code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import copy
import random
from transformers import CLIPTokenizer
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__(self, *lowerCamelCase_, **lowerCamelCase_ ):
'''simple docstring'''
super().__init__(*lowerCamelCase_,... | 316 |
"""simple docstring"""
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Tuple = len(lowerCamelCase_ )
lowerCamelCase__ : Any = [0] * len_array
... | 316 | 1 |
"""simple docstring"""
import re
def lowerCamelCase_ ( _lowerCamelCase ):
if len(re.findall('[ATCG]' , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' , 'TAGC' ) )
if __name... | 316 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : Dict = ['image_processor', 'tokenizer']
lowerCamelCase__... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('One and only one argument must be 0' ... | 316 |
"""simple docstring"""
import cva
import numpy as np
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowerCamelCase_ ):
'''simple docstring'''
if k in (0.04, 0.06):
lowerCamelCase__ : Tuple = k
lower... | 316 | 1 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , ):
lowerCamelCase__ , lowerCamelCase__ : Union[str, Any] =... | 316 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
A_ : str = TypeVar("KEY")
A_ : List[Any] = TypeVar("VAL")
@dataclass(frozen=snake_case_ , slots=snake_case_ )
class a_ (... | 316 | 1 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
A_ : Union[str, Any] = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < ve... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( ):
lowerCamelCase__ : Optional[Any] = []
lowerCamelCase__ : List[Any] = 1
while len(_lowerCamelCase ) < 1e6:
constant.append(str(_lowerCamelCase ) )
i += 1
lowerCamelCase__ : str = ... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
return int((input_a, input_a).count(0 ) == 0 )
def lowerCamelCase_ ( ):
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , ... | 316 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
A_ : Union[str, Any] = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < ve... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_config... | 316 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
A_ : str = ... | 316 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_i... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = []
lowerCamelCase__ : List[str] = []
lowerCamelCase__ : Tuple = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
import queue
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Union[str, Any] = data
lowerCamelCase__ : ... | 316 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
fro... | 316 | 1 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Optional[Any] = [
'encoder.version',
'decoder.version',
... | 316 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : list[list[int]] = []
lowerCamelCase__ : list[int] = []
lowerCamelCase__ : List[str] = ... | 316 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A_ : List[str] = logging.get_logger(__name__)
A_ : ... | 316 |
"""simple docstring"""
from __future__ import annotations
import queue
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Union[str, Any] = data
lowerCamelCase__ : ... | 316 | 1 |
"""simple docstring"""
from math import pi, sqrt
def lowerCamelCase_ ( _lowerCamelCase ):
if num <= 0:
raise ValueError('math domain error' )
if num > 171.5:
raise OverflowError('math range error' )
elif num - int(_lowerCamelCase ) not in (0, 0.5):
raise NotImplementedError('num... | 316 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# -... | 316 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class a_ ( snake_case_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def a__ (lowerCamelCase_ ):
'''simple docstring'''
raise NotImp... | 316 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class a_ ( snake_case_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def a__ (lowerCamelCase_ ):
'''simple docstring'''
raise NotImp... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : str = word.split()
def justify(_lowerCamelCase , _lowerCamelCase , _lowerCamelCase ) -> str:
lowerCamelCase__ : Optional[Any] ... | 316 |
"""simple docstring"""
import re
def lowerCamelCase_ ( _lowerCamelCase ):
if len(re.findall('[ATCG]' , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' , 'TAGC' ) )
if __name... | 316 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokeni... | 316 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Any ... | 316 | 1 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : List[Any] = (UnCLIPScheduler,)
def a__ (self, **low... | 316 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
if not arr:
return Non... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
while second != 0:
lowerCamelCase__ : Tuple = first & second
first ^= second
lowerCamelCase__ : int = c << 1
return first
if __name__ == "__main__":
i... | 316 | 1 |
"""simple docstring"""
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
... | 316 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : List[str] = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
if n... | 316 | 1 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class a_ ( unittest.TestCase , snake_case_ ):
'''simple docstring'''
def a__ (self ):
'''simple docstring'''
lowerCamelC... | 316 |
"""simple docstring"""
import numpy as np
def lowerCamelCase_ ( _lowerCamelCase ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 316 | 1 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
A_ : str = TypeVar("KEY")
A_ : List[Any] = TypeVar("VAL")
@dataclass(frozen=snake_case_ , slots=snake_case_ )
class a_ (... | 316 |
"""simple docstring"""
