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 |
|---|---|---|---|---|
'''simple docstring'''
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __A ( unittest.TestCase ):
'''simple docstring'''
__lowerCamelCase : Tuple = JukeboxTokenizer
__lowerCamelCase : Dict = {... | 11 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
return len(set(__A)) == len(__A)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 11 | 1 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipelin... | 11 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if len(__A) == 0:
return False
_a = len(__A) // 2
if a_list[midpoint] == item:
return True
if item < a_list[midpoint]:
... | 11 | 1 |
'''simple docstring'''
import unittest
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavi... | 11 |
'''simple docstring'''
class __A :
'''simple docstring'''
def __init__(self , A ) -> None:
"""simple docstring"""
_a = len(A )
_a = [0] * len_array
if len_array > 0:
_a = array[0]
for i in rang... | 11 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_ = {
"configuration_nllb_moe": [
"NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP",
"NllbMoeConfig",
]
}
try:
if not is_torch_av... | 11 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
_a = 2
_a = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_... | 11 | 1 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def lowerCAmelCase (__A):
"... | 11 |
'''simple docstring'''
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
lowercase_ = {
# 1536-bit
5: {
"prime": int... | 11 | 1 |
'''simple docstring'''
from __future__ import annotations
lowercase_ = tuple[int, int, int]
lowercase_ = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
lowercase_ = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
# -------------------------- defa... | 11 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
lowercase_ = log... | 11 | 1 |
'''simple docstring'''
def lowerCAmelCase (__A , __A):
"""simple docstring"""
return 1 if input_a == input_a else 0
def lowerCAmelCase ():
"""simple docstring"""
assert xnor_gate(0 , 0) == 1
assert xnor_gate(0 , 1) == 0
assert xnor_gat... | 11 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
if not isinstance(__A , __A):
raise ValueError('''multiplicative_persistence() only accepts integral values''')
if num < 0:
raise ValueError('''multiplicative_persistence() does not accep... | 11 | 1 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgu... | 11 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_... | 11 | 1 |
'''simple docstring'''
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class __A ( nn.Module ):
'''simple docstring'''
def __init__(self , A = 16 , A = 88 , A = None , A = 1 , A = 0.0 ... | 11 |
'''simple docstring'''
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_... | 11 | 1 |
'''simple docstring'''
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import s... | 11 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 11 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase_ = {
"configuration_efficientformer": [
"EFFICIENTFORMER_PRETRAINED_CON... | 11 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax... | 11 | 1 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_a... | 11 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6'''))
def lowerCAmelCase (__A):
"""simple docstring"""
_a = credit_card_number
_a ... | 11 | 1 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowercase_ = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kernel", ... | 11 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase_ = {
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 11 | 1 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Th... | 11 |
'''simple docstring'''
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowerCAmelCase (__A = "laptop"):
"""simple docstring"""
_a = F'''https://www.amazon.in/laptop/s?k={product}'''
_a = {
... | 11 | 1 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowercase_ = "\\n@article{hendrycksmath2021,\n title={Measuring Mathematical Problem Solving With the MATH Dataset},\n author={Dan Hendrycks\n and Collin Burns\n and Saurav Ka... | 11 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoen... | 11 | 1 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
lowercase_ = "\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel, O. an... | 11 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __A ( A , unittest.TestCase ):
'''simple docstring'''
__lowerCame... | 11 | 1 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTa... | 11 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pyto... | 11 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}
... | 11 |
'''simple docstring'''
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A) , __A)
return number - int(__A)
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolate(35.345, 1))
... | 11 | 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
lowercase_ = logging.get_logger(__name__)
lowercase_ = {... | 11 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Th... | 11 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowercase_ = (3, 9, -11, 0, 7, 5, 1, -1)
lowercase_ = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __A :
'''simple docstring'''
... | 11 |
'''simple docstring'''
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerat... | 11 | 1 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
return sum(i for i in range(1 , number // 2 + 1) if number % i == 0) == number
if __name__ == "__main__":
print("Program to check whether a number is a Perfect number or not...")
lowercase_ = int... | 11 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipelin... | 11 | 1 |
'''simple docstring'''
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A) , __A)
return number - int(__A)
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolate(35.345, 1))
... | 11 |
'''simple docstring'''
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTeste... | 11 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class __A :
'''simple docstring'''
__lowerCamelCase : Optional[Union[str, Path]] = None
__lowerCamelCase : bool = False
... | 11 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
return len(set(__A)) == len(__A)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 11 | 1 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase_ = logging.get_logger(__nam... | 11 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if len(__A) == 0:
return False
_a = len(__A) // 2
if a_list[midpoint] == item:
return True
if item < a_list[midpoint]:
... | 11 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax... | 11 |
'''simple docstring'''
class __A :
'''simple docstring'''
def __init__(self , A ) -> None:
"""simple docstring"""
_a = len(A )
_a = [0] * len_array
if len_array > 0:
_a = array[0]
for i in rang... | 11 | 1 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class __A ( A ):
'''simple docstr... | 11 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
_a = 2
_a = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_... | 11 | 1 |
'''simple docstring'''
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
lowercase_ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
... | 11 |
'''simple docstring'''
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
lowercase_ = {
# 1536-bit
5: {
"prime": int... | 11 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase_ = {
"configuration_biogpt": ["BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BioGptConfig"],
"tokenization_biogpt": ["B... | 11 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
lowercase_ = log... | 11 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase_ = logging.get... | 11 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
if not isinstance(__A , __A):
