code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import argparse
import os
import re
import packaging.version
SCREAMING_SNAKE_CASE : int = "examples/"
SCREAMING_SNAKE_CASE : Dict = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"... | 635 | import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDatase... | 635 | 1 |
from collections import defaultdict
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : int ):
UpperCamelCase_ : Optional[int] = 1
UpperCamelCase_ : Optional[Any] = True
for v in tree[start]:
if v not in visited:
ret += dfs(_... | 635 | import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 635 | 1 |
SCREAMING_SNAKE_CASE : Optional[Any] = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : dict , _SCREAMING_SNAKE_CASE ... | 635 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
... | 635 | 1 |
import numpy as np
import datasets
SCREAMING_SNAKE_CASE : Optional[int] = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt ... | 635 | from __future__ import annotations
SCREAMING_SNAKE_CASE : Tuple = 1.6_021E-19 # units = C
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (conductivity, electron_conc, mobilit... | 635 | 1 |
from __future__ import annotations
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supp... | 635 | from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_avail... | 635 | 1 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : dict ):
... | 635 | from __future__ import annotations
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supp... | 635 | 1 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
SCREAMING_SNAKE_CASE : List[Any] = "http://www.m... | 635 | from heapq import heappop, heappush
import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.ndarray , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : bool , ):
UpperCamelCase_,UpperCame... | 635 | 1 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diffusio... | 635 | import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Tuple = {
"facebook/encodec_24khz": "htt... | 635 | 1 |
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_channel_dimension_forma... | 635 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE : Union[str, Any] = {
"configuration_bridgetower": [
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BridgeTowerConfig... | 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE : Dict = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechCo... | 635 | import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCAmelCase_ ( ):
print("""Making key files...""" )
make_key_files("""rsa""" , 1024 )
print("""Key files gene... | 635 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required... | 635 | from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE : Union[str, Any] = {"UserAgent": UserAgent().random}
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Dict ):
... | 635 | 1 |
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[int] = logging.get_logger(__name__)
class UpperCamelCase ( __a ):
a__... | 635 | import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diffusio... | 635 | 1 |
import numpy as np
SCREAMING_SNAKE_CASE : List[Any] = [
["a", "b", "c", "d", "e"],
["f", "g", "h", "i", "k"],
["l", "m", "n", "o", "p"],
["q", "r", "s", "t", "u"],
["v", "w", "x", "y", "z"],
]
class UpperCamelCase :
def __init__(self ) ->... | 635 | import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType,... | 635 | 1 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_sco... | 635 | from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from... | 635 | 1 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : int = 1000 ):
UpperCamelCase_,UpperCamelCase_ : Optional[int] = 1, 1
UpperCamelCase_ : Optional[int] = []
for i in range(1 , n + 1 ):
UpperCamelCase_ : List[str] = prev_numerator + 2 * prev_den... | 635 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, req... | 635 | 1 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class UpperCamelCase ( __a ):
a__ :Optional[int] = ''''''
a__ :str = (
None # protocol passed in prefi... | 635 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_C... | 635 | 1 |
from collections import namedtuple
SCREAMING_SNAKE_CASE : int = namedtuple("from_to", "from_ to")
SCREAMING_SNAKE_CASE : str = {
"cubicmeter": from_to(1, 1),
"litre": from_to(0.001, 1000),
"kilolitre": from_to(1, 1),
"gallon": from_to(0.00454, 264.172),
"cubicyar... | 635 | import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class UpperCamelCase ( unittes... | 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE : List[Any] = {
"configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"],
"tokenization_canine": ["Ca... | 635 | import numpy as np
import datasets
SCREAMING_SNAKE_CASE : Optional[int] = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt ... | 635 | 1 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
class UpperCamelCase ( __a ):
def __init__(self , *__UpperCamelCase , **__Upp... | 635 | import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
SCREAMING_SNAKE_CASE : List[str] = False
class UpperCamelCase ( unittest.TestCase ):
... | 635 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Dict = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : int = {
"facebook/vit-mae-base": "https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json",
# See ... | 635 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Union[str, Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class Upp... | 635 | 1 |
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... | 635 | import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE : Tuple = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\n bookti... | 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE : List[Any] = {
"configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "... | 635 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__na... | 635 | 1 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : list[list] ):
UpperCamelCase_ : str = current_set.copy()
for row_index, row in enumerate(_SCREAMING_SNAKE_CASE ):
UpperCamelCase_ : Optional[Any] = row[0]
for column_index, column in enumerate(_SCR... | 635 | import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDatase... | 635 | 1 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, 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... | 635 | import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 635 | 1 |
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
SCREAMING_SNAKE_CASE : List[str] = 3
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : int ):
print("""Generating primitive root of p""" )
while Tru... | 635 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
