code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
def _lowerCamelCase ( a_ : int):
lowerCamelCase :List[Any] = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def _lowerCamelCase ( a_ : int = 50_00):
lowerCamelCase :str = [(i * (3 * i - 1)) // 2 for i in range(1 , __UpperCamelCase)]... | 721 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""andreasmadsen/efficient_mlm_m0.40""": (
... | 49 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_att... | 700 | import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase... | 49 | 0 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
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_con... | 701 | import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import wr... | 49 | 0 |
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class _lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
def ... | 702 | import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_... | 49 | 0 |
from math import ceil, sqrt
def _lowerCamelCase ( a_ : int = 1_00_00_00):
lowerCamelCase :Tuple = 0
for outer_width in range(3 , (limit // 4) + 2):
if outer_width**2 > limit:
lowerCamelCase :int = max(ceil(sqrt(outer_width**2 - limit... | 703 | import os
from math import logaa
def _lowerCamelCase ( a_ : str = "base_exp.txt"):
lowerCamelCase :float = 0
lowerCamelCase :Optional[int] = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(a_) , a_))):
lowerCamelCase , lowe... | 49 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class _lowerCAmelCase :
def __init__( self : List[str] , __snake_case : Collection[float] | None = None ... | 704 | def _lowerCamelCase ( a_ : list):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''')
for cell_n in range(1 , len(grid[0])):
grid[0][cell_n] += grid[0][cell_n - 1]
lowerCamelCase :Any = grid[0]
for ... | 49 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, TensorType... | 705 | import math
def _lowerCamelCase ( a_ : int):
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 not primes
return False
# All primes number... | 49 | 0 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenizati... | 706 | import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_av... | 49 | 0 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
... | 707 | from maths.prime_factors import prime_factors
def _lowerCamelCase ( a_ : int):
if not isinstance(a_ , a_):
lowerCamelCase :Tuple = F"Input value of [number={number}] must be an integer"
raise TypeError(a_)
if number < 1:
raise ValueError('''Input ... | 49 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"distilbert-base-uncased": "https://huggingface.co/distilbert-... | 708 | import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
... | 49 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
'''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GraphormerConfig'''],
}
try:
if not ... | 709 | def _lowerCamelCase ( a_ : int = 4_00_00_00):
lowerCamelCase :Dict = [0, 1]
lowerCamelCase :Optional[Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1])
if fib[i + 2] > n:
break
i += 1
lowerCamelCase :Dict = ... | 49 | 0 |
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention, ImageClassifierOutputWith... | 710 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A__ = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
if not is_torch_available(... | 49 | 0 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""vocab_file""": """vocab.json""",
"""merges... | 711 | import numpy
class _lowerCAmelCase :
def __init__( self : Dict , __snake_case : numpy.ndarray , __snake_case : numpy.ndarray ):
lowerCamelCase :Dict = input_array
# Random initial weights are assigned where first argument... | 49 | 0 |
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_up_block
@dataclass
class _l... | 712 | def _lowerCamelCase ( a_ : str , a_ : str):
lowerCamelCase :List[str] = len(a_)
lowerCamelCase :List[str] = len(a_)
lowerCamelCase :int = [[False for _ in range(m + 1)] for _ in range(n + 1)]
lowerCamelCase :Optional[Any] = ... | 49 | 0 |
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
A__ = logging.getLogger(__name__)
@dataclass
class ... | 713 | import inspect
import unittest
from transformers import YolosConfig
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_configuration_common import ConfigTester
from ...tes... | 49 | 0 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class _lowerCAmelCase ( unittest.TestCase ):
def snake_case ( self : str ):
lowerCamelCase :Optional[Any] ... | 714 | import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils import p... | 49 | 0 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
A__ = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1), 6: ... | 715 | import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
_UpperCAmelCase = ''
_UpperCAmelCase = (
None # p... | 49 | 0 |
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, load_n... | 716 | import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...t... | 49 | 0 |
