code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _UpperCAmelCase ( _UpperCAmelCase, ... | 371 |
"""simple docstring"""
def lowercase ( _snake_case : int ) ->str:
"""simple docstring"""
if number > 0:
raise ValueError('''input must be a negative integer''' )
__snake_case : Any = len(bin(_snake_case )[3:] )
__snake_case : List[Any] ... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : list[int] ) ->Dict:
"""simple docstring"""
__snake_case : int = []
if len(__a ) == 1:
return [nums.copy()]
for _ in range(len(__a ) ):
__snake_case : List[Any] = nums.pop(0 ... | 350 |
"""simple docstring"""
def lowercase ( ) ->int:
"""simple docstring"""
return [
a * b * (1_000 - a - b)
for a in range(1 , 999 )
for b in range(_snake_case , 999 )
if (a * a + b * b == (1_000 - a - b) ** 2)
][0]
if __name__ == "__main__":
p... | 24 | 0 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase ( _snake_case : Tuple , _snake_case : str , _snake_case : List[str] = None ) ->List[str]:
... | 351 |
"""simple docstring"""
def lowercase ( _snake_case : int = 100 ) ->int:
"""simple docstring"""
__snake_case : str = n * (n + 1) * (2 * n + 1) / 6
__snake_case : Dict = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE : List[Any] = TypeVar("""KT""")
SCREAMING_SNAKE_CASE : Optional[int] = TypeVar("""VT""")
class _UpperCAmelCase ( Generic[KT, VT] ):
... | 352 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
SCREAMING_SNAKE_CASE : int = datasets.utils.logging.get_logger(__name__)
@dataclass
cla... | 24 | 0 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_token... | 353 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArg... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def lowercase ( _snake_case : list ) ->Dict:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case : Dict = {"""+""", """-""", """*""", """/"""}
__snake_cas... | 354 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
SCREAMING_SNAKE_CASE : Tuple = None
try:
import msvcrt
except ImportError:
SCREAMING_SNAKE_CASE : List[str] = None
try:
import fcntl
except ImportError:
SC... | 24 | 0 |
def lowercase ( _snake_case : str ) ->bool:
"""simple docstring"""
__snake_case : Any = 0
for ch in input_str:
__snake_case : Any = ord(lowercase__ )
__snake_case : Dict = pow(2 , lowercase__ )
# If we alr... | 355 |
"""simple docstring"""
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 impor... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : int = 4_000_000 ) ->List[Any]:
"""simple docstring"""
__snake_case : Optional[Any] = [0, 1]
__snake_case : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib... | 356 |
"""simple docstring"""
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 ModelT... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( _snake_case : List[str] , _snake_case : Optional[int] , _snake_case : Union[str, Any] , _snake_case : Any ) ->Union[str, Any]:
"""simple docstring"""
... | 357 |
"""simple docstring"""
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.u... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : float , _snake_case : float ) ->float:
"""simple docstring"""
if density <= 0:
raise ValueError('''Impossible fluid density''' )
if bulk_modulus <= 0:
raise ValueError('''Impossible bulk modulus''' ... | 358 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 24 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def lowercase ( _snake_case : Union[str, Any] ) ->Dict:
"""simple docstring"""
if "img_encoder.pos_embed" in name:... | 359 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Optional[int] = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert... | 24 | 0 |
"""simple docstring"""
from collections import defaultdict
def lowercase ( _snake_case : Union[str, Any] , _snake_case : str ) ->bool:
"""simple docstring"""
__snake_case : Dict = first_str.lower().strip()
__snake_case : List[Any] ... | 360 |
"""simple docstring"""
def lowercase ( _snake_case : Union[str, Any] ) ->Union[str, Any]:
"""simple docstring"""
__snake_case : Tuple = len(_snake_case )
__snake_case : str = sum(_snake_case )
__snake_case : Dict = [[Fal... | 24 | 0 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[int] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : List[st... | 361 |
"""simple docstring"""
from collections.abc import Callable
def lowercase ( _snake_case : Callable[[float], float] , _snake_case : float , _snake_case : float ) ->float:
"""simple docstring"""
__snake_case : float = a
__sn... | 24 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE : Tuple = {
"""configuration_xlm""": ["""XLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMConfig""", """XLMOnnxConfig"""],
... | 362 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[str] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class _UpperCAmelCase :
'''simple docstring'''
def __init__(self , a_ ):
'''simple docstring'''
__snake_case : Optional[Any] = list_of_points
# Degree det... | 363 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _UpperCAmelCase ( __snake_case ):
'''simple docstring'''
lowerCamelCase__ =['image_processor', 'tokenizer']
