code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_b... | 648 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Optional[Any] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': [... | 648 | 1 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import... | 648 |
from __future__ import annotations
from math import pi
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one argument must be 0""")
if... | 648 | 1 |
from __future__ import annotations
lowercase_: List[str] = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
class lowercase__ :
"""simple docstring"""
... | 648 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceCla... | 648 | 1 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ = "cpu" , UpperCAmelCase_ = None):
"""simple docstring"""
snake_case__ : Optional[int] = torch.load(UpperCAmelCase_ , ... | 648 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : Any = (CMStochasticIterativeScheduler,)
__UpperCa... | 648 | 1 |
# 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-2.0
#
# Unless ... | 648 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save... | 648 | 1 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
lowercase_: Any = '\\n@misc{chen2021evaluating,\n title={Evaluati... | 648 |
# Copyright 2023 The HuggingFace 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-2.0
#
# Unless requi... | 648 | 1 |
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 accelerate import ... | 648 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : List[str] ):
debug_launch... | 648 | 1 |
def _lowercase ( UpperCAmelCase_=28_123):
"""simple docstring"""
snake_case__ : Dict = [1] * (limit + 1)
for i in range(2 , int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1):
sum_divs[k * i] += k + i
sn... | 648 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = year % 19
snake_case__ : Tuple = year % 4
snake_case__ : Any = year % 7
... | 648 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowercase_: Dict = {'tokenization_byt5': ['ByT5Tokenizer']}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
lowercase_: Any = _LazyModule(__name__, globals()['__f... | 648 |
import torch
from diffusers import DiffusionPipeline
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : List[Any] , __a : Optional[Any] , __a : List[str] ):
super().__init__()
self.register_modules(unet=__a ... | 648 | 1 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
lowercase_: Optional[Any] = logging.get_logger('transformers.models.speecht5')
def _lowercase ( UpperCAmelCase_ , UpperCA... | 648 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 | 1 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = year % 19
snake_case__ : Tuple = year % 4
snake_case__ : Any = year % 7
... | 648 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 648 | 1 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
return 1 if digit in (0, 1) else (digit * factorial(digit - 1))
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : List[Any] = 0
snake_case__ : Any ... | 648 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
... | 648 |
def _lowercase ( UpperCAmelCase_ = 10 , UpperCAmelCase_ = 1_000 , UpperCAmelCase_ = True):
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCA... | 648 | 1 |
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 accelerate import ... | 648 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not is_accelerate_available():
return method
snake_case__ : Union[str, An... | 648 | 1 |
from __future__ import annotations
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Optional[int] = 0.00
snake_case__ : str = 0
for resistor in resistors:
if resistor <= 0:
snake_case__ : Optional[int... | 648 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 | 1 |
from typing import Dict, Optional
import numpy as np
import datasets
lowercase_: Optional[int] = '\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two ... | 648 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 | 1 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 648 |
from collections import namedtuple
lowercase_: Optional[int] = namedtuple('from_to', 'from_ to')
lowercase_: str = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 10_00),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
... | 648 | 1 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.util... | 648 |
def _lowercase ( UpperCAmelCase_=28_123):
"""simple docstring"""
snake_case__ : Dict = [1] * (limit + 1)
for i in range(2 , int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1):
sum_divs[k * i] += k + i
sn... | 648 | 1 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class lowercase__ :
"""simple docstring"""
__UpperCamelCase : Optional[str] = field(
default='codeparrot/codeparrot' , metadata={'help': 'Model name or path... | 648 |
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, PatchingSp... | 648 | 1 |
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from t... | 648 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: int = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertC... | 648 | 1 |
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Dict = len(UpperCAmelCase_)
snake_case__ : List[Any] = [[False] * (required_sum + 1) for _ in range(arr_len + 1)]
# for each arr value, a sum... | 648 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 648 | 1 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_t... | 648 |
from __future__ import annotations
import math
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are ... | 648 | 1 |
import itertools
import string
from collections.abc import Generator, Iterable
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
snake_case__ : List[str] = iter(UpperCAmelCase_)
while True:
snake_case__ : Tuple ... | 648 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Optional[Any] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': [... | 648 | 1 |
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ = 10**-10):
"""simple docstring"""
snake_case__ : List[str] ... | 648 |
from __future__ import annotations
from math import pi
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one argument must be 0""")
if... | 648 | 1 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceCla... | 648 | 1 |
lowercase_: Union[str, 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 _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAm... | 648 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : Any = (CMStochasticIterativeScheduler,)
__UpperCa... | 648 | 1 |
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowercase__ (__snake_case ):
"""simple docstring"""
def __lt__( self : List[str] , __a : Tuple ):
... | 648 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save... | 648 | 1 |
