | 0 |
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCAmelCase_ ( lowerCamelCase_ ):
def __lt__( self ,snake_case__ ):
return self[-1] < other[-1]
def __eq... | 718 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : int=() , lowerCamelCase_ ... | 685 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
... | 719 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Tuple = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : int = _LazyModule... | 685 | 0 |
'''simple docstring'''
from collections.abc import Callable
class lowerCAmelCase_ :
def __init__( self ,snake_case__ = None ):
# Stores actual heap items.
SCREAMING_SNAKE_CASE_ : list = []
# Stores indexes of each item for supporting update... | 720 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 685 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ... | 721 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fr... | 685 | 0 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
UpperCam... | 700 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __v... | 685 | 0 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : int=() , lowerCamelCase_ ... | 701 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Dict = logging.get_logger(__name__)
UpperCamelCase__ : Optional[int] = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
... | 685 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.mode... | 702 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> Union[str, Any]:
"""simple docstring"""
def is_in_circle(lowerCamelCase_ : float , ... | 685 | 0 |
'''simple docstring'''
import os
import jsonlines
import numpy as np
from tqdm import tqdm
UpperCamelCase__ : List[Any] = 20_48
UpperCamelCase__ : Optional[Any] = 40_96
UpperCamelCase__ : Dict = 42
UpperCamelCase__ : Any = os.environ.pop('''PROCESS_TRAIN'... | 703 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 685 | 0 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ) -> Tuple:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase_ , int(b / 2 ) ) * actual_power(lowerCamelCas... | 704 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTokenizerFast,
XLMRob... | 685 | 0 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __UpperCAmelCase ( ) -> List[str]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] = {
'repo_name': ['... | 705 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' , [None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' , ['default', 0, 1_00 * 2**20, 9_00 * 2**20] )
def __... | 685 | 0 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 706 |
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCamelCase__ : Any = 3_00 # TEMPERATURE (unit = K)
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float , ) ... | 685 | 0 |
'''simple docstring'''
from __future__ import annotations
from random import choice
def __UpperCAmelCase ( lowerCamelCase_ : List[Any] ) -> List[str]:
"""simple docstring"""
return choice(lowerCamelCase_ )
def __UpperCAmelCase ( lowerCame... | 707 |
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ :
def __init__( self ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = [
[],
... | 685 | 0 |
from __future__ import annotations
from typing import Any
class lowerCAmelCase_ :
def __init__( self ,snake_case__ ):
SCREAMING_SNAKE_CASE_ : List[Any] = num_of_nodes
SCREAMING_SNAKE_CASE_ : list[list[int]] = []
SCREAMING_SNAK... | 708 |
def __UpperCAmelCase ( lowerCamelCase_ : int = 10_00 ) -> int:
"""simple docstring"""
return sum(e for e in range(3 , lowerCamelCase_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 685 | 0 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcessor, ResN... | 709 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=lowerCamelCase_ ):
__a : Tuple = ["flax"]
def __init__( self ,*snake_case__ ,**snake_case__ ):
requires_backends(self ,['flax'] )
@classmethod
... | 685 | 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_xlnet impo... | 710 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
UpperCamelCase__ : Union[str, Any] = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow('''''', ''... | 685 | 0 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class lowerCAmelCase_ ( lowerCamelCase_ ):
__a : Optional[... | 711 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE_ : Tuple = 0
... | 685 | 0 |
from math import factorial
UpperCamelCase__ : Optional[Any] = {str(d): factorial(d) for d in range(10)}
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> int:
"""simple docstring"""
return sum(DIGIT_FACTORIAL[d] for d in str(lowerCamelCase_ ) ... | 712 |
import qiskit
def __UpperCAmelCase ( lowerCamelCase_ : int = 2 ) -> qiskit.result.counts.Counts:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = qubits
# Using Aer's simulator
SCREAMING_SNAKE_CASE_ : Optional[int] = q... | 685 | 0 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
UpperCamelCase__ : Dict = logging.getLogger(__name__)
@dataclass
class lowerCAmelCas... | 713 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> bool:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise ValueError('check_bouncy() accepts only integer arguments' )
SCREAMING_SNAKE_CASE_ : Optional[i... | 685 | 0 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Tuple = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : int = _LazyModule(__nam... | 714 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : Dict = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
... | 685 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase_ ( lowerCamelCase_ ):
__a : List[Any] = ["image_processor", "tokenizer"]
__a : List[Any] = "ChineseCLIPIma... | 715 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ) -> Tuple:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase_ , int(b / 2 ) ) * actual_power(lowerCamelCas... | 685 | 0 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
cl... | 716 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 685 | 0 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Pr... | 717 |
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 Conversation
UpperCam... | 685 | 0 |
from collections.abc import Callable
import numpy as np