lowerCamelCase__ ... | 24 | 0 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert im... | 364 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging... | 24 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.... | 365 |
"""simple docstring"""
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,
RobertaToke... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : int = 10**12 ) ->int:
"""simple docstring"""
__snake_case : Optional[Any] = 1
__snake_case : int = 0
__snake_case : List[Any] = 1
__snake_case : int = 1
wh... | 366 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : List[str] = {
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface... | 24 | 0 |
"""simple docstring"""
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
SCREAMING_SNAKE_CASE : Optional[int] ... | 367 |
"""simple docstring"""
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,
)
f... | 24 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_r... | 368 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase ( metaclass=__snake_case ):
'''simple docstring'''
lowerCamelCase__ =['transformers', 'torch', 'note_seq']
def __init__(self , *a_ , **a_ ):
'''simple docstring'... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER... | 369 |
"""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_avail... | 24 | 0 |
"""simple docstring"""
from torch import nn
def lowercase ( _snake_case : Tuple ) ->List[str]:
"""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 ValueE... | 370 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state imp... | 24 | 0 |
"""simple docstring"""
from math import factorial
class _UpperCAmelCase :
'''simple docstring'''
def __init__(self , a_ , a_ ):
'''simple docstring'''
__snake_case : Optional[int] = real
if isinstance(__lowercase , __lowercase ):
__snake_case : ... | 371 |
"""simple docstring"""
def lowercase ( _snake_case : int ) ->str:
"""simple docstring"""
if number > 0:
raise ValueError('''input must be a negative integer''' )
__snake_case : Any = len(bin(_snake_case )[3:] )
__snake_case : List[Any] ... | 24 | 0 |
"""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_video_inputs
if is_torch_avail... | 350 |
"""simple docstring"""
def lowercase ( ) ->int:
"""simple docstring"""
return [
a * b * (1_000 - a - b)
for a in range(1 , 999 )
for b in range(_snake_case , 999 )
if (a * a + b * b == (1_000 - a - b) ** 2)
][0]
if __name__ == "__main__":
p... | 24 | 0 |
"""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
from t... | 351 |
"""simple docstring"""
def lowercase ( _snake_case : int = 100 ) ->int:
"""simple docstring"""
__snake_case : str = n * (n + 1) * (2 * n + 1) / 6
__snake_case : Dict = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __... | 24 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmToken... | 352 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
SCREAMING_SNAKE_CASE : int = datasets.utils.logging.get_logger(__name__)
@dataclass
cla... | 24 | 0 |
"""simple docstring"""
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
SCREAMING_SNAKE_CASE : int = {
"""n_samples""": 64,
"""horizon""": 32,
"""num_inference_steps""": 20,
"""n_guide_steps""": 2, # can set to 0 for faster sampling, do... | 353 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArg... | 24 | 0 |
"""simple docstring"""
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowercase ( _snake_case : Optional[int] , _snake_case : bool = True , _snake_case : float = math.inf , _snake_case : fl... | 354 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
SCREAMING_SNAKE_CASE : Tuple = None
try:
import msvcrt
except ImportError:
SCREAMING_SNAKE_CASE : List[str] = None
try:
import fcntl
except ImportError:
SC... | 24 | 0 |
from __future__ import annotations
from math import pow, sqrt
def lowercase ( _snake_case : float , _snake_case : float , _snake_case : float ) ->List[str]:
"""simple docstring"""
if (resistance, reactance, impedance).count(0 ) != 1:
... | 355 |
"""simple docstring"""
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 impor... | 24 | 0 |
"""simple docstring"""
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformer... | 356 |
"""simple docstring"""
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 ModelT... | 24 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : Optional[Any] = {
"""configuration_instructblip""": [
"""INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""InstructBli... | 357 |
"""simple docstring"""
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.u... | 24 | 0 |
"""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_common i... | 358 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 24 | 0 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
Aut... | 359 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Optional[int] = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert... | 24 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tok... | 360 |
"""simple docstring"""
def lowercase ( _snake_case : Union[str, Any] ) ->Union[str, Any]:
"""simple docstring"""