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
if a < 0:
raise ValueError('Input value must be a positive integer' )
elif isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError('Input value must be a \'int\' type' )
return bin(_lowerCamelCase ).co... | 316 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ : int = {
"configuration_clip": ... | 316 | 1 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
A_ : Optional[int] = {
"<": operator.lt,
"<=": operator.le,
"==": operator.eq,
"!=": operator.ne,
">=": operator.ge,
">": opera... | 316 |
"""simple docstring"""
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config impo... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 316 |
"""simple docstring"""
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Tuple = len(lowerCamelCase_ )
lowerCamelCase__ : Any = [0] * len_array
... | 316 | 1 |
"""simple docstring"""
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes -... | 316 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : Dict = ['image_processor', 'tokenizer']
lowerCamelCase__... | 316 | 1 |
"""simple docstring"""
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def lowerCamelCase_ ... | 316 |
"""simple docstring"""
import cva
import numpy as np
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowerCamelCase_ ):
'''simple docstring'''
if k in (0.04, 0.06):
lowerCamelCase__ : Tuple = k
lower... | 316 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from datasets import load_dataset
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, pr... | 316 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
A_ : str = TypeVar("KEY")
A_ : List[Any] = TypeVar("VAL")
@dataclass(frozen=snake_case_ , slots=snake_case_ )
class a_ (... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
if len(_lowerCamelCase ) == 0:
return False
lowerCamelCase__ : Union[str, Any] = len(_lowerCamelCase ) // 2
if a_list[midpoint] == item:... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( ):
lowerCamelCase__ : Optional[Any] = []
lowerCamelCase__ : List[Any] = 1
while len(_lowerCamelCase ) < 1e6:
constant.append(str(_lowerCamelCase ) )
i += 1
lowerCamelCase__ : str = ... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Any = [1]
lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ : List[str] = 0, 0, 0
lowerCamelCase__ : Optional[Any] = ugly_nums[ia] ... | 316 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
A_ : Union[str, Any] = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < ve... | 316 | 1 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 316 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
A_ : str = ... | 316 | 1 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils ... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = []
lowerCamelCase__ : List[str] = []
lowerCamelCase__ : Tuple = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
print('\nThe shortest path matrix using Floyd Warshall algorithm\n' )
for i in range(_lowerCamelCase ):
for j in range(_lowerCamelCase ):
if dist[i][j] != float('inf' ):
print(int(dist[i]... | 316 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
fro... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Tuple = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation... | 316 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : list[list[int]] = []
lowerCamelCase__ : list[int] = []
lowerCamelCase__ : List[str] = ... | 316 | 1 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_de... | 316 |
"""simple docstring"""
from __future__ import annotations
import queue
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Union[str, Any] = data
lowerCamelCase__ : ... | 316 | 1 |
"""simple docstring"""
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 316 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# -... | 316 | 1 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
... | 316 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class a_ ( snake_case_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def a__ (lowerCamelCase_ ):
'''simple docstring'''
raise NotImp... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
if len(_lowerCamelCase ) != 2 or len(a[0] ) != 2 or len(_lowerCamelCase ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' ... | 316 |
"""simple docstring"""
import re
def lowerCamelCase_ ( _lowerCamelCase ):
if len(re.findall('[ATCG]' , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' , 'TAGC' ) )
if __name... | 316 | 1 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
A_ : Dict = logging.get_logger(__name__)
A_ : List[str] = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/blob/... | 316 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Any ... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Tuple = 2
lowerCamelCase__ : List[str] = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_lowerCamel... | 316 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 316 | 1 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=l... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
while second != 0:
lowerCamelCase__ : Tuple = first & second
first ^= second
lowerCamelCase__ : int = c << 1
return first
if __name__ == "__main__":
i... | 316 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ : Optional[int] = {
"configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
"tokenization_luke": ["LukeTokenizer"],
}
try:... | 316 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : List[str] = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
if n... | 316 | 1 |
"""simple docstring"""
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def lowerCamelCase_ ( _lowerCamelCase ): # picklable for ... | 316 |
"""simple docstring"""