def __UpperCAmelCase ( lowerCamelCase_ : Callable , lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float ) -> np.arr... | 718 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : int=() , lowerCamelCase_ ... | 685 | 0 |
import math
import os
import sys
def __UpperCAmelCase ( lowerCamelCase_ ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = ''
try:
with open(lowerCamelCase_ , 'rb' ) as binary_file:
SCREAMING_SNAKE_CASE_ ... | 719 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Tuple = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : int = _LazyModule... | 685 | 0 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew... | 720 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 685 | 0 |
UpperCamelCase__ : Any = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def __UpperCAmelCase ( lowerCamelCase_ : Optional[Any] , lowerCamelCase_ : str , ... | 721 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fr... | 685 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase :str = {
'''configuration_nllb_moe''': [
'''NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''NllbMoeConfig''',
... | 686 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase :Any = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''Lon... | 686 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 686 | 1 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCase :str = get_tests_dir('''fixt... | 686 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class _lowerCAmelCase ( __UpperCAmelCase , unittest.TestCase ):
__SCREAMING_SNAKE_CAS... | 686 | 1 |
'''simple docstring'''
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keeping the
# fu... | 686 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ = None ):
'''simple docstring'''
A_ : List[Any] = word_bank or []
# create a table
A_ : int = len(lowerCamelCase__ ) + 1
A_ : list[list[list[str]]] =... | 686 | 1 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase :Optio... | 686 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : int = []
A_ : int = set({"""(""", """[""", """{"""} )
A_ : Union[str, Any] = set({""")""", """]""", """}"""} )
A_ : Tuple = {"""{""": """}""", """[""": """]""", """("""... | 686 | 1 |
'''simple docstring'''
import random
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
A_ : int = a[left_index]
A_ : int = left_index + 1
for j in range(left_index + 1 , lowerCamelCase__ ):
if a[j] < pivot:
... | 686 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 686 | 1 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_ava... | 686 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase :Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa... | 686 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase :str = {
'''configuration_x_clip''': [
'''XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XCLIPConfig''',
''... | 686 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase :Any = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''Lon... | 686 | 1 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accel... | 686 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCamelCase :Any = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/... | 686 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identi... | 686 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 | 1 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
f... | 686 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
class _lowerCA... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_model... | 686 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-smal... | 686 | 1 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase :Tuple = log... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Any = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is... | 686 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase :Optio... | 686 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase :Tuple = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Foca... | 686 |
'''simple docstring'''
from math import factorial
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
... | 686 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Optional[int] = logging.get_logger(__name__)
lowerCamelCase :Dict ... | 686 |
'''simple docstring'''
import re
def a ( lowerCamelCase__ ):
'''simple docstring'''
if len(re.findall("""[ATCG]""" , lowerCamelCase__ ) ) != len(lowerCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , ... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def a ( lowerCamelCase__ , lowerCamelCase__=0 ):
'''simple docstring'''
return sorted(lowerCame... | 686 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ):
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 686 | 1 |
'''simple docstring'''
from torch import nn
def a ( lowerCamelCase__ ):
'''simple docstring'''
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f'Uns... | 686 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fr... | 686 | 1 |
'''simple docstring'''
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 a ( lowerCamelCase__ ):
'''simple... | 686 |
'''simple docstring'''
import pytest
lowerCamelCase :Optional[Any] = '''__dummy_dataset1__'''
lowerCamelCase :List[Any] = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = ... | 686 | 1 |
'''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager impo... | 686 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase :int = datasets.load_iris()
lowerCamelCase :str = np.array(data['''data'''])
lowerCamelCase ... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_c... | 686 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowerCamelCase :List[str] = logging.get_logg... | 686 | 1 |
'''simple docstring'''
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVi... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def a ( lowerCamelCase__ ):
'''simple docstring'''
... | 686 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 | 1 |
'''simple docstring'''
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa... | 686 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 686 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :str = logging.get_logger(__name__)
lowerCamelCase :str ... | 686 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class _lowerCAmelCase ( __UpperCAmelCase , unittest.TestCase ):