__snake_case : Tuple = len(_snake_case )
__snake_case : str = sum(_snake_case )
__snake_case : Dict = [[Fal... | 24 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
query_table,
)
from .np_format... | 361 |
"""simple docstring"""
from collections.abc import Callable
def lowercase ( _snake_case : Callable[[float], float] , _snake_case : float , _snake_case : float ) ->float:
"""simple docstring"""
__snake_case : float = a
__sn... | 24 | 0 |
"""simple docstring"""
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
SCREAMING_SNAKE_CASE : Tuple = loggin... | 362 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[str] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""... | 24 | 0 |
"""simple docstring"""
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def... | 363 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _UpperCAmelCase ( __snake_case ):
'''simple docstring'''
lowerCamelCase__ =['image_processor', 'tokenizer']
lowerCamelCase__ ... | 24 | 0 |
"""simple docstring"""
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from t... | 364 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : List[str] , _snake_case : int , _snake_case : Union[str, Any] ) ->int:
"""simple docstring"""
if len(SCREAMING_SNAKE_CASE_ ) != len(SCREAMING_SNAKE_CASE_ ):
raise ValueError('''The le... | 365 |
"""simple docstring"""
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,
RobertaToke... | 24 | 0 |
"""simple docstring"""
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from t... | 366 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : List[str] = {
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface... | 24 | 0 |
"""simple docstring"""
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class _UpperCAmelCase ( _a ):
'''simple docstring'''
def __init__(self , a_ , a_ = None ... | 367 |
"""simple docstring"""
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,
)
f... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class _UpperCAmelCase :
'''simple docstring'''
def __init__(self , a_ = None ):
'''simple docstring'''
... | 368 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase ( metaclass=__snake_case ):
'''simple docstring'''
lowerCamelCase__ =['transformers', 'torch', 'note_seq']
def __init__(self , *a_ , **a_ ):
'''simple docstring'... | 24 | 0 |
"""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_avail... | 369 |
"""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_avail... | 24 | 0 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def lowercase ( _snake_case : Union[str, Any] = 1_500_000 ) ->Optional[Any]:
"""simple docstring"""
__snake_case : defaultdict = defaultdict(_snake_case )
__snake_case : ... | 370 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state imp... | 24 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE : Union[str, Any] = ... | 371 |
"""simple docstring"""
def lowercase ( _snake_case : int ) ->str:
"""simple docstring"""
if number > 0:
raise ValueError('''input must be a negative integer''' )
__snake_case : Any = len(bin(_snake_case )[3:] )
__snake_case : List[Any] ... | 24 | 0 |
"""simple docstring"""
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
b... | 350 |
"""simple docstring"""
def lowercase ( ) ->int:
"""simple docstring"""
return [
a * b * (1_000 - a - b)
for a in range(1 , 999 )
for b in range(_snake_case , 999 )
if (a * a + b * b == (1_000 - a - b) ** 2)
][0]
if __name__ == "__main__":
p... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : int = 1 , _snake_case : int = 1_000 ) ->Optional[int]:
"""simple docstring"""
__snake_case : List[str] = 1
__snake_case : Any = 0
for divide_by_number in range(UpperCamelCase... | 351 |
"""simple docstring"""
def lowercase ( _snake_case : int = 100 ) ->int:
"""simple docstring"""
__snake_case : str = n * (n + 1) * (2 * n + 1) / 6
__snake_case : Dict = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def lowercase ( ) ->List[str]:
"""simple docstring"""
__snake_case : Union[str, Any] = {}
__snake_case : Optional[Any] = 2
while True:
__snake_case :... | 352 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
SCREAMING_SNAKE_CASE : int = datasets.utils.logging.get_logger(__name__)
@dataclass
cla... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import random
class _UpperCAmelCase :
'''simple docstring'''
def __init__(self , a_ = None ):
'''simple docstring'''
__snake_case : Tuple = value
__snake_case : Any = rando... | 353 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArg... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : int = 200 ) ->int:
"""simple docstring"""
__snake_case : Union[str, Any] = [1, 2, 5, 10, 20, 50, 100, 200]
__snake_case : List[str] = [0] * (pence + 1)
__snake_case : List[str] = ... | 354 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
SCREAMING_SNAKE_CASE : Tuple = None
try:
import msvcrt
except ImportError:
SCREAMING_SNAKE_CASE : List[str] = None
try:
import fcntl
except ImportError:
SC... | 24 | 0 |
import argparse
import os
from accelerate.test_utils import execute_subprocess_async
def lowercase ( _snake_case : Union[str, Any]=None ) ->List[str]:
"""simple docstring"""