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 transform... | 717 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A__ = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Layo... | 49 | 0 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowerCamelCase ( ):
lowerCamelCase :Dict = ArgumentParser(
description=(
'''PyTorch TPU distributed training ... | 718 | import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is... | 49 | 0 |
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
A__ = lo... | 719 | import operator as op
def _lowerCamelCase ( a_ : Tuple):
lowerCamelCase :int = []
lowerCamelCase :List[str] = lambda a_ , a_: int(x / y) # noqa: E731 integer division operation
lowerCamelCase :Optional[int] = {
'''^''': op.... | 49 | 0 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerF... | 720 | import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fai... | 49 | 0 |
A__ : Union[str, Any] = "\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
A__ : str = [{"type": "code", "content": INSTALL_CONTENT}]
A... | 721 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""andreasmadsen/efficient_mlm_m0.40""": (
... | 49 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""microsoft/trocr-base-handwritten""": (
"""https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"""
),
... | 700 | import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase... | 49 | 0 |
def _lowerCamelCase ( a_ : Any):
lowerCamelCase :Optional[int] = []
lowerCamelCase :Optional[Any] = []
lowerCamelCase :List[str] = {
'''^''': 3,
'''*''': 2,
'''/''': 2,
'''%''': 2,
'''+''': 1,
'''-''': 1,
} ... | 701 | import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import wr... | 49 | 0 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _lowerCAmelCase ( unittest.TestCase ):
def snake_case ( sel... | 702 | import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_... | 49 | 0 |
def _lowerCamelCase ( a_ : Optional[int] = 1_00_00_00):
lowerCamelCase :Tuple = 1
lowerCamelCase :Any = 1
lowerCamelCase :Union[str, Any] = {1: 1}
for inputa in range(2 , lowerCAmelCase_):
lowerCamelCase :List[Any] = ... | 703 | import os
from math import logaa
def _lowerCamelCase ( a_ : str = "base_exp.txt"):
lowerCamelCase :float = 0
lowerCamelCase :Optional[int] = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(a_) , a_))):
lowerCamelCase , lowe... | 49 | 0 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
A__ = logging.getLogger(__name__)
... | 704 | def _lowerCamelCase ( a_ : list):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''')
for cell_n in range(1 , len(grid[0])):
grid[0][cell_n] += grid[0][cell_n - 1]
lowerCamelCase :Any = grid[0]
for ... | 49 | 0 |
from functools import reduce
A__ = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""66896648... | 705 | import math
def _lowerCamelCase ( a_ : int):
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 not primes
return False
# All primes number... | 49 | 0 |
def _lowerCamelCase ( a_ : Tuple , a_ : Optional[int]):
lowerCamelCase :Tuple = (boundary[1] - boundary[0]) / steps
lowerCamelCase :Any = boundary[0]
lowerCamelCase :str = boundary[1]
lowerCamelCase :Tuple = make_points(... | 706 | import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_av... | 49 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class _lowerCAmelCase ( UpperCAmelCase_ ... | 707 | from maths.prime_factors import prime_factors
def _lowerCamelCase ( a_ : int):
if not isinstance(a_ , a_):
lowerCamelCase :Tuple = F"Input value of [number={number}] must be an integer"
raise TypeError(a_)
if number < 1:
raise ValueError('''Input ... | 49 | 0 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
logging.b... | 708 | import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
... | 49 | 0 |
import mpmath # for roots of unity
import numpy as np
class _lowerCAmelCase :
def __init__( self : Union[str, Any] , __snake_case : Optional[Any]=None , __snake_case : Optional[int]=None ):
# Input as list
lowerCamelCase :Optional[i... | 709 | def _lowerCamelCase ( a_ : int = 4_00_00_00):
lowerCamelCase :Dict = [0, 1]
lowerCamelCase :Optional[Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1])
if fib[i + 2] > n:
break
i += 1
lowerCamelCase :Dict = ... | 49 | 0 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class _lowerCAmelCase ( pl.LightningModule ):
def __init__( self : Union[str, Any] , __snake_case : Any ):
s... | 710 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A__ = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
if not is_torch_available(... | 49 | 0 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _lowerCamelCase ( a_ : int):
lowerCamelCase :List[str] = int(number**0.5)
return number == sq * sq
def _lowerCamelCase ( a_ : int , a_ : int ... | 711 | import numpy
class _lowerCAmelCase :