import enum
import shutil
import sys
lowercase_ , lowercase_: List[Any] = shutil.get_terminal_size()
lowercase_: str = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class lowercase__ (enum.Enum ):
"""simple docstring"""
... | 648 |
# Copyright 2023 The HuggingFace 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-2.0
#
# Unless requi... | 648 | 1 |
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowercase_: Optional[int] = numpy.array([0, 0])
lowercase_: List[str] = numpy.array([0.5, 0.8_6_6_0_2_5_4])
lowercase_: Optional[int] ... | 648 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : List[str] ):
debug_launch... | 648 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@req... | 648 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = year % 19
snake_case__ : Tuple = year % 4
snake_case__ : Any = year % 7
... | 648 | 1 |
import functools
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_) or not all(isinstance(UpperCAmelCase_ , UpperCAmelCase_) for day in days):
raise ValueError("""The parameter days sh... | 648 |
import torch
from diffusers import DiffusionPipeline
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : List[Any] , __a : Optional[Any] , __a : List[str] ):
super().__init__()
self.register_modules(unet=__a ... | 648 | 1 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
lowercase_: Union[str, Any] = logging.getLogger(__name__)
class lowercase__ (__snake_case ... | 648 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowercase_: Optional[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 check_copies # noqa: E4... | 648 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 648 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having m... | 648 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 | 1 |
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor
if... | 648 |
def _lowercase ( UpperCAmelCase_ = 10 , UpperCAmelCase_ = 1_000 , UpperCAmelCase_ = True):
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCA... | 648 | 1 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params impor... | 648 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not is_accelerate_available():
return method
snake_case__ : Union[str, An... | 648 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class lowercase__ (__snake_case ):
... | 648 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 | 1 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
lowercase_: Tuple = TypeVar('T')
class lowercase__ (Generic[T] ):
"""simple docstring"""
__UpperCamelCase : deque[T] # Cache... | 648 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 | 1 |
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def _lowercase ( Uppe... | 648 |
from collections import namedtuple
lowercase_: Optional[int] = namedtuple('from_to', 'from_ to')
lowercase_: str = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 10_00),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
... | 648 | 1 |
from __future__ import annotations
from collections.abc import Generator
def _lowercase ( ):
"""simple docstring"""
snake_case__ : dict[int, int] = {}
snake_case__ : str = 2
while True:
snake_case__ : Union[str, Any] ... | 648 |
def _lowercase ( UpperCAmelCase_=28_123):
"""simple docstring"""
snake_case__ : Dict = [1] * (limit + 1)
for i in range(2 , int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1):
sum_divs[k * i] += k + i
sn... | 648 | 1 |
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
lowercase_: Optional[Any] = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( s... | 648 |
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, PatchingSp... | 648 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_: Dict = {
'configuration_wav2vec2': ['WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Wav2V... | 648 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: int = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertC... | 648 | 1 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : int = int(number**0.5)
return number == sq * sq
def _lowercase ( UpperCAmelCase_ ,... | 648 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 648 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Optional[Any] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': [... | 648 |
from __future__ import annotations
import math
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are ... | 648 | 1 |
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
lowercase_: List[str] = 3
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
print("""Generating primitive root of p""")
while True:
snake_cas... | 648 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Optional[Any] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': [... | 648 | 1 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if n_term == "":
return []
snake_case__ : list = []
for temp in range(int(UpperCAmelCase_)):
series.append(F'1/{temp + 1}' if series else """1""")
return series
if __name__ == "__main__":
l... | 648 |
from __future__ import annotations
from math import pi
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one argument must be 0""")
if... | 648 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Any = {
'configuration_altclip': [
'ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'AltCLIPConfig',
'AltCLIPT... | 648 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceCla... | 648 | 1 |
from __future__ import annotations
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if len(UpperCAmelCase_) < k or k < 0:
raise ValueError("""Invalid Input""")
snake_case__ : Union[str, Any] = sum(array[:k])
for i in range(l... | 648 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : Any = (CMStochasticIterativeScheduler,)
__UpperCa... | 648 | 1 |
import argparse
import json
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... | 648 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save... | 648 | 1 |
from math import factorial
lowercase_: dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_):
raise TypeError("""Parameter number ... | 648 |
# Copyright 2023 The HuggingFace 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-2.0
#
# Unless requi... | 648 | 1 |
from functools import lru_cache
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Optional[int] = 2
snake_case__ : List[Any] = set()
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.add(Upper... | 648 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : List[str] ):
debug_launch... | 648 | 1 |
from __future__ import annotations
import os
from typing import Any
import requests
lowercase_: Optional[int] = 'https://api.github.com'
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowercase_: List[Any] = BASE_URL ... | 648 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = year % 19
