code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
a__ : Any = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerCo... | 349 |
'''simple docstring'''
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_ten... | 349 | 1 |
'''simple docstring'''
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowercase ( __A = "isbn/0140328726" ):
'''simple docstring'''
__UpperCamelCase = olid.strip().strip("""/""" ) # Rem... | 349 |
'''simple docstring'''
import pytest
a__ : List[str] = '__dummy_dataset1__'
a__ : Optional[int] = '\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"\nURLS = {"train": REPO_URL + "wikiann-bn-t... | 349 | 1 |
'''simple docstring'''
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
f... | 349 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaP... | 349 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import Auto... | 349 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 349 | 1 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def _lowercase ( ):
'''simple docstring'''
__UpperCamelCase = {
"""repo_name""": ["""... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowercase ( __A ,__A ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b ,2 ) for a, b in zip(__A ,__A ... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
import bisect
def _lowercase ( __A ,__A ,__A = 0 ,__A = -1 ):
'''simple docstring'''
if hi < 0:
__UpperCamelCase = len(__A )
while lo < hi:
__UpperCamelCase ... | 349 |
'''simple docstring'''
from datetime import datetime
import requests
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
__UpperCamelCase = requests.g... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A ):
'''simple docstring'''
if num <= 0:
raise ValueError("""Input must be a positive integer""" )
__UpperCamelCase = [True] * (num + 1)
__UpperCamelCase = 2
while p * p <= num:
if primes[p]:
fo... | 349 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from un... | 349 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
a__ : int = logging.getLo... | 349 |
'''simple docstring'''
import re
def _lowercase ( __A ):
'''simple docstring'''
return [char.split() for char in re.split(R"""[^ a-z A-Z 0-9 \s]""" ,str_ )]
def _lowercase ( __A ):
'''simple docstring'''
__Uppe... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A ,__A ):
'''simple docstring'''
__UpperCamelCase = len(__A )
print("""The following activities are selected:""" )
# The first activity is always selected
__UpperCamelCase = 0
print(__A ,en... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
fr... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class UpperCAmelCase__ :
__SCREAMING_SNAKE_CASE = 42
__SCREAMING_SNAKE_CASE = 42
class Uppe... | 349 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=UpperCAmelCase_):
__SCREAMING_SNAKE_CASE = ['''flax''']
def __init__( self , *lowercase , **lowercase ) -> List[Any]:
requires_backends(se... | 349 | 1 |
'''simple docstring'''
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_... | 349 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class UpperCAmelCase__ ( logging.LoggerAdapter):
@staticmethod
def __lowerCamelCase ( lowercase ) -> Dict:
__UpperCamelCase = PartialState()
return not main_process_... | 349 | 1 |
'''simple docstring'''
import random
def _lowercase ( __A ,__A ,__A ):
'''simple docstring'''
__UpperCamelCase = a[left_index]
__UpperCamelCase = left_index + 1
for j in range(left_index + 1 ,__A ):
if a[j] < pivot:
... | 349 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
a__ : Optional[Any] = logging.getLogger(__name__)
class UpperCAmelCase__ :
de... | 349 | 1 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCAmelCase__ ( nn.Module):
__SCREAMING_SNAKE_CASE = 42
__SCREAMING_S... | 349 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a__ : Optional[Any] =... | 349 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTex... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
a__ : str = {
'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_... | 349 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from to... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
a__ : Union[str, Any] = {
'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
... | 349 | 1 |
'''simple docstring'''
import argparse
import copy
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = {}
with open(__A ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
__UpperCamelCase = []... | 349 |
'''simple docstring'''
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 _lowercase ( __A ):
... | 349 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ : str = {
'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'],
}
try:
if not is_torch_available():
raise Op... | 349 |
'''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