import numpy as np
def lowerCamelCase_ ( _lowerCamelCase ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 316 | 1 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_module... | 316 |
"""simple docstring"""
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase = 100_0000 ):
lowerCamelCase__ : Optional[int] = 1
lowerCamelCase__ : List[Any] = 1
lowerCamelCase__ : List[Any] = {1: 1}
for inputa in range(2 , _lowerCamelCas... | 316 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ : int = {
"configuration_clip": ... | 316 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelC... | 316 |
"""simple docstring"""
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config impo... | 316 | 1 |
"""simple docstring"""
from collections import deque
from math import floor
from random import random
from time import time
class a_ :
'''simple docstring'''
def __init__(self ):
'''simple docstring'''
lowerCamelCase__ : Optional[int] = {}
... | 316 |
"""simple docstring"""
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Tuple = len(lowerCamelCase_ )
lowerCamelCase__ : Any = [0] * len_array
... | 316 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import ... | 316 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : Dict = ['image_processor', 'tokenizer']
lowerCamelCase__... | 316 | 1 |
"""simple docstring"""
class a_ :
'''simple docstring'''
def __init__(self ):
'''simple docstring'''
lowerCamelCase__ : int = 0
lowerCamelCase__ : List[str] = 0
lowerCamelCase__ : Optional[Any] =... | 316 |
"""simple docstring"""
import cva
import numpy as np
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowerCamelCase_ ):
'''simple docstring'''
if k in (0.04, 0.06):
lowerCamelCase__ : Tuple = k
lower... | 316 | 1 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# -... | 316 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
A_ : str = TypeVar("KEY")
A_ : List[Any] = TypeVar("VAL")
@dataclass(frozen=snake_case_ , slots=snake_case_ )
class a_ (... | 316 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : List[str] = logging.get_logger(__name__)
A_ : Union[str, Any] = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json",... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( ):
lowerCamelCase__ : Optional[Any] = []
lowerCamelCase__ : List[Any] = 1
while len(_lowerCamelCase ) < 1e6:
constant.append(str(_lowerCamelCase ) )
i += 1
lowerCamelCase__ : str = ... | 316 | 1 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A_ : List[Any] = logging.get_logger(__n... | 316 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
A_ : Union[str, Any] = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < ve... | 316 | 1 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
A_ : str = ... | 316 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
A_ : str = ... | 316 | 1 |
"""simple docstring"""
from math import isqrt, loga
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : List[Any] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , _lowerCam... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = []
lowerCamelCase__ : List[str] = []
lowerCamelCase__ : Tuple = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
... | 316 | 1 |
"""simple docstring"""
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CO... | 316 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
fro... | 316 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, w... | 316 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : list[list[int]] = []
lowerCamelCase__ : list[int] = []
lowerCamelCase__ : List[str] = ... | 316 | 1 |
"""simple docstring"""
from collections import namedtuple
import requests
from lxml import html # type: ignore
A_ : int = namedtuple("covid_data", "cases deaths recovered")
def lowerCamelCase_ ( _lowerCamelCase = "https://www.worldometers.info/coronavirus/" ):
lowerCamelCase__ ... | 316 |
"""simple docstring"""
from __future__ import annotations
import queue
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Union[str, Any] = data
lowerCamelCase__ : ... | 316 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import Patchi... | 316 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# -... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
8: [5, 7],
},
{
0: [6],
... | 316 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class a_ ( snake_case_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def a__ (lowerCamelCase_ ):
'''simple docstring'''
raise NotImp... | 316 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
A_ : Optional[int] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDepende... | 316 |
"""simple docstring"""
import re
def lowerCamelCase_ ( _lowerCamelCase ):
if len(re.findall('[ATCG]' , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' , 'TAGC' ) )
if __name... | 316 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class a_ ( unittest.TestCase ):
... | 316 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Any ... | 316 | 1 |
"""simple docstring"""
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 (
... | 316 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 316 | 1 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
A_ : Any = 3
def lowerCamelCase_ ( _lowerCamelCase ):
print('Generating primitive root of p' )
while True:
lowerCamelCase__ : str ... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
while second != 0:
lowerCamelCase__ : Tuple = first & second
first ^= second
lowerCamelCase__ : int = c << 1
return first
if __name__ == "__main__":
i... | 316 | 1 |
"""simple docstring"""
A_ : dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609344,
"knot": 1.852,
}
A_ : dict[str, float] = {
"km/h": 1.0,
"m/s": 0.277777778,