snake_case__ : Tuple = year % 4
snake_case__ : Any = year % 7
... | 648 | 1 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
lowercase_: Optional[int] = logging.get_logger(__name__)
lowercase_: Dict = 'T5Config'
class lowerc... | 648 |
import torch
from diffusers import DiffusionPipeline
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : List[Any] , __a : Optional[Any] , __a : List[str] ):
super().__init__()
self.register_modules(unet=__a ... | 648 | 1 |
# Copyright 2023 The HuggingFace 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-2.0
#
# Unless requi... | 648 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 | 1 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
C... | 648 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 648 | 1 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
lowercase_: Optional[int] = datasets.utils.logging.get_logger(__name__)
class lowercase__ (folder_based_builder.FolderBasedB... | 648 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 | 1 |
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
assert x is not None
assert y is not None
snake_case__ : str = len(UpperCAmelCase_)
snake_case__ : int = len(UpperCAmelCase_)
# declaring the array fo... | 648 |
def _lowercase ( UpperCAmelCase_ = 10 , UpperCAmelCase_ = 1_000 , UpperCAmelCase_ = True):
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCA... | 648 | 1 |
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
return x + 2
class lowercase__ (unittest.TestCase ):
"""simple do... | 648 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not is_accelerate_available():
return method
snake_case__ : Union[str, An... | 648 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_: List[str] = logging.get_logger(__name__)
lowercase_: Any = {
'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json',
# See all V... | 648 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 | 1 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : Optional[int] = (IPNDMScheduler,)
__UpperCamel... | 648 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 | 1 |
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from t... | 648 |
from collections import namedtuple
lowercase_: Optional[int] = namedtuple('from_to', 'from_ to')
lowercase_: str = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 10_00),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
... | 648 | 1 |
from math import loga
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if a < 0:
raise ValueError("""Input value must be a positive integer""")
elif isinstance(UpperCAmelCase_ , UpperCAmelCase_):
raise TypeError("""Input value must be a 'int' type""")
return 0... | 648 |
def _lowercase ( UpperCAmelCase_=28_123):
"""simple docstring"""
snake_case__ : Dict = [1] * (limit + 1)
for i in range(2 , int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1):
sum_divs[k * i] += k + i
sn... | 648 | 1 |
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
lowercase_: str = 'src/transformers... | 648 |
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, PatchingSp... | 648 | 1 |
import string
from math import logaa
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = document.translate(
str.maketrans("""""" , """""" , string.punctuation)).replace("""\n""" ... | 648 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: int = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertC... | 648 | 1 |
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,
AutoMo... | 648 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 648 | 1 |
from __future__ import annotations
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not nums:
raise ValueError("""List is empty""")
return sum(UpperCAmelCase_) / len(UpperCAmelCase_)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 648 |
from __future__ import annotations
import math
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are ... | 648 | 1 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : int = False
while is_sorted is False: # Until all the indices are traversed keep looping
snake_case__ : Optional[Any] = True
for i in range(0 , len(UpperCAm... | 648 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Optional[Any] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': [... | 648 | 1 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ = False):
"""simple docstring"""
if radian_mode:
return [magnitude * ... | 648 |
from __future__ import annotations
from math import pi
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one argument must be 0""")
if... | 648 | 1 |
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""... | 648 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceCla... | 648 | 1 |
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class lowercase__ (ctypes.Structure ):
"""simple docstring"""
__UpperCamelCase : Dict = [('size', ctypes.c_i... | 648 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : Any = (CMStochasticIterativeScheduler,)
__UpperCa... | 648 | 1 |
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
lowercase_: int = {
'sample_size': 32,
'in_channels': 3,
'out_channels': 3,
'layers_per_block': 2,
'num_clas... | 648 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save... | 648 | 1 |
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowercase_: str = TypeVar('KT')
lowercase_: Optional[Any] = TypeVar('VT')
class lowercase__ (Generic[KT, VT] ):
"""simple docstring"""
... | 648 |
# Copyright 2023 The HuggingFace 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-2.0
#
# Unless requi... | 648 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import ... | 648 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : List[str] ):
debug_launch... | 648 | 1 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save... | 648 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = year % 19
snake_case__ : Tuple = year % 4
snake_case__ : Any = year % 7
... | 648 | 1 |
from collections import namedtuple
lowercase_: Optional[int] = namedtuple('from_to', 'from_ to')
lowercase_: str = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 10_00),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
... | 648 |
import torch
from diffusers import DiffusionPipeline
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : List[Any] , __a : Optional[Any] , __a : List[str] ):
super().__init__()
self.register_modules(unet=__a ... | 648 | 1 |
import numpy as np
from PIL import Image
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Optional[int] = np.array(UpperCAmelCase_)
if arr.shape[0] != arr.shape[1]:
raise ValueError("""... | 648 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 | 1 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 648 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 648 | 1 |