if subparsers is not None:
__snake_case : Optional[int] = subparsers.add_parser(''... | 355 |
"""simple docstring"""
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 impor... | 24 | 0 |
"""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
class ... | 356 |
"""simple docstring"""
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 ModelT... | 24 | 0 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusion... | 357 |
"""simple docstring"""
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.u... | 24 | 0 |
"""simple docstring"""
# flake8: noqa
# Lint as: python3
SCREAMING_SNAKE_CASE : Tuple = [
"""VerificationMode""",
"""Version""",
"""disable_progress_bar""",
"""enable_progress_bar""",
"""is_progress_bar_enabled""",
"""experimental""",
]
from .info_utils import VerificationMode
fro... | 358 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 24 | 0 |
"""simple docstring"""
from collections import Counter
from timeit import timeit
def lowercase ( _snake_case : str = "" , ) ->Dict:
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(''' ''' , '''''' ).lower() ).values() ) <... | 359 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Optional[int] = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def lowercase ( _snake_case : Optional[int] ) ->str:
"""simple docstring"""
return choice(_a )
def lowercase ( _snake_case : list[int] , _snake_case ... | 360 |
"""simple docstring"""
def lowercase ( _snake_case : Union[str, Any] ) ->Union[str, Any]:
"""simple docstring"""
__snake_case : Tuple = len(_snake_case )
__snake_case : str = sum(_snake_case )
__snake_case : Dict = [[Fal... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE : Tuple = {"""UserAgent""": UserAgent().random}
def lowercase ( _snake_case : List[Any] ) ->dic... | 361 |
"""simple docstring"""
from collections.abc import Callable
def lowercase ( _snake_case : Callable[[float], float] , _snake_case : float , _snake_case : float ) ->float:
"""simple docstring"""
__snake_case : float = a
__sn... | 24 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
SCREAMING_SNAKE_CASE : Optional[int] = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''... | 362 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[str] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""... | 24 | 0 |
"""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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_ou... | 363 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _UpperCAmelCase ( __snake_case ):
'''simple docstring'''
lowerCamelCase__ =['image_processor', 'tokenizer']
lowerCamelCase__ ... | 24 | 0 |
"""simple docstring"""
def lowercase ( ) ->int:
"""simple docstring"""
return 1
def lowercase ( _snake_case : int ) ->int:
"""simple docstring"""
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def lowercase ( _snake_case ... | 364 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging... | 24 | 0 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE : Dict = TypeVar("""_T""")
class _UpperCAmelCase ( Generic[_T] ):
'''simple docstring'''
def __init__(self , a_ = None ):
'''simple docstring'''
... | 365 |
"""simple docstring"""
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,
RobertaToke... | 24 | 0 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import Fla... | 366 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : List[str] = {
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface... | 24 | 0 |
"""simple docstring"""
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class _UpperCAmelCase :
'''simple docstring'''
def SCREAMING_SNAKE_CASE (self , a_ ):
'''simple docstring'''
raise NotImpl... | 367 |
"""simple docstring"""
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,
)
f... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : str ) ->List[Any]:
"""simple docstring"""
return " ".join(
''''''.join(word[::-1] ) if len(__UpperCamelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import do... | 368 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase ( metaclass=__snake_case ):
'''simple docstring'''
lowerCamelCase__ =['transformers', 'torch', 'note_seq']
def __init__(self , *a_ , **a_ ):
'''simple docstring'... | 24 | 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,
is_vision_available,
)
SCREAMING_SNAKE_CASE : Tuple = {
'configura... | 369 |
"""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_avail... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : int , _snake_case : int ) ->List[Any]:
"""simple docstring"""
while second != 0:
__snake_case : str = first & second
first ^= second
__snake_case : List[str] = c << 1
ret... | 370 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state imp... | 24 | 0 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def lowercase ( _snake_case : int , _snake_case : Tuple , ... | 371 |
"""simple docstring"""
def lowercase ( _snake_case : int ) ->str:
"""simple docstring"""
if number > 0:
raise ValueError('''input must be a negative integer''' )
__snake_case : Any = len(bin(_snake_case )[3:] )
__snake_case : List[Any] ... | 24 | 0 |
"""simple docstring"""