def __init__( self : Dict , __snake_case : numpy.ndarray , __snake_case : numpy.ndarray ):
lowerCamelCase :Dict = input_array
# Random initial weights are assigned where first argument... | 49 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
A__ = {
"configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}
try:
if not is_torch_available():
raise Optional... | 712 | def _lowerCamelCase ( a_ : str , a_ : str):
lowerCamelCase :List[str] = len(a_)
lowerCamelCase :List[str] = len(a_)
lowerCamelCase :int = [[False for _ in range(m + 1)] for _ in range(n + 1)]
lowerCamelCase :Optional[Any] = ... | 49 | 0 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
A__ = {
"""susnato/ernie-m-base_pytorch""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json""",
"""susnato/ernie-m-large_pytorch""": """https:/... | 713 | import inspect
import unittest
from transformers import YolosConfig
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_configuration_common import ConfigTester
from ...tes... | 49 | 0 |
import random
def _lowerCAmelCase ( a_ : List[str] , a_ : str , a_ : str):
lowerCamelCase :Dict = a[left_index]
lowerCamelCase :Union[str, Any] = left_index + 1
for j in range(left_index + 1 , UpperCamelCase__):
if a[j] <... | 714 | import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils import p... | 49 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json... | 715 | import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
_UpperCAmelCase = ''
_UpperCAmelCase = (
None # p... | 49 | 0 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
A__ = version.parse(version.parse(torch.__ve... | 716 | import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...t... | 49 | 0 |
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_image_inputs
if is_torch_avai... | 717 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A__ = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Layo... | 49 | 0 |
from __future__ import annotations
from typing import TypedDict
class _lowerCAmelCase ( __snake_case ):
_UpperCAmelCase = 4_2
_UpperCAmelCase = 4_2
def _lowerCamelCase ( a_ : str):
if not isinstance(_lowerCamelCase , _lowerCamelCase):
rai... | 718 | import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is... | 49 | 0 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between c... | 719 | import operator as op
def _lowerCamelCase ( a_ : Tuple):
lowerCamelCase :int = []
lowerCamelCase :List[str] = lambda a_ , a_: int(x / y) # noqa: E731 integer division operation
lowerCamelCase :Optional[int] = {
'''^''': op.... | 49 | 0 |
from __future__ import annotations
from collections.abc import Generator
def _lowerCamelCase ( ):
lowerCamelCase :Optional[Any] = {}
lowerCamelCase :Optional[int] = 2
while True:
lowerCamelCase :Optional[Any] = factor_map.pop(lowerC... | 720 | import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fai... | 49 | 0 |
from __future__ import annotations
import math
def _lowerCamelCase ( a_ : int):
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 not primes
... | 721 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""andreasmadsen/efficient_mlm_m0.40""": (
... | 49 | 0 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def _lowerCamelCase ( a_ : str):
lowerCamelCase :Optional[Any] = args.pruning_method
lowerCamelCase :List[Any] = args... | 700 | import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase... | 49 | 0 |
import argparse
from collections import defaultdict
import yaml
A__ = """docs/source/en/_toctree.yml"""
def _lowerCamelCase ( a_ : List[Any]):
lowerCamelCase :str = defaultdict(SCREAMING_SNAKE_CASE_)
for doc in model_doc:
counts[doc["local"]] += 1
lowerCa... | 701 | import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import wr... | 49 | 0 |
from math import pi
def _lowerCamelCase ( a_ : int , a_ : int):
return 2 * pi * radius * (angle / 3_60)
if __name__ == "__main__":
print(arc_length(90, 10))
| 702 | import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_... | 49 | 0 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.mode... | 703 | import os
from math import logaa
def _lowerCamelCase ( a_ : str = "base_exp.txt"):
lowerCamelCase :float = 0
lowerCamelCase :Optional[int] = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(a_) , a_))):
lowerCamelCase , lowe... | 49 | 0 |
'''simple docstring'''
def _lowerCamelCase ( a_ : Optional[int] , a_ : Optional[Any]):
return abs(__snake_case) if a == 0 else greatest_common_divisor(b % a , __snake_case)
def _lowerCamelCase ( a_ : int , a_ : Dict):
while y: # --> when y=0 ... | 704 | def _lowerCamelCase ( a_ : list):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''')
for cell_n in range(1 , len(grid[0])):
grid[0][cell_n] += grid[0][cell_n - 1]
lowerCamelCase :Any = grid[0]
for ... | 49 | 0 |
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 accelerate im... | 705 | import math
def _lowerCamelCase ( a_ : int):
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 not primes