... | 635 | 1 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
SCREAMING_SNAKE_CASE : List[str] = False
class UpperCamelCase ( unittest.TestCase ):
... | 635 | from __future__ import annotations
SCREAMING_SNAKE_CASE : Tuple = 1.6_021E-19 # units = C
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (conductivity, electron_conc, mobilit... | 635 | 1 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available():
from tran... | 635 | from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_avail... | 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE : Union[str, Any] = {
"configuration_roformer": ["ROFORMER... | 635 | from __future__ import annotations
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supp... | 635 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
SCREAMING_SNAKE_CASE : str = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : int = {
"speechbrain/m-ctc-t-large": "https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json",
... | 635 | from heapq import heappop, heappush
import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.ndarray , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : bool , ):
UpperCamelCase_,UpperCame... | 635 | 1 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer... | 635 | import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Tuple = {
"facebook/encodec_24khz": "htt... | 635 | 1 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
SCREAMING_SNAKE_CASE : Any = get_tests_dir("fixtures/test_sentencepiece_wit... | 635 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE : Union[str, Any] = {
"configuration_bridgetower": [
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BridgeTowerConfig... | 635 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Spl... | 635 | import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCAmelCase_ ( ):
print("""Making key files...""" )
make_key_files("""rsa""" , 1024 )
print("""Key files gene... | 635 | 1 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class UpperCamelCase (... | 635 | from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE : Union[str, Any] = {"UserAgent": UserAgent().random}
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Dict ):
... | 635 | 1 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
SCREAMING_SNAKE_CASE : Optional[Any] = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that... | 635 | import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diffusio... | 635 | 1 |
from manim import *
class UpperCamelCase ( __a ):
def A_ (self ) -> Union[str, Any]:
UpperCamelCase_ : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
UpperCamelCase_ : Union[str, Any] = Rectangle(h... | 635 | import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType,... | 635 | 1 |
from __future__ import annotations
SCREAMING_SNAKE_CASE : Optional[Any] = list[list[int]]
# assigning initial values to the grid
SCREAMING_SNAKE_CASE : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0... | 635 | from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from... | 635 | 1 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE : Union[str, Any] = {"UserAgent": UserAgent().random}
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Dict ):
... | 635 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, req... | 635 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer
SC... | 635 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_C... | 635 | 1 |
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 ...test_configuration_... | 635 | import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class UpperCamelCase ( unittes... | 635 | 1 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : list ):
UpperCamelCase_ : str = len(_SCREAMING_SNAKE_CASE )
for _ in range(_SCREAMING_SNAKE_CASE ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
Up... | 635 | import numpy as np
import datasets
SCREAMING_SNAKE_CASE : Optional[int] = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt ... | 635 | 1 |
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
SCREAMING_SNAKE_CASE : List[str] = {
"<": operator.lt,
"<=": operator.le,
"==": operator.eq,
"!=": operator.ne,
">=": operator.ge,
">": operator... | 635 | import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
SCREAMING_SNAKE_CASE : List[str] = False
class UpperCamelCase ( unittest.TestCase ):
... | 635 | 1 |
SCREAMING_SNAKE_CASE : Dict = 65521
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : str ):
UpperCamelCase_ : List[Any] = 1
UpperCamelCase_ : List[str] = 0
for plain_chr in plain_text:
UpperCamelCase_ : str = (a + ord(_... | 635 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Union[str, Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class Upp... | 635 | 1 |
from math import pow, sqrt
def lowerCAmelCase_ ( *_SCREAMING_SNAKE_CASE : float ):
UpperCamelCase_ : Optional[int] = len(_SCREAMING_SNAKE_CASE ) > 0 and all(value > 0.0 for value in values )
return result
def lowerCAmelCase_ ( _SCREAMING_SNAK... | 635 | import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE : Tuple = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\n bookti... | 635 | 1 |
import enum
import shutil
import sys
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : Any = shutil.get_terminal_size()
SCREAMING_SNAKE_CASE : Optional[Any] = {"UP": "A", "DOWN": "B", "RIGHT": "C", "LEFT": "D"}
class UpperCamelCase ( enum.Enum ):
a__ ... | 635 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__na... | 635 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class U... | 635 | import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDatase... | 635 | 1 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : int ):
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
raise TypeError("""only integers accepted as input""" )
else:
UpperCamelCase_ : Tuple = str(abs(_SCREAMING_SNAKE_CASE ) )
... | 635 | import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE : int = {
"configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
"tokenization_tapas": ["TapasTokenizer"],
}... | 635 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
... | 635 | 1 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
SCREAMING_SNAKE_CASE : Any = "\\n@misc{chen2021evaluating,\n title={Evaluat... | 635 | from __future__ import annotations
SCREAMING_SNAKE_CASE : Tuple = 1.6_021E-19 # units = C
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (conductivity, electron_conc, mobilit... | 635 | 1 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, ... | 635 | from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_avail... | 635 | 1 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common i... | 635 | from __future__ import annotations