lowercase_: int = range(2, 20 + 1)
lowercase_: Any = [10**k for k in range(ks[-1] + 1)]
lowercase_: dict[int, dict[int, list[list[int]]]] = {}
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
... | 648 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 | 1 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
from... | 648 |
def _lowercase ( UpperCAmelCase_ = 10 , UpperCAmelCase_ = 1_000 , UpperCAmelCase_ = True):
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCA... | 648 | 1 |
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
lowercase_: int = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.195... | 648 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if not is_accelerate_available():
return method
snake_case__ : Union[str, An... | 648 | 1 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowercase_: Dict = None
try:
import msvcrt
except ImportError:
lowercase_: List[Any] = None
try:
import fcntl
except ImportError:
lowercase_: Optional[int] ... | 648 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 | 1 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = AutoConfig.... | 648 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase_: Tuple = {
'tiny.en': 'https://openaipublic.azureedge.net/main/wh... | 648 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image... | 648 |
from collections import namedtuple
lowercase_: Optional[int] = namedtuple('from_to', 'from_ to')
lowercase_: str = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 10_00),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_7_2),
... | 648 | 1 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
lowercase_: A... | 648 |
def _lowercase ( UpperCAmelCase_=28_123):
"""simple docstring"""
snake_case__ : Dict = [1] * (limit + 1)
for i in range(2 , int(limit**0.5) + 1):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1):
sum_divs[k * i] += k + i
sn... | 648 | 1 |
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, PatchingSp... | 648 |
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, PatchingSp... | 648 | 1 |
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
while a != 0:
snake_case__ , snake_case__ : Tuple = b % a, a
return b
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
... | 648 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_: int = {
'configuration_lxmert': ['LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LxmertC... | 648 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils import loggin... | 648 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 648 | 1 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids... | 648 |
from __future__ import annotations
import math
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are ... | 648 | 1 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
lowercase_: int = pd.read_csv('sample_data.csv', header=None)
lowercase_: Uni... | 648 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_: Optional[Any] = {
'configuration_canine': ['CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CanineConfig'],
'tokenization_canine': [... | 648 | 1 |
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 lowercase__ (__snake_case , unitte... | 648 |
from __future__ import annotations
from math import pi
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if (inductance, frequency, reactance).count(0) != 1:
raise ValueError("""One and only one argument must be 0""")
if... | 648 | 1 |
import argparse
import json
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... | 648 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceCla... | 648 | 1 |
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
if discount_rate < 0:
raise ValueError("""Discount rate cannot be negative""")
if not cash_flows:
raise ValueError("""Cash flows list cannot be empty""")
snake_case__ : Dict ... | 648 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ (__snake_case ):
"""simple docstring"""
__UpperCamelCase : Any = (CMStochasticIterativeScheduler,)
__UpperCa... | 648 | 1 |
def _lowercase ( UpperCAmelCase_ = 10 , UpperCAmelCase_ = 1_000 , UpperCAmelCase_ = True):
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCAmelCase_ , UpperCAmelCase_)
and isinstance(UpperCA... | 648 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save... | 648 | 1 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 |
# Copyright 2023 The HuggingFace 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-2.0
#
# Unless requi... | 648 | 1 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 648 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ (unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : List[str] ):
debug_launch... | 648 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_: Optional[Any] = logging.get_logger(__name__)
lowercase_: Optional[Any] = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'tiiu... | 648 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Union[str, Any] = year % 19
snake_case__ : Tuple = year % 4
snake_case__ : Any = year % 7
... | 648 | 1 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowercase__ :
"""simple docstring"""
__UpperCamelCase : torch.Tensor # [batch_size x 3]
__UpperCamelCase : torch.Tensor # [batch_size x 3]
... | 648 |
import torch
from diffusers import DiffusionPipeline
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : List[Any] , __a : Optional[Any] , __a : List[str] ):
super().__init__()
self.register_modules(unet=__a ... | 648 | 1 |
from itertools import product
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_):
"""simple docstring"""
snake_case__ : int = sides_number
snake_case__ : Any = max_face_number * dice_number
snake_case__ : Optional[Any] ... | 648 |
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_: str = logging.get_logger(__name__)
class lowercase__ (__snake_case ):
"""simple docstring"""
def __init__( self : in... | 648 | 1 |
from __future__ import annotations
from collections.abc import Iterator
class lowercase__ :
"""simple docstring"""
def __init__( self : List[Any] , __a : int ):
snake_case__ : int = value
snake_case__ : Node | None ... | 648 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import... | 648 | 1 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
lowercase_: List[Any] = namedtuple('covid_data', 'cases deaths recovered')
def _lowercase ( UpperCAmelCase_ = "https://www.worldometers.info/coronavirus/"):
"""simple docstring"""
... | 648 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowercase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
"""simple docstring"""
snake_case__ , sna... | 648 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.