return False
# All primes number... | 49 | 0 |
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_modeling_common import... | 706 | import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_av... | 49 | 0 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
_UpperCAmelCase = ''
_UpperCAmelCase = (
None # p... | 707 | from maths.prime_factors import prime_factors
def _lowerCamelCase ( a_ : int):
if not isinstance(a_ , a_):
lowerCamelCase :Tuple = F"Input value of [number={number}] must be an integer"
raise TypeError(a_)
if number < 1:
raise ValueError('''Input ... | 49 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A__ = {'configuration_reformer': ['REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ReformerConfig']}
try:
i... | 708 | import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
... | 49 | 0 |
from __future__ import annotations
from collections import Counter
from random import random
class _lowerCAmelCase :
def __init__( self : Optional[int] ):
lowerCamelCase :str = {}
def snake_case ( self : Dict , ... | 709 | def _lowerCamelCase ( a_ : int = 4_00_00_00):
lowerCamelCase :Dict = [0, 1]
lowerCamelCase :Optional[Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1])
if fib[i + 2] > n:
break
i += 1
lowerCamelCase :Dict = ... | 49 | 0 |
import os
from datetime import datetime as dt
from github import Github
A__ = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''enhancement''',
'''new pipeline/model''',
'''new scheduler''',
'''wip''',
]
def _lowerCamelCase ( ):
... | 710 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A__ = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
if not is_torch_available(... | 49 | 0 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from tr... | 711 | import numpy
class _lowerCAmelCase :
def __init__( self : Dict , __snake_case : numpy.ndarray , __snake_case : numpy.ndarray ):
lowerCamelCase :Dict = input_array
# Random initial weights are assigned where first argument... | 49 | 0 |
from math import factorial
class _lowerCAmelCase :
def __init__( self : Dict , __snake_case : str , __snake_case : int ):
lowerCamelCase :Optional[Any] = real
if isinstance(lowerCamelCase_ , lowerCamelCase_ ):
lowerC... | 712 | def _lowerCamelCase ( a_ : str , a_ : str):
lowerCamelCase :List[str] = len(a_)
lowerCamelCase :List[str] = len(a_)
lowerCamelCase :int = [[False for _ in range(m + 1)] for _ in range(n + 1)]
lowerCamelCase :Optional[Any] = ... | 49 | 0 |
def _lowerCamelCase ( a_ : float):
return 10 - x * x
def _lowerCamelCase ( a_ : float , a_ : float):
if equation(A__) * equation(A__) >= 0:
raise ValueError('''Wrong space!''')
lowerCamelCase :int = a
while (b - a) >= 0.01:
#... | 713 | import inspect
import unittest
from transformers import YolosConfig
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_configuration_common import ConfigTester
from ...tes... | 49 | 0 |
from math import isqrt
def _lowerCAmelCase ( a_ : Any):
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCamelCase__) + 1))
def _lowerCAmelCase ( a_ : List[Any] = 10**6):
lowerCamelCase :Dict = 0
lowerCamelCase :Tuple ... | 714 | import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils import p... | 49 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A__ = {
"""configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConfig"""],
}
try:
... | 715 | import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
_UpperCAmelCase = ''
_UpperCAmelCase = (
None # p... | 49 | 0 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_util... | 716 | import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...t... | 49 | 0 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as P... | 717 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A__ = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Layo... | 49 | 0 |
def _lowerCamelCase ( a_ : Tuple = 1_00):
lowerCamelCase :List[str] = set()
lowerCamelCase :Optional[Any] = 0
lowerCamelCase :Any = n + 1 # maximum limit
for a in range(2 , a_):
for b in range(2 , a_):
lowerCamelCase ... | 718 | import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is... | 49 | 0 |
import inspect
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_config_docstrings.py
A__ = """src/transformers"""
# This is to make sure the t... | 719 | import operator as op
def _lowerCamelCase ( a_ : Tuple):
lowerCamelCase :int = []
lowerCamelCase :List[str] = lambda a_ , a_: int(x / y) # noqa: E731 integer division operation
lowerCamelCase :Optional[int] = {
'''^''': op.... | 49 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.json""",
# See all Cvt models at https://huggingface.co/mo... | 720 | import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fai... | 49 | 0 |
from __future__ import annotations
def _lowerCamelCase ( a_ : list[int] , a_ : int):
lowerCamelCase :Optional[Any] = 0
lowerCamelCase :str = len(a_) - 1
while i < j:
if nums[i] + nums[j] == target:
return [i, j]