SCREAMING_SNAKE_CASE : Union[str, Any] = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def lowercase ( _snake_case : dict , _snake_case ... | 350 |
"""simple docstring"""
def lowercase ( ) ->int:
"""simple docstring"""
return [
a * b * (1_000 - a - b)
for a in range(1 , 999 )
for b in range(_snake_case , 999 )
if (a * a + b * b == (1_000 - a - b) ** 2)
][0]
if __name__ == "__main__":
p... | 24 | 0 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _UpperCAmelCase ( __lowercase, unittest.TestCase ):
'''simple docstring... | 351 |
"""simple docstring"""
def lowercase ( _snake_case : int = 100 ) ->int:
"""simple docstring"""
__snake_case : str = n * (n + 1) * (2 * n + 1) / 6
__snake_case : Dict = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __... | 24 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class _UpperCAmelCase ( un... | 352 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
SCREAMING_SNAKE_CASE : int = datasets.utils.logging.get_logger(__name__)
@dataclass
cla... | 24 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class _UpperCAmelCase ( unittest.TestCase ... | 353 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArg... | 24 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 354 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
SCREAMING_SNAKE_CASE : Tuple = None
try:
import msvcrt
except ImportError:
SCREAMING_SNAKE_CASE : List[str] = None
try:
import fcntl
except ImportError:
SC... | 24 | 0 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
SCREAMING_SNAKE_CASE : Union[str, Any] = TypeVar("""T""")
SCREAMING_SNAKE_CASE : Tuple = Union[List[T], Tuple[T, ...]]
SCREAMING_SNAKE_CASE : Union[str, Any] = Union[T, List[T], Dict[str, T]]
SCREAMING_SNAKE_CASE : ... | 355 |
"""simple docstring"""
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 impor... | 24 | 0 |
"""simple docstring"""
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,
)
f... | 356 |
"""simple docstring"""
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 ModelT... | 24 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
SCREAMING_SNAKE_CASE : str = {
'configuration_gpt_neo': ['GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoConfig', 'GPTNeoOnnxConfig'],
}
... | 357 |
"""simple docstring"""
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.u... | 24 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from... | 358 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 24 | 0 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowercase ( _snake_case : Optional[int] ) ->Any:
"""simple docstring"""
return ConvertCommand(
args.model_type , args... | 359 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Optional[int] = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : list , _snake_case : list , _snake_case : int ) ->int:
"""simple docstring"""
if len(_snake_case ) != len(_snake_case ):
raise ValueError('''The length of profit and weight must be sa... | 360 |
"""simple docstring"""
def lowercase ( _snake_case : Union[str, Any] ) ->Union[str, Any]:
"""simple docstring"""
__snake_case : Tuple = len(_snake_case )
__snake_case : str = sum(_snake_case )
__snake_case : Dict = [[Fal... | 24 | 0 |
"""simple docstring"""
import re
import subprocess
import sys
SCREAMING_SNAKE_CASE : List[Any] = subprocess.check_output("""git merge-base main HEAD""".split()).decode("""utf-8""")
SCREAMING_SNAKE_CASE : List[str] = (
subprocess.check_output(F'git diff --diff-filter=d --name-only {fork_po... | 361 |
"""simple docstring"""
from collections.abc import Callable
def lowercase ( _snake_case : Callable[[float], float] , _snake_case : float , _snake_case : float ) ->float:
"""simple docstring"""
__snake_case : float = a
__sn... | 24 | 0 |
"""simple docstring"""
from collections.abc import Generator
from math import sin
def lowercase ( _snake_case : Optional[int] ) ->bytes:
"""simple docstring"""
if len(UpperCAmelCase__ ) != 32:
raise ValueError('''Input must be of length 32''' )
__snake_case : ... | 362 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[str] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""... | 24 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _UpperCAmelCase ( ... | 363 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _UpperCAmelCase ( __snake_case ):
'''simple docstring'''
lowerCamelCase__ =['image_processor', 'tokenizer']
lowerCamelCase__ ... | 24 | 0 |
"""simple docstring"""
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class _Upper... | 364 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging... | 24 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import gcd
def lowercase ( _snake_case : int , _snake_case : int = 2 , _snake_case : int = 1 , _snake_case : int = 3 , ) ->int | None:
"""simple docstrin... | 365 |
"""simple docstring"""
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,
RobertaToke... | 24 | 0 |
"""simple docstring"""
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 : Tuple = (
"""This metric will be ... | 366 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : List[str] = {