__SCREAMING_SNAKE_CAS... | 686 | 1 |
'''simple docstring'''
import numpy as np
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ = 1E-12 , lowerCamelCase__ = 1_00 , ):
'''simple docstring'''
assert np.shape(lowerCamelCase__ )[0] == np.shape(lowerCamelCase__ )[1]
# Ensure proper dimensional... | 686 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ = None ):
'''simple docstring'''
A_ : List[Any] = word_bank or []
# create a table
A_ : int = len(lowerCamelCase__ ) + 1
A_ : list[list[list[str]]] =... | 686 | 1 |
'''simple docstring'''
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_d... | 686 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : int = []
A_ : int = set({"""(""", """[""", """{"""} )
A_ : Union[str, Any] = set({""")""", """]""", """}"""} )
A_ : Tuple = {"""{""": """}""", """[""": """]""", """("""... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ = None ):
'''simple docstring'''
A_ : List[Any] = word_bank or []
# create a table
A_ : int = len(lowerCamelCase__ ) + 1
A_ : list[list[list[str]]] =... | 686 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 686 | 1 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
["""empty:README.md"""... | 686 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase :Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa... | 686 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
cla... | 686 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase :Any = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''Lon... | 686 | 1 |
'''simple docstring'''
import warnings
warnings.warn(
'''memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '''
'''`from accelerate import find_executable_batch_size` to avoid this warning.''',
FutureWarning,
) | 686 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCamelCase :Any = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/... | 686 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase :Tuple = logging.get_logger(__name__)
lowerCamelCase :Any = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-... | 686 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 686 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
class _lowerCA... | 686 | 1 |
'''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_dict impor... | 686 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-smal... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def a ( lowerCamelCase__ ):
'''simple docstring'''
return np.maximum(0 , lowerCamelCase__ )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5] | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Any = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
lowerCamelCase :str = logging.get_logger(__name__)
class _lowerCAmelCase ( __UpperCAmelCase ):
def __init__(self , *lowercase , ... | 686 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase :Optio... | 686 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
f... | 686 |
'''simple docstring'''
from math import factorial
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
... | 686 | 1 |
'''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
lowerCamelCase :str = datasets.logging.get_logger(__name__)
lowerCamelCase :List[str] = '''\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig... | 686 |
'''simple docstring'''
import re
def a ( lowerCamelCase__ ):
'''simple docstring'''
if len(re.findall("""[ATCG]""" , lowerCamelCase__ ) ) != len(lowerCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , ... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ = 50 ):
'''simple docstring'''
A_ : Any = [[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 - tile_length... | 686 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ):
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(lowerCamelCase__ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__('''doctest''').testmod() | 686 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fr... | 686 | 1 |
'''simple docstring'''
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
lowerCamelCase :Optional[Any] = '''\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language... | 686 |
'''simple docstring'''
import pytest
lowerCamelCase :Optional[Any] = '''__dummy_dataset1__'''
lowerCamelCase :List[Any] = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = ... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
A_ : int = len(lowerCamelCase__ )
A_ : int = len(lowerCamelCase__ )
A_ : int = (
first_str_length if first_str_length > second_str_length else second_str... | 686 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase :int = datasets.load_iris()
lowerCamelCase :str = np.array(data['''data'''])
lowerCamelCase ... | 686 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerC... | 686 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowerCamelCase :List[str] = logging.get_logg... | 686 | 1 |
'''simple docstring'''
from graphs.minimum_spanning_tree_kruskal import kruskal
def a ( ):
'''simple docstring'''
A_ : Dict = 9
A_ : List[str] = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
[2, 8, 2],
[8, 6, 6],
... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase :Opt... | 686 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 | 1 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_... | 686 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 686 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerCamelCase :List[str] = {
'''caidas/swin2sr-classicalsr-x2-64''': (
'''https://huggingface.co/... | 686 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class _lowerCAmelCase ( __UpperCAmelCase , unittest.TestCase ):
__SCREAMING_SNAKE_CAS... | 686 | 1 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( lowerCamelCase__ = 3 ):
'''simple docstring'''
if isinstance(lowerCamelCase__ , lowerCamelCase__ ):
raise TypeE... | 686 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ = None ):
'''simple docstring'''
A_ : List[Any] = word_bank or []
# create a table
A_ : int = len(lowerCamelCase__ ) + 1
A_ : list[list[list[str]]] =... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , ):
'''simple docstring'''