elif nu... | 721 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""andreasmadsen/efficient_mlm_m0.40""": (
... | 49 | 0 |
import re
import string
import numpy as np
import datasets
A__ = """
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
"""
A__ = """
Args:
predictions: List of predict... | 700 | import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase... | 49 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFeatureE... | 701 | import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import wr... | 49 | 0 |
from __future__ import annotations
def _lowerCamelCase ( a_ : Optional[Any] , a_ : Union[str, Any] = None , a_ : List[str] = None):
if start is None:
lowerCamelCase :Optional[int] = 0
if end is None:
lowerCamelCase :Tuple ... | 702 | import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_... | 49 | 0 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from... | 703 | import os
from math import logaa
def _lowerCamelCase ( a_ : str = "base_exp.txt"):
lowerCamelCase :float = 0
lowerCamelCase :Optional[int] = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(a_) , a_))):
lowerCamelCase , lowe... | 49 | 0 |
'''simple docstring'''
from __future__ import annotations
def _lowerCamelCase ( a_ : int):
if not nums:
raise ValueError('''List is empty''')
return sum(a_) / len(a_)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 704 | def _lowerCamelCase ( a_ : list):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''')
for cell_n in range(1 , len(grid[0])):
grid[0][cell_n] += grid[0][cell_n - 1]
lowerCamelCase :Any = grid[0]
for ... | 49 | 0 |
# 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 required... | 705 | import math
def _lowerCamelCase ( a_ : int):
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 not primes
return False
# All primes number... | 49 | 0 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch... | 706 | import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_av... | 49 | 0 |
def _lowerCamelCase ( a_ : int = 1_00):
lowerCamelCase :str = 0
lowerCamelCase :Optional[int] = 0
for i in range(1 , n + 1):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ == "__main__":
... | 707 | from maths.prime_factors import prime_factors
def _lowerCamelCase ( a_ : int):
if not isinstance(a_ , a_):
lowerCamelCase :Tuple = F"Input value of [number={number}] must be an integer"
raise TypeError(a_)
if number < 1:
raise ValueError('''Input ... | 49 | 0 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 708 | import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
... | 49 | 0 |
import math
def _lowerCamelCase ( a_ : List[str] , a_ : int):
lowerCamelCase :Any = len(a_)
lowerCamelCase :Tuple = int(math.floor(math.sqrt(a_)))
lowerCamelCase :Optional[int] = 0
while arr[min(a_ , a_) - 1] < x:
... | 709 | def _lowerCamelCase ( a_ : int = 4_00_00_00):
lowerCamelCase :Dict = [0, 1]
lowerCamelCase :Optional[Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1])
if fib[i + 2] > n:
break
i += 1
lowerCamelCase :Dict = ... | 49 | 0 |
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@require_sentencepiece
@require_tokenizers... | 710 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A__ = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
if not is_torch_available(... | 49 | 0 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . ... | 711 | import numpy
class _lowerCAmelCase :
def __init__( self : Dict , __snake_case : numpy.ndarray , __snake_case : numpy.ndarray ):
lowerCamelCase :Dict = input_array
# Random initial weights are assigned where first argument... | 49 | 0 |
def _lowerCamelCase ( a_ : int , a_ : int):
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''')
lowerCamelCase :Any = str(bin(a_))[2:] # remove the leading "0b"
lowerCamelCase :Optional[Any] = str(bin(a_))[2:] # remov... | 712 | def _lowerCamelCase ( a_ : str , a_ : str):
lowerCamelCase :List[str] = len(a_)
lowerCamelCase :List[str] = len(a_)
lowerCamelCase :int = [[False for _ in range(m + 1)] for _ in range(n + 1)]
lowerCamelCase :Optional[Any] = ... | 49 | 0 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from .... | 713 | import inspect
import unittest
from transformers import YolosConfig
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_configuration_common import ConfigTester
from ...tes... | 49 | 0 |
A__ = {
"""a""": """AAAAA""",
"""b""": """AAAAB""",
"""c""": """AAABA""",
"""d""": """AAABB""",
"""e""": """AABAA""",
"""f""": """AABAB""",
"""g""": """AABBA""",
"""h""": """AABBB""",
"""i""": """ABAAA""",
"""j""": """BBBAA""",
"""k""": """ABAAB""",... | 714 | import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils import p... | 49 | 0 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _lowerCamelCase ( a_ : str , a_ : int , a_ : List[str] , a_ : str=10_24):
lowerCamelCase , lowerCamelCase :Tuple ... | 715 | import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
_UpperCAmelCase = ''