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supp... | 635 | 1 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : list[list[int]] , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : list[int] ):
# 1. Validate that path exists between current and next vertices
if graph[path[curr_ind - 1]][next_ver... | 635 | from heapq import heappop, heappush
import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.ndarray , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : bool , ):
UpperCamelCase_,UpperCame... | 635 | 1 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.a... | 635 | import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Tuple = {
"facebook/encodec_24khz": "htt... | 635 | 1 |
import argparse
from collections import defaultdict
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : Optional[int] , _SCREAMING_SNAKE_CASE : Any )... | 635 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE : Union[str, Any] = {
"configuration_bridgetower": [
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BridgeTowerConfig... | 635 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Dict = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Optional[Any] = {
"Salesforce/blip-vqa-base": "https://huggingfac... | 635 | import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCAmelCase_ ( ):
print("""Making key files...""" )
make_key_files("""rsa""" , 1024 )
print("""Key files gene... | 635 | 1 |
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 --user <user> --host <host> --key_pa... | 635 | from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE : Union[str, Any] = {"UserAgent": UserAgent().random}
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Dict ):
... | 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE : Dict = {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_... | 635 | import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diffusio... | 635 | 1 |
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE : Tuple = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\n bookti... | 635 | import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType,... | 635 | 1 |
import inspect
import unittest
from transformers import MobileNetVaConfig
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 ... | 635 | from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from... | 635 | 1 |
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.schedulers.scheduling_... | 635 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, req... | 635 | 1 |
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : List[Any] ):
UpperCamelCase_ : Dict = test_file... | 635 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_C... | 635 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Optional[Any] = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See a... | 635 | import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class UpperCamelCase ( unittes... | 635 | 1 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
imp... | 635 | import numpy as np
import datasets
SCREAMING_SNAKE_CASE : Optional[int] = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt ... | 635 | 1 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testin... | 635 | import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
SCREAMING_SNAKE_CASE : List[str] = False
class UpperCamelCase ( unittest.TestCase ):
... | 635 | 1 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : str ):
UpperCamelCase_ : Any = 0
# if input_string is "aba" than new_input_string become "a|b|a"
UpperCamelCase_ : str = """"""
UpperCamelCase_ : List[Any] = """"""
# append each character + ... | 635 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Union[str, Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class Upp... | 635 | 1 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceClassificatio... | 635 | import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE : Tuple = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\n bookti... | 635 | 1 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : List... | 635 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__na... | 635 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_camembert ... | 635 | import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDatase... | 635 | 1 |
import qiskit
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int ):
UpperCamelCase_ : Optional[Any] = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
UpperCamelCase_ : ... | 635 | import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : Dict = {
"configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}
try:
if not is_torch_available():
raise OptionalDependenc... | 635 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
... | 635 | 1 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float ):
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0:
raise ValueError("""Impossible bulk modulus""" )
return (bulk_mo... | 635 | from __future__ import annotations
SCREAMING_SNAKE_CASE : Tuple = 1.6_021E-19 # units = C
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (conductivity, electron_conc, mobilit... | 635 | 1 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCamelCase ( unittest.TestCase ):
def A_ (self ) -> Tuple:
... | 635 | from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_avail... | 635 | 1 |
from __future__ import annotations
import os
from typing import Any
import requests
SCREAMING_SNAKE_CASE : Union[str, Any] = "https://api.github.com"
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
SCREAMING_SNAKE_CASE : List[Any] ... | 635 | from __future__ import annotations
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supp... | 635 | 1 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
SCREAMING_SNAKE_CASE : List[str] = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn": "attention.self",
... | 635 | from heapq import heappop, heappush
import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.ndarray , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : bool , ):
UpperCamelCase_,UpperCame... | 635 | 1 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : str ):
if len(_SCREAMING_SNAKE_CASE ) != len(_SCREAMING_SNAKE_CASE ):
raise ValueError("""String lengths must match!""" )
UpperCamelCase_ : List[str] = 0
for chara, c... | 635 | import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Tuple = {
"facebook/encodec_24khz": "htt... | 635 | 1 |
def lowerCAmelCase_ ( ):
UpperCamelCase_ : List[Any] = []
UpperCamelCase_ : Optional[Any] = 1
while len(_SCREAMING_SNAKE_CASE ) < 1E6:
constant.append(str(_SCREAMING_SNAKE_CASE ) )
i += 1