fro... | 349 | 1 |
'''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def _lowercase ( __A ):
'''simple docstring'''
if not isinstance(__A ,__A ):
raise TypeError("""Undefined for non-integers""" )
elif precision < 1:
... | 349 |
'''simple docstring'''
import string
def _lowercase ( __A ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__UpperCamelCase = """"""
for symbol in message:
if symbol in string.ascii_uppercase:
__UpperCamelC... | 349 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
a__ : Optional[int] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_c... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils impo... | 349 | 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 transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def _lo... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a__ : int = {
'configuration_layoutlmv3': [
... | 349 | 1 |
'''simple docstring'''
import pytest
a__ : List[str] = '__dummy_dataset1__'
a__ : Optional[int] = '\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"\nURLS = {"train": REPO_URL + "wikiann-bn-t... | 349 |
'''simple docstring'''
def _lowercase ( __A ,__A ):
'''simple docstring'''
__UpperCamelCase = len(__A )
__UpperCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed by no... | 349 | 1 |
'''simple docstring'''
import math
import qiskit
def _lowercase ( __A = 1 ,__A = 1 ,__A = 1 ):
'''simple docstring'''
if (
isinstance(__A ,__A )
or isinstance(__A ,__A )
or isinstance(__A ,__A )
):
... | 349 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelo... | 349 | 1 |
'''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
a__ : Union[str, An... | 349 |
'''simple docstring'''
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_ten... | 349 | 1 |
'''simple docstring'''
import math
def _lowercase ( __A ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are no... | 349 |
'''simple docstring'''
import pytest
a__ : List[str] = '__dummy_dataset1__'
a__ : Optional[int] = '\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"\nURLS = {"train": REPO_URL + "wikiann-bn-t... | 349 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils impo... | 349 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaP... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A ):
'''simple docstring'''
if not isinstance(__A ,__A ):
raise TypeError("""only integers accepted as input""" )
else:
__UpperCamelCase = str(abs(__A ) )
__UpperCamelCase = [list(__A )... | 349 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 349 | 1 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
a__ : Optional[Any] = logging.getLogger(__name__)
class UpperCAmelCase__ :
de... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowercase ( __A ,__A ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b ,2 ) for a, b in zip(__A ,__A ... | 349 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
a__ : Union[str, Any] = {
'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
... | 349 |
'''simple docstring'''
from datetime import datetime
import requests
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
__UpperCamelCase = requests.g... | 349 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a__ : Optional[Any] =... | 349 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from un... | 349 | 1 |
'''simple docstring'''
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, re... | 349 |
'''simple docstring'''
import re
def _lowercase ( __A ):
'''simple docstring'''
return [char.split() for char in re.split(R"""[^ a-z A-Z 0-9 \s]""" ,str_ )]
def _lowercase ( __A ):
'''simple docstring'''
__Uppe... | 349 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_im... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
fr... | 349 | 1 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class UpperCAmelCase__ :
def __init__( self ) -> List[str]:
__UpperCamelCase = {}
def __lowerCamelCase ( self , ... | 349 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=UpperCAmelCase_):
__SCREAMING_SNAKE_CASE = ['''flax''']
def __init__( self , *lowercase , **lowercase ) -> List[Any]:
requires_backends(se... | 349 | 1 |
'''simple docstring'''
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... | 349 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class UpperCAmelCase__ ( logging.LoggerAdapter):
@staticmethod
def __lowerCamelCase ( lowercase ) -> Dict:
__UpperCamelCase = PartialState()
return not main_process_... | 349 | 1 |
'''simple docstring'''
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
... | 349 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
a__ : Optional[Any] = logging.getLogger(__name__)
class UpperCAmelCase__ :
de... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
a__ : List[Any] = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def _lowercase ( __A ,__A ,__A ,__A ,__A ,):