"mph": 0.621371192,
"knot": 0.539956803,
}
def lowerCamelCase_ ( _lowe... | 316 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : List[str] = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
if n... | 316 | 1 |
"""simple docstring"""
import functools
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
# Validation
if not isinstance(_lowerCamelCase , _lowerCamelCase ) or not all(isinstance(_lowerCamelCase , _lowerCamelCase ) for day in days ):
raise V... | 316 |
"""simple docstring"""
import numpy as np
def lowerCamelCase_ ( _lowerCamelCase ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 316 | 1 |
"""simple docstring"""
from __future__ import annotations
import bisect
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase = 0 , _lowerCamelCase = -1 ):
if hi < 0:
lowerCamelCase__ : str = len(_lowerCamelCase )
... | 316 |
"""simple docstring"""
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 316 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax... | 316 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ : int = {
"configuration_clip": ... | 316 | 1 |
"""simple docstring"""
A_ : int = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase... | 316 |
"""simple docstring"""
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config impo... | 316 | 1 |
"""simple docstring"""
A_ : List[Any] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Tuple = 0
while number:
# Increased Speed Slightly by checking every 5 digits together.... | 316 |
"""simple docstring"""
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Tuple = len(lowerCamelCase_ )
lowerCamelCase__ : Any = [0] * len_array
... | 316 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_chan... | 316 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : Dict = ['image_processor', 'tokenizer']
lowerCamelCase__... | 316 | 1 |
"""simple docstring"""
A_ : Optional[Any] = "Input must be a string of 8 numbers plus letter"
A_ : str = "TRWAGMYFPDXBNJZSQVHLCKE"
def lowerCamelCase_ ( _lowerCamelCase ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ :... | 316 |
"""simple docstring"""
import cva
import numpy as np
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowerCamelCase_ ):
'''simple docstring'''
if k in (0.04, 0.06):
lowerCamelCase__ : Tuple = k
lower... | 316 | 1 |
"""simple docstring"""
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_... | 316 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
A_ : str = TypeVar("KEY")
A_ : List[Any] = TypeVar("VAL")
@dataclass(frozen=snake_case_ , slots=snake_case_ )
class a_ (... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
A_ : Tuple = [8, 5, 9, 7]
A_ : Any = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
A_ : List[Any] = [
[3, 2, 1, 4],
[0, ... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( ):
lowerCamelCase__ : Optional[Any] = []
lowerCamelCase__ : List[Any] = 1
while len(_lowerCamelCase ) < 1e6:
constant.append(str(_lowerCamelCase ) )
i += 1
lowerCamelCase__ : str = ... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
return int(input_a == input_a == 0 )
def lowerCamelCase_ ( ):
print('Truth Table of NOR Gate:' )
print('| Input 1 | Input 2 | Output |' )
print(f'''| 0 | 0 | {... | 316 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
A_ : Union[str, Any] = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < ve... | 316 | 1 |
"""simple docstring"""
import string
from math import logaa
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : List[Any] = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' ... | 316 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
A_ : str = ... | 316 | 1 |
"""simple docstring"""
from functools import reduce
A_ : Dict = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = []
lowerCamelCase__ : List[str] = []
lowerCamelCase__ : Tuple = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
... | 316 | 1 |
"""simple docstring"""
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('socket.socket' )
@patch('builtins.open' )
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
# ===== initialization =====
lowerCamelCase__ : Opti... | 316 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
fro... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : list[list[str]] = [[] for _ in range(_lowerCamelCase )]
lowerCamelCase__ : List[str] = key - 1
if key <= 0:
raise ValueError('Height of gr... | 316 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : list[list[int]] = []
lowerCamelCase__ : list[int] = []
lowerCamelCase__ : List[str] = ... | 316 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, log... | 316 |
"""simple docstring"""
from __future__ import annotations
import queue
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Union[str, Any] = data
lowerCamelCase__ : ... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
lowerCamelCase__ : int = 1
lowerCamelCase__ : str = 1
while repunit:
lowerCamelCase__ : Optional[int] = (10 * repun... | 316 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# -... | 316 | 1 |
"""simple docstring"""
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 Co... | 316 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class a_ ( snake_case_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def a__ (lowerCamelCase_ ):
'''simple docstring'''
raise NotImp... | 316 | 1 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_ima... | 316 |
"""simple docstring"""
import re
def lowerCamelCase_ ( _lowerCamelCase ):
if len(re.findall('[ATCG]' , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' , 'TAGC' ) )
if __name... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase = 100_0000 ):