_UpperCAmelCase = (
None # p... | 49 | 0 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenizati... | 716 | import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...t... | 49 | 0 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
A__ = "https://www.indeed.co.in/jobs?q=mobile+app+development&l="
def _lowerCamelCase ( a_ : str = "mumbai"):
lowerCamelCase :Optional[int] ... | 717 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A__ = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Layo... | 49 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.functional import Interpol... | 718 | import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is... | 49 | 0 |
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase ( lowercase_ , unittest.TestCase ):
_UpperCAmelCase = Transf... | 719 | import operator as op
def _lowerCamelCase ( a_ : Tuple):
lowerCamelCase :int = []
lowerCamelCase :List[str] = lambda a_ , a_: int(x / y) # noqa: E731 integer division operation
lowerCamelCase :Optional[int] = {
'''^''': op.... | 49 | 0 |
from __future__ import annotations
import requests
A__ = set(
"""approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories created_utc downs\... | 720 | import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fai... | 49 | 0 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def _lowerCamelCase ( a_ : List[Any]):
if "model" in orig_key:
lowerCamelCase :Dict = orig_key.replace('''model.''' , '''''')
if "norm1" in orig_key:
lowerCamelCase ... | 721 | from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""andreasmadsen/efficient_mlm_m0.40""": (
... | 49 | 0 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization... | 700 | import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase... | 49 | 0 |
A__ = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(100_000)]
def _lowerCamelCase ( a_ : int):
lowerCamelCase :str = 0
while number:
# Increased Speed Slightly by checking every 5 digits together.
sum_of_digits_squared += DIGITS_SQUARED[number... | 701 | import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import wr... | 49 | 0 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
A__ = False
try:
A__ = _is_packag... | 702 | import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_... | 49 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
... | 703 | import os
from math import logaa
def _lowerCamelCase ( a_ : str = "base_exp.txt"):
lowerCamelCase :float = 0
lowerCamelCase :Optional[int] = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(a_) , a_))):
lowerCamelCase , lowe... | 49 | 0 |
'''simple docstring'''
import numpy
class _lowerCAmelCase :
def __init__( self : Dict , __snake_case : numpy.ndarray , __snake_case : numpy.ndarray ):
lowerCamelCase :Dict = input_array
# Random initial weights... | 704 | def _lowerCamelCase ( a_ : list):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''')
for cell_n in range(1 , len(grid[0])):
grid[0][cell_n] += grid[0][cell_n - 1]
lowerCamelCase :Any = grid[0]
for ... | 49 | 0 |
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_common import Onn... | 705 | import math
def _lowerCamelCase ( a_ : int):
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 not primes
return False
# All primes number... | 49 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A__ = {
"""configuration_lxmert""": ["""LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LxmertConfig"""]... | 706 | import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_av... | 49 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class _lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
_Up... | 707 | from maths.prime_factors import prime_factors
def _lowerCamelCase ( a_ : int):
if not isinstance(a_ , a_):
lowerCamelCase :Tuple = F"Input value of [number={number}] must be an integer"
raise TypeError(a_)
if number < 1:
raise ValueError('''Input ... | 49 | 0 |
from collections import defaultdict
from math import gcd
def _lowerCamelCase ( a_ : int = 1_50_00_00):
lowerCamelCase :defaultdict = defaultdict(a_)
lowerCamelCase :Optional[Any] = 2
while 2 * euclid_m * (euclid_m + 1) <= limit:
for euclid_n in range((euclid... | 708 | import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
BitConfig,
... | 49 | 0 |
_UpperCamelCase = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_UpperCamelCase = [{"""type""": """code""", """content""": INSTALL_CONTENT}]
_U... | 709 | def _lowerCamelCase ( a_ : int = 4_00_00_00):
lowerCamelCase :Dict = [0, 1]
lowerCamelCase :Optional[Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1])
if fib[i + 2] > n:
break
i += 1
lowerCamelCase :Dict = ... | 49 | 0 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
if... | 710 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A__ = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""",
]
}
try:
if not is_torch_available(... | 49 | 0 |
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