'''simple docstring''... | 349 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a__ : Optional[Any] =... | 349 | 1 |
'''simple docstring'''
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transform... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
a__ : str = {
'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_... | 349 | 1 |
'''simple docstring'''
import numpy as np
def _lowercase ( __A ,__A ,__A ,__A ,__A ):
'''simple docstring'''
__UpperCamelCase = int(np.ceil((x_end - xa) / h ) )
__UpperCamelCase = np.zeros((n + 1,) )
__Upper... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
a__ : Union[str, Any] = {
'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A ,__A ,__A=False ):
'''simple docstring'''
if isinstance(__A ,__A ) and isinstance(__A ,__A ):
__UpperCamelCase = len(set_a.intersection(__A ) )
if alternative_union:
__UpperCam... | 349 |
'''simple docstring'''
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 _lowercase ( __A ):
... | 349 | 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_comm... | 349 |
'''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
fro... | 349 | 1 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class UpperCAmelCase__ ( UpperCAmelCase_):
def __in... | 349 |
'''simple docstring'''
import string
def _lowercase ( __A ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__UpperCamelCase = """"""
for symbol in message:
if symbol in string.ascii_uppercase:
__UpperCamelC... | 349 | 1 |
'''simple docstring'''
from bisect import bisect
from itertools import accumulate
def _lowercase ( __A ,__A ,__A ,__A ):
'''simple docstring'''
__UpperCamelCase = sorted(zip(__A ,__A ) ,key=lambda __A : x[0] / x[1] ... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils impo... | 349 | 1 |
'''simple docstring'''
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
a__ : Optional[Any] = 4
a__ : str = 3
class UpperCA... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a__ : int = {
'configuration_layoutlmv3': [
... | 349 | 1 |
'''simple docstring'''
import numpy as np
def _lowercase ( __A ,__A ,__A = 1E-12 ,__A = 100 ,):
'''simple docstring'''
assert np.shape(__A )[0] == np.shape(__A )[1]
# Ensure proper dimensionality.
assert np.shape(__A )[0] == np.... | 349 |
'''simple docstring'''
def _lowercase ( __A ,__A ):
'''simple docstring'''
__UpperCamelCase = len(__A )
__UpperCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed by no... | 349 | 1 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_mo... | 349 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelo... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A ):
'''simple docstring'''
if len(__A ) <= 1:
return lst
__UpperCamelCase = 1
while i < len(__A ):
if lst[i - 1] <= lst[i]:
i += 1
else:
__UpperCamelCase , __UpperCamelCase = l... | 349 |
'''simple docstring'''
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_ten... | 349 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : int = logging.get_logger(__name__)
a__ : Union[str, Any] = {
'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
'https://huggingface.co/tanreinama/GPTSAN-2.8B-spo... | 349 |
'''simple docstring'''
import pytest
a__ : List[str] = '__dummy_dataset1__'
a__ : Optional[int] = '\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"\nURLS = {"train": REPO_URL + "wikiann-bn-t... | 349 | 1 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class UpperCAmelCase__ ( UpperCAmelCase_):... | 349 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaP... | 349 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def _lowercase ( __A = None ):
'''simple docstring'''
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__UpperCamelCase = nums[0]
for i in ra... | 349 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class UpperCAmelCase__ :
__SCREAMING_SNAKE_CASE = 42
__SCREAMING_SNAKE_CASE ... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowercase ( __A ,__A ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b ,2 ) for a, b in zip(__A ,__A ... | 349 | 1 |
'''simple docstring'''
a__ : Union[str, Any] = 9.8_06_65
def _lowercase ( __A ,__A ,__A = g ):
'''simple docstring'''
if fluid_density <= 0:
raise ValueError("""Impossible fluid density""" )
if volume < 0:
raise ValueError("""Impos... | 349 |
'''simple docstring'''
from datetime import datetime
import requests
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
__UpperCamelCase = requests.g... | 349 | 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,
r... | 349 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from un... | 349 | 1 |
'''simple docstring'''
from collections.abc import Generator
from math import sin
def _lowercase ( __A ):
'''simple docstring'''
if len(__A ) != 32:
raise ValueError("""Input must be of length 32""" )