UpperCamelCase_ : List[str] = """... | 635 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE : Union[str, Any] = {
"configuration_bridgetower": [
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BridgeTowerConfig... | 635 | 1 |
import string
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : str ):
UpperCamelCase_ : Optional[int] = """"""
for i in sequence:
UpperCamelCase_ : Dict = ord(_SCREAMING_SNAKE_CASE )
if 65 <= extract <= 90:
output ... | 635 | import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCAmelCase_ ( ):
print("""Making key files...""" )
make_key_files("""rsa""" , 1024 )
print("""Key files gene... | 635 | 1 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
SCREAMING_SNAKE_CASE : Optional[Any] = "\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},... | 635 | from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE : Union[str, Any] = {"UserAgent": UserAgent().random}
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Dict ):
... | 635 | 1 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
SCREAMING_SNAKE_CASE : List[str] = "\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n ... | 635 | import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diffusio... | 635 | 1 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def... | 635 | import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType,... | 635 | 1 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
SCREAMING_SNAKE_CASE : Dict = TypeVar("T")
class UpperCamelCase ( Generic[T] ):
def __init__(self , __UpperCamelCase , __UpperCamelCase ... | 635 | from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from... | 635 | 1 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPM... | 635 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, req... | 635 | 1 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class UpperCamelCase ( unittes... | 635 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_C... | 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE : Tuple = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
"configuration_maskform... | 635 | import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class UpperCamelCase ( unittes... | 635 | 1 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
SCREAMING_SNAKE_CASE : Dict = Mapping[str, np.ndarray]
SCREAMING_SNAKE_CASE : int = Mapping[str, Any] #... | 635 | import numpy as np
import datasets
SCREAMING_SNAKE_CASE : Optional[int] = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\nIt ... | 635 | 1 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
SCREAMING_SNAKE_CASE : List[Any] = False
class UpperCamelCase ... | 635 | import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
SCREAMING_SNAKE_CASE : List[str] = False
class UpperCamelCase ( unittest.TestCase ):
... | 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : Tuple = {
"configuration_clipseg": [
"CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP",
"CLIPSegConfig",
"CLIPSegTextConfig",
"... | 635 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Union[str, Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class Upp... | 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : Optional[Any] = {"configuration_ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig", "IBertOnnxConfig"]}
try:
if not is_torch_available():
r... | 635 | import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE : Tuple = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\n bookti... | 635 | 1 |
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from torch.utils.data impo... | 635 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__na... | 635 | 1 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Tuple , _SCREAMING_SNAKE_CASE : List[Any] , _SC... | 635 | import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDatase... | 635 | 1 |
# 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_ ( _SCREAMING_SNAKE_CASE : str ):
return 1 / (1 + np.exp(-z ))
... | 635 | import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 635 | 1 |
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_modules import _PACKAGED_DA... | 635 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
... | 635 | 1 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDatase... | 635 | from __future__ import annotations
SCREAMING_SNAKE_CASE : Tuple = 1.6_021E-19 # units = C
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (conductivity, electron_conc, mobilit... | 635 | 1 |
import argparse
import os
import re
import packaging.version
SCREAMING_SNAKE_CASE : Optional[Any] = "examples/"
SCREAMING_SNAKE_CASE : List[Any] = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init":... | 635 | from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_avail... | 635 | 1 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch
... | 635 | from __future__ import annotations
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , _SCREAMING_SNAKE_CASE : float , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supp... | 635 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : Optional[Any] = {
"configuration_table_transformer": [
"TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TableTransformerConfig",
... | 635 | from heapq import heappop, heappush
import numpy as np
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : np.ndarray , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : tuple[int, int] , _SCREAMING_SNAKE_CASE : bool , ):
UpperCamelCase_,UpperCame... | 635 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from... | 635 | import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Union[str, Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Tuple = {
"facebook/encodec_24khz": "htt... | 635 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffusion.modeling_roberta_series imp... | 635 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE : Union[str, Any] = {
"configuration_bridgetower": [
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"BridgeTowerConfig... | 635 | 1 |
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.data import Dat... | 635 | import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCAmelCase_ ( ):
print("""Making key files...""" )
make_key_files("""rsa""" , 1024 )
print("""Key files gene... | 635 | 1 |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase ( __a )... | 635 | from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE : Union[str, Any] = {"UserAgent": UserAgent().random}
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Dict ):
... | 635 | 1 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
AutoCo... | 635 | import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diffusio... | 635 | 1 |
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