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supply more or less than 2 v... | 686 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : int = []
A_ : int = set({"""(""", """[""", """{"""} )
A_ : Union[str, Any] = set({""")""", """]""", """}"""} )
A_ : Tuple = {"""{""": """}""", """[""": """]""", """("""... | 686 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
Wav... | 686 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ = 3 , lowerCamelCase__ = 7 , lowerCamelCase__ = 1_00_00_00 ):
'''simple docstring'''
A_ : List[str] = 0
A_ : Any = 1
for current_denominator in range(1 , limit + 1 ):
A_ : List[Any] = current_deno... | 686 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase :Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : Optional[int] = [0] * len(lowerCamelCase__ )
A_ : Optional[int] = []
A_ : Any = []
A_ : List[str] = 0
for values in graph.values():
for i in values:
inde... | 686 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase :Any = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''Lon... | 686 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowerCamelCase :Optional[Any] = {
'''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Erni... | 686 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCamelCase :Any = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/... | 686 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 686 |
'''simple docstring'''
lowerCamelCase :dict[tuple[int, int, int], int] = {}
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not fail... | 686 | 1 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glu... | 686 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
class _lowerCA... | 686 | 1 |
'''simple docstring'''
import math
from collections.abc import Callable
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
A_ : float = xa
A_ : float = xa
while True:
if x_n == x_na or function(lowerCamelCase__ ) ... | 686 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-smal... | 686 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :Any = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_cha... | 686 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
lowerCamelCase :Optio... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
return int((input_a, input_a).count(1 ) != 0 )
def a ( ):
'''simple docstring'''
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
asse... | 686 |
'''simple docstring'''
from math import factorial
def a ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
... | 686 |
'''simple docstring'''
import re
def a ( lowerCamelCase__ ):
'''simple docstring'''
if len(re.findall("""[ATCG]""" , lowerCamelCase__ ) ) != len(lowerCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , ... | 686 | 1 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
if not head:
return True
# split the list to two parts
A_, A_ : List[Any] = head.next, head
while fast and fast.next:
A_ : Dict = fast.next.next
A_ : Dict = slow.nex... | 686 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a ( ):
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 686 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class _lowerCAmelCase :
def __init__(self , lowercase = None ):
if components is None:
A_ : Tuple = []
A_ : L... | 686 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
fr... | 686 | 1 |
'''simple docstring'''
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v ... | 686 |
'''simple docstring'''
import pytest
lowerCamelCase :Optional[Any] = '''__dummy_dataset1__'''
lowerCamelCase :List[Any] = '''
import json
import os
import datasets
REPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"
URLS = ... | 686 | 1 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
class _lowerCA... | 686 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase :int = datasets.load_iris()
lowerCamelCase :str = np.array(data['''data'''])
lowerCamelCase ... | 686 | 1 |
'''simple docstring'''
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impor... | 686 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowerCamelCase :List[str] = logging.get_logg... | 686 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase :Dict = {
'''google/pegasus-large''': '''https://huggingface.co/google/pegasus-... | 686 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase :int = logging.get_logger(__name__)
lowerC... | 686 | 1 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_com... | 686 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 | 1 |
'''simple docstring'''
from collections import defaultdict
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : str = 1
A_ : List[Any] = True
for v in tree[start]:
if v not in visited:
ret += dfs(lowerCamelCase__ )
if ret % 2 == 0:
cuts... | 686 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_... | 686 | 1 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="""session""" )
def a ( ):
'''s... | 686 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class _lowerCAmelCase ( __UpperCAmelCase , unittest.TestCase ):
__SCREAMING_SNAKE_CAS... | 686 | 1 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..u... | 686 |
'''simple docstring'''
from __future__ import annotations
def a ( lowerCamelCase__ , lowerCamelCase__ = None ):
'''simple docstring'''
A_ : List[Any] = word_bank or []
# create a table
A_ : int = len(lowerCamelCase__ ) + 1
A_ : list[list[list[str]]] =... | 686 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)... | 686 |
'''simple docstring'''
def a ( lowerCamelCase__ ):
'''simple docstring'''
A_ : int = []
A_ : int = set({"""(""", """[""", """{"""} )
A_ : Union[str, Any] = set({""")""", """]""", """}"""} )
A_ : Tuple = {"""{""": """}""", """[""": """]""", """("""... | 686 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase :Optional[int] = logging.get_logger(__name__)
lowerCamelCase :Any = {
'''SCUT-DLVCLab/lilt-roberta-en-base''': (
'''https://huggingfac... | 686 |
'''simple docstring'''
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 686 | 1 |
'''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, prepare_image_inputs
if is_torch_... | 686 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase :Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa... | 686 | 1 |
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