lowerCamelCase__ : List[Any] = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , _lower... | 316 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : Any ... | 316 | 1 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class a_ :
'''simple docstring'''
def __init__(self ):
'''simple docstring'''
lowerCamelCase__ : int = ''
lowerCamelCase__ ... | 316 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 316 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
A_ : Union[str, Any] = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def lo... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
while second != 0:
lowerCamelCase__ : Tuple = first & second
first ^= second
lowerCamelCase__ : int = c << 1
return first
if __name__ == "__main__":
i... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
while second != 0:
lowerCamelCase__ : Tuple = first & second
first ^= second
lowerCamelCase__ : int = c << 1
return first
if __name__ == "__main__":
i... | 316 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : List[str] = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
if n... | 316 | 1 |
"""simple docstring"""
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 316 |
"""simple docstring"""
import numpy as np
def lowerCamelCase_ ( _lowerCamelCase ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 316 | 1 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
fro... | 316 |
"""simple docstring"""
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 316 | 1 |
"""simple docstring"""
class a_ : # Public class to implement a graph
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowerCamelCase_, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Dict = row
lowerCamel... | 316 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A_ : int = {
"configuration_clip": ... | 316 | 1 |
"""simple docstring"""
def lowerCamelCase_ ( ):
lowerCamelCase__ : Optional[Any] = []
lowerCamelCase__ : List[Any] = 1
while len(_lowerCamelCase ) < 1e6:
constant.append(str(_lowerCamelCase ) )
i += 1
lowerCamelCase__ : str = ... | 316 |
"""simple docstring"""
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config impo... | 316 | 1 |
"""simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_tru... | 316 |
"""simple docstring"""
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Tuple = len(lowerCamelCase_ )
lowerCamelCase__ : Any = [0] * len_array
... | 316 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ : List[str] = {"configuration_encoder_decoder": ["EncoderDecoderConfig"]}
try:
if n... | 316 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( snake_case_ ):
'''simple docstring'''
lowerCamelCase__ : Dict = ['image_processor', 'tokenizer']
lowerCamelCase__... | 316 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTMSNConfig
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 C... | 316 |
"""simple docstring"""
import cva
import numpy as np
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_, lowerCamelCase_ ):
'''simple docstring'''
if k in (0.04, 0.06):
lowerCamelCase__ : Tuple = k
lower... | 316 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : str = {
"YituTech/conv-ber... | 316 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
A_ : str = TypeVar("KEY")
A_ : List[Any] = TypeVar("VAL")
@dataclass(frozen=snake_case_ , slots=snake_case_ )
class a_ (... | 316 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : list[list[int]] = []
lowerCamelCase__ : list[int] = []
lowerCamelCase__ : List[str] = ... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( ):
lowerCamelCase__ : Optional[Any] = []
lowerCamelCase__ : List[Any] = 1
while len(_lowerCamelCase ) < 1e6:
constant.append(str(_lowerCamelCase ) )
i += 1
lowerCamelCase__ : str = ... | 316 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ : List[Any] = logging.get_logger(__name__)
A_ : List[Any] = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
"st... | 316 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
A_ : Union[str, Any] = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < ve... | 316 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(snake_case_ ... | 316 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
A_ : str = ... | 316 | 1 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class a_ ( snake_case_ ):
... | 316 |
"""simple docstring"""
def lowerCamelCase_ ( _lowerCamelCase ):
lowerCamelCase__ : Union[str, Any] = []
lowerCamelCase__ : List[str] = []
lowerCamelCase__ : Tuple = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
... | 316 | 1 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class a_ ( unittest.TestCase ):
'''simple docstring'''
def a__ (self ):
'''simple docstring'''
lowerCamelCase__ : int =... | 316 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
fro... | 316 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
A_ : Optional[Any] = logging.get_logger(__name__)
class a_ ( snake_case_ ):
'''simple docstring'''
def __init__(self, *lowerCam... | 316 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : list[list[int]] = []
lowerCamelCase__ : list[int] = []
lowerCamelCase__ : List[str] = ... | 316 | 1 |
"""simple docstring"""
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def lowerCamelCase_ ( _lowerCamelCase ):
return 1 / (1 + np.exp(-z ))
def lowerC... | 316 |
"""simple docstring"""
from __future__ import annotations
import queue
class a_ :
'''simple docstring'''
def __init__(self, lowerCamelCase_ ):
'''simple docstring'''
lowerCamelCase__ : Union[str, Any] = data
lowerCamelCase__ : ... | 316 | 1 |
"""simple docstring"""
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 ... | 316 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# -... | 316 | 1 |
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