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface... | 24 | 0 |
"""simple docstring"""
from manim import *
class _UpperCAmelCase ( UpperCamelCase__ ):
'''simple docstring'''
def SCREAMING_SNAKE_CASE (self ):
'''simple docstring'''
__snake_case : Dict = Rectangle(height=0.5 , width=0.5 )
__snake_case : ... | 367 |
"""simple docstring"""
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,
)
f... | 24 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import requests
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_imag... | 368 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase ( metaclass=__snake_case ):
'''simple docstring'''
lowerCamelCase__ =['transformers', 'torch', 'note_seq']
def __init__(self , *a_ , **a_ ):
'''simple docstring'... | 24 | 0 |
"""simple docstring"""
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def lowercase ( _snake_case : Any , _snake_case : List[Any] , _snake_case : str=0 ) ->Any:
"""simple doc... | 369 |
"""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_avail... | 24 | 0 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase ( _snake_case : Optional[int] ... | 370 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state imp... | 24 | 0 |
"""simple docstring"""
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import M... | 371 |
"""simple docstring"""
def lowercase ( _snake_case : int ) ->str:
"""simple docstring"""
if number > 0:
raise ValueError('''input must be a negative integer''' )
__snake_case : Any = len(bin(_snake_case )[3:] )
__snake_case : List[Any] ... | 24 | 0 |
"""simple docstring"""
import argparse
from .config import config_command_parser
from .config_args import default_config_file, load_config_from_file # noqa: F401
from .default import default_command_parser
from .update import update_command_parser
def lowercase ( _snake_case : Dict=None ... | 350 |
"""simple docstring"""
def lowercase ( ) ->int:
"""simple docstring"""
return [
a * b * (1_000 - a - b)
for a in range(1 , 999 )
for b in range(_snake_case , 999 )
if (a * a + b * b == (1_000 - a - b) ** 2)
][0]
if __name__ == "__main__":
p... | 24 | 0 |
"""simple docstring"""
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_do... | 351 |
"""simple docstring"""
def lowercase ( _snake_case : int = 100 ) ->int:
"""simple docstring"""
__snake_case : str = n * (n + 1) * (2 * n + 1) / 6
__snake_case : Dict = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __... | 24 | 0 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is... | 352 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
SCREAMING_SNAKE_CASE : int = datasets.utils.logging.get_logger(__name__)
@dataclass
cla... | 24 | 0 |
"""simple docstring"""
from collections.abc import Callable
def lowercase ( _snake_case : Callable[[float], float] , _snake_case : float , _snake_case : float ) ->float:
"""simple docstring"""
__snake_case : float = a
__sn... | 353 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArg... | 24 | 0 |
"""simple docstring"""
import json
import sys
def lowercase ( _snake_case : Optional[int] , _snake_case : Optional[int] ) ->List[str]:
"""simple docstring"""
with open(_snake_case , encoding='''utf-8''' ) as f:
__snake_case : Optiona... | 354 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
SCREAMING_SNAKE_CASE : Tuple = None
try:
import msvcrt
except ImportError:
SCREAMING_SNAKE_CASE : List[str] = None
try:
import fcntl
except ImportError:
SC... | 24 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
if is_flax_available... | 355 |
"""simple docstring"""
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 impor... | 24 | 0 |
"""simple docstring"""
from itertools import permutations
def lowercase ( _snake_case : tuple ) ->bool:
"""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
__snake_case :... | 356 |
"""simple docstring"""
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 ModelT... | 24 | 0 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_model... | 357 |
"""simple docstring"""
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.u... | 24 | 0 |
"""simple docstring"""
def lowercase ( _snake_case : list ) ->list:
"""simple docstring"""
if len(_snake_case ) <= 1:
return lst
__snake_case : List[str] = 1
while i < len(_snake_case ):
if lst[i - 1] <= lst[i]:
i += 1
else:
__snake_case ... | 358 |
"""simple docstring"""
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
impo... | 24 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_util... | 359 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Optional[int] = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert... | 24 | 0 |
"""simple docstring"""
import argparse
from collections import defaultdict
def lowercase ( _snake_case : Union[str, Any] , _snake_case : Tuple , _snake_case : Union[str, Any] , _snake_case : Optional[Any] , _snake_case : ... | 360 |
"""simple docstring"""
def lowercase ( _snake_case : Union[str, Any] ) ->Union[str, Any]:
"""simple docstring"""
__snake_case : Tuple = len(_snake_case )
__snake_case : str = sum(_snake_case )
__snake_case : Dict = [[Fal... | 24 | 0 |
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