__UpperCamelCase = b""""""
for i in ... | 349 |
'''simple docstring'''
import re
def _lowercase ( __A ):
'''simple docstring'''
return [char.split() for char in re.split(R"""[^ a-z A-Z 0-9 \s]""" ,str_ )]
def _lowercase ( __A ):
'''simple docstring'''
__Uppe... | 349 | 1 |
'''simple docstring'''
import math
def _lowercase ( __A = 100 ):
'''simple docstring'''
__UpperCamelCase = sum(i * i for i in range(1 ,n + 1 ) )
__UpperCamelCase = int(math.pow(sum(range(1 ,n + 1 ) ) ,2 ) )... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
fr... | 349 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Dict = logging.get_logger(__name__)
a__ : Union[str, Any] = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json... | 349 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=UpperCAmelCase_):
__SCREAMING_SNAKE_CASE = ['''flax''']
def __init__( self , *lowercase , **lowercase ) -> List[Any]:
requires_backends(se... | 349 | 1 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a__ : Any ... | 349 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class UpperCAmelCase__ ( logging.LoggerAdapter):
@staticmethod
def __lowerCamelCase ( lowercase ) -> Dict:
__UpperCamelCase = PartialState()
return not main_process_... | 349 | 1 |
'''simple docstring'''
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested... | 349 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
a__ : Optional[Any] = logging.getLogger(__name__)
class UpperCAmelCase__ :
de... | 349 | 1 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_c... | 349 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a__ : Optional[Any] =... | 349 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=UpperCAmelCase_):
__SCREAMING_SNAKE_CASE = ['''flax''']
def __init__( self , *lowercase , **lowercase ) -> List[Any]:
requires_backends(se... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
a__ : str = {
'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_... | 349 | 1 |
'''simple docstring'''
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextMode... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
a__ : Union[str, Any] = {
'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
... | 349 | 1 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
a__ : str = '\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WIL... | 349 |
'''simple docstring'''
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 _lowercase ( __A ):
... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def _lowercase ( __A ,__A ,__A ,__A = 100 ,):
'''simple docstring'''
__UpperCamelCase = x_start
__UpperCamelCase = fnc(__A ... | 349 |
'''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
fro... | 349 | 1 |
'''simple docstring'''
print((lambda quine: quine % quine)('print((lambda quine: quine %% quine)(%r))'))
| 349 |
'''simple docstring'''
import string
def _lowercase ( __A ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__UpperCamelCase = """"""
for symbol in message:
if symbol in string.ascii_uppercase:
__UpperCamelC... | 349 | 1 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_mod... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils impo... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a__ : int = {
'configuration_layoutlmv3': [
... | 349 | 1 |
'''simple docstring'''
import requests
def _lowercase ( __A ,__A ):
'''simple docstring'''
__UpperCamelCase = {"""Content-Type""": """application/json"""}
__UpperCamelCase = requests.post(__A ,json={"""text""": message_body} ... | 349 |
'''simple docstring'''
def _lowercase ( __A ,__A ):
'''simple docstring'''
__UpperCamelCase = len(__A )
__UpperCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed by no... | 349 | 1 |
'''simple docstring'''
a__ : List[Any] = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .d... | 349 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelo... | 349 | 1 |
'''simple docstring'''
class UpperCAmelCase__ :
def __init__( self , lowercase , lowercase , lowercase ) -> Optional[Any]:
__UpperCamelCase = name
__UpperCamelCase = value
__UpperCamelCase = weight
def __repr__( ... | 349 |
'''simple docstring'''
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_ten... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A ):
'''simple docstring'''
if not isinstance(__A ,__A ):
__UpperCamelCase = f"Input value of [number={number}] must be an integer"
raise TypeError(__A )
if number < 0:
return False
__UpperCamelCase ... | 349 |
'''simple docstring'''
import pytest
a__ : List[str] = '__dummy_dataset1__'
a__ : Optional[int] = '\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"\nURLS = {"train": REPO_URL + "wikiann-bn-t... | 349 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def _lowercase ( __A ):
'''simple docstring'''
if num <= 0:
__UpperCamelCase = f"{num}: Invalid input, please enter a positive integer."
raise ValueError(__A )
__Upper... | 349 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaP... | 349 | 1 |
'''simple docstring'''
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_avai... | 349 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A = 2_000_000 ):
'''simple docstring'''
__UpperCamelCase = [0 for i in range(n + 1 )]
__UpperCamelCase = 1
__UpperCamelCase = 1
for i in range(2 ,int(n**0.5 ) + 1 ):
if primality_lis... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowercase ( __A ,__A ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b ,2 ) for a, b in zip(__A ,__A ... | 349 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
a__ : List[Any] = logging.get_logger(__name__)
a__ : Optional[Any] = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-lar... | 349 |
'''simple docstring'''
from datetime import datetime
import requests
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
__UpperCamelCase = requests.g... | 349 | 1 |
'''simple docstring'''
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = []
__Upp... | 349 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from un... | 349 | 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__ : Dict = logging.get_logger(__name__)
a__ : List[Any] = {
'junnyu/ro... | 349 |
'''simple docstring'''
import re
def _lowercase ( __A ):
'''simple docstring'''
return [char.split() for char in re.split(R"""[^ a-z A-Z 0-9 \s]""" ,str_ )]
def _lowercase ( __A ):
'''simple docstring'''
__Uppe... | 349 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
a__ : str = {
'configuration_speech_to_te... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
fr... | 349 | 1 |
'''simple docstring'''
from math import pi, sqrt
def _lowercase ( __A ):
'''simple docstring'''
if num <= 0:
raise ValueError("""math domain error""" )
if num > 171.5:
raise OverflowError("""math range error""" )
elif num - int(__A ) not in (0... | 349 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=UpperCAmelCase_):
__SCREAMING_SNAKE_CASE = ['''flax''']
def __init__( self , *lowercase , **lowercase ) -> List[Any]:
requires_backends(se... | 349 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaP... | 349 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class UpperCAmelCase__ ( logging.LoggerAdapter):
@staticmethod
def __lowerCamelCase ( lowercase ) -> Dict:
__UpperCamelCase = PartialState()
return not main_process_... | 349 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a__ : int = {
'configuration_layoutlmv3': [
... | 349 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
a__ : Optional[Any] = logging.getLogger(__name__)
class UpperCAmelCase__ :
de... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A ,__A ,__A ,__A ,__A ,):
'''simple docstring'''
__UpperCamelCase = [redshift, radiation_density, matter_density, dark_energy]
if any(p < 0 for p in parameters ):
raise ValueError("""All inpu... | 349 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
a__ : Optional[Any] =... | 349 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a__ : Optional[int] = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
a__ : str = {
'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_... | 349 | 1 |
'''simple docstring'''
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionMod... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
a__ : Union[str, Any] = {
'albert-base-v1': 'https://huggingface.co/albert-base-v1/resolve/main/config.json',
... | 349 | 1 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from tran... | 349 |
'''simple docstring'''
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 _lowercase ( __A ):
... | 349 | 1 |
'''simple docstring'''
import numpy
# List of input, output pairs
a__ : List[Any] = (
((5, 2, 3), 1_5),
((6, 5, 9), 2_5),
((1_1, 1_2, 1_3), 4_1),
((1, 1, 1), 8),
((1_1, 1_2, 1_3), 4_1),
)
a__ : List[str] = (((5_1_5, 2_2, 1_3), 5_5_5), ((6_1, 3_5, 4_9), 1_5_0... | 349 |
'''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
fro... | 349 | 1 |
'''simple docstring'''
import baseaa
def _lowercase ( __A ):
'''simple docstring'''
return baseaa.baaencode(string.encode("""utf-8""" ) )
def _lowercase ( __A ):
'''simple docstring'''
return baseaa.baadecode(__A ... | 349 |
'''simple docstring'''
import string
def _lowercase ( __A ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__UpperCamelCase = """"""
for symbol in message:
if symbol in string.ascii_uppercase:
__UpperCamelC... | 349 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Dict = logging.get_logger(__name__)
a__ : str = {
'facebook/dpr-ctx_encoder-single-nq-base': (
'https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-ba... | 349 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils impo... | 349 | 1 |
'''simple docstring'''
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing impor... | 349 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a__ : int = {
'configuration_layoutlmv3': [
... | 349 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoToken... | 349 |
'''simple docstring'''
def _lowercase ( __A ,__A ):
'''simple docstring'''
__UpperCamelCase = len(__A )
__UpperCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed by no... | 349 | 1 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
a__ : Any = 'docs/source/en/_toctree.yml'
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = defaultdict(__A )
for doc in model_d... | 349 |
'''simple docstring'''
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelo... | 349 | 1 |
'''simple docstring'''
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
a__ : Dict = logging.get_logger(__name__)
... | 349 |
'''simple docstring'''
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_ten... | 349 | 1 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def _lowercase ( __A = "AAPL" ):
'''simple docstring'''
__UpperCamelCase = f"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"
__UpperCamelCase = BeautifulSoup(reques... | 349 |
'''simple docstring'''
import pytest
a__ : List[str] = '__dummy_dataset1__'
a__ : Optional[int] = '\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"\nURLS = {"train": REPO_URL + "wikiann-bn-t... | 349 | 1 |
'''simple docstring'''
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCAmelCase__ ( UpperCAmelCase_):
def __init__( self , lowercase , lowercase... | 349 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaP... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A ,__A ):
'''simple docstring'''
__UpperCamelCase = (boundary[1] - boundary[0]) / steps
__UpperCamelCase = boundary[0]
__UpperCamelCase = boundary[1]
__UpperCamelCase = make_points(__A ... | 349 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 349 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determini... | 349 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowercase ( __A ,__A ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b ,2 ) for a, b in zip(__A ,__A ... | 349 | 1 |
'''simple docstring'''
def _lowercase ( __A ,__A ):
'''simple docstring'''
__UpperCamelCase = len(__A )
__UpperCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed by no... | 349 |
'''simple docstring'''
from datetime import datetime
import requests
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
__UpperCamelCase = requests.g... | 349 | 1 |
'''simple docstring'''
import requests
a__ : Dict = 'https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()
... | 349 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from un... | 349 | 1 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from un... | 349 |
'''simple docstring'''
import re
def _lowercase ( __A ):
'''simple docstring'''
return [char.split() for char in re.split(R"""[^ a-z A-Z 0-9 \s]""" ,str_ )]
def _lowercase ( __A ):
'''simple docstring'''
__Uppe... | 349 | 1 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from tra... | 349 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
fr... | 349 | 1 |
'''simple docstring'''
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not u... | 349 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=UpperCAmelCase_):
__SCREAMING_SNAKE_CASE = ['''flax''']
def __init__( self , *lowercase , **lowercase ) -> List[Any]:
requires_backends(se... | 349 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optiona... | 349 |
'''simple docstring'''
import logging
import os
from .state import PartialState
class UpperCAmelCase__ ( logging.LoggerAdapter):
@staticmethod
def __lowerCamelCase ( lowercase ) -> Dict:
__UpperCamelCase = PartialState()
return not main_process_... | 349 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : Any = logging.get_logger(__name__)
a__ : Tupl... | 349 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
a__ : Optional[Any] = logging.getLogger(__name__)
class UpperCAmelCase__ :
de... | 349 | 1 |
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