raise ValueError('''multiplicative_persistence() only accepts integral values''')
if num < 0:
raise ValueError('''multiplicative_persistence() does not accep... | 11 | 1 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 11 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_... | 11 | 1 |
'''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __A ( A ):
'''simple docstring'''
__lo... | 11 |
'''simple docstring'''
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_... | 11 | 1 |
'''simple docstring'''
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase (__A ... | 11 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 11 | 1 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def lowerCAmelCase (__A):
"""simple docstring"""
for i in range(0 , __A):
for _ in range(0 , n - i - 1): # printing spaces
print(''' ''' , end='''''')
fo... | 11 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax... | 11 | 1 |
'''simple docstring'''
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
'''split_dict''' , [
SplitDict(),
SplitDict({'''train''': SplitInfo(name='''train''' , num_bytes=1_337 , nu... | 11 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6'''))
def lowerCAmelCase (__A):
"""simple docstring"""
_a = credit_card_number
_a ... | 11 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowercase_ = TypeVar("T")
lowercase_ = TypeVar("U")
class __A ( Generic[T, U] ):
'''simple docstring'''
def __init__(self , A... | 11 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase_ = {
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 11 | 1 |
'''simple docstring'''
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
lowercase_ = get_tests_dir("fixtures/test_sentencepie... | 11 |
'''simple docstring'''
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowerCAmelCase (__A = "laptop"):
"""simple docstring"""
_a = F'''https://www.amazon.in/laptop/s?k={product}'''
_a = {
... | 11 | 1 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def lowerCAmelCase (__A , ... | 11 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoen... | 11 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
... | 11 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __A ( A , unittest.TestCase ):
'''simple docstring'''
__lowerCame... | 11 | 1 |
'''simple docstring'''
import collections
import os
import re
from pathlib import Path
lowercase_ = "src/transformers"
# Matches is_xxx_available()
lowercase_ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowercase_ = re.compile(R"^_... | 11 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pyto... | 11 | 1 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)... | 11 |
'''simple docstring'''
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A) , __A)
return number - int(__A)
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolate(35.345, 1))
... | 11 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def lowerCAmelCase (__A = None):
"""simple docstring"""
if nums is None or not nums:
raise ValueError('''Input sequence should not be empty''')
_a = nums[0]
for i in range(1 , len(__A)):... | 11 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Th... | 11 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowercase_ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# T... | 11 |
'''simple docstring'''
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerat... | 11 | 1 |
'''simple docstring'''
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __A ( A ):
'''simple docstring'''
def a__ (self , A ) -> Union[str, Any]:
"""simple docstring"""
with open(A , ... | 11 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipelin... | 11 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(A ) , ... | 11 |
'''simple docstring'''
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTeste... | 11 | 1 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
lowercase_ = logging.get_logger(__... | 11 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
return len(set(__A)) == len(__A)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 11 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
... | 11 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if len(__A) == 0:
return False
_a = len(__A) // 2
if a_list[midpoint] == item:
return True
if item < a_list[midpoint]:
... | 11 | 1 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
if isinstance(__A , __A):
raise TypeError('''\'float\' object cannot be interpreted as an integer''')
if isinstance(__A , __A):
raise TypeError('''\'str\' object cannot be interpr... | 11 |
'''simple docstring'''
class __A :
'''simple docstring'''
def __init__(self , A ) -> None:
"""simple docstring"""
_a = len(A )
_a = [0] * len_array
if len_array > 0:
_a = array[0]
for i in rang... | 11 | 1 |
'''simple docstring'''
import math
def lowerCAmelCase (__A):
"""simple docstring"""
_a = math.loga(math.sqrt(4 * positive_integer + 1) / 2 + 1 / 2)
return exponent == int(__A)
def lowerCAmelCase (__A = 1 / 12_345):
"""simple docstring"""
_a ... | 11 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
_a = 2
_a = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_... | 11 | 1 |
'''simple docstring'''
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"vocab_file": "vocab.json",
"tokenizer_confi... | 11 |
'''simple docstring'''
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
lowercase_ = {
# 1536-bit
5: {
"prime": int... | 11 | 1 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __A ( A ):
'''simple docstring'''
__lowerCamelCase : List[Any] = (DDPMScheduler,)
def a__ (self , **A ) -> Optional[int]:
... | 11 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
lowercase_ = log... | 11 | 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 AutoTokenizer
lowercase... | 11 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
if not isinstance(__A , __A):
raise ValueError('''multiplicative_persistence() only accepts integral values''')
if num < 0:
raise ValueError('''multiplicative_persistence() does not accep... | 11 | 1 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
def lowerCAmelCase (__A , __A):
"""simple docstring"""
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def lowerCAmelCase (__A)... | 11 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_... | 11 | 1 |
'''simple docstring'''
def lowerCAmelCase (__A = 1 , __A = 1_000):
"""simple docstring"""
_a = 1
_a = 0
for divide_by_number in range(__A , digit + 1):
_a = []
_a = numerator
for _ in... | 11 |
'''simple docstring'''
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_... | 11 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class __A :
'''simple docstring'''
def __init__(self , A ) -> None:
"""simple docstring"""
_a = num_of_nodes
_a = []
_a = {}
... | 11 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 11 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowercase_ = {"tokenization_wav2vec2_phoneme": ["Wav2Vec2PhonemeCTCTokenizer"]}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
lowercase_ ... | 11 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax... | 11 | 1 |
'''simple docstring'''
from math import sqrt
def lowerCAmelCase (__A = 1_000_000):
"""simple docstring"""
_a = 0
_a = 0
_a = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 ... | 11 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6'''))
def lowerCAmelCase (__A):
"""simple docstring"""
_a = credit_card_number
_a ... | 11 | 1 |
'''simple docstring'''
import random
def lowerCAmelCase (__A , __A , __A = False):
"""simple docstring"""
_a = {i: [] for i in range(__A)}
# if probability is greater or equal than 1, then generate a complete graph
if probability >= 1:
re... | 11 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase_ = {
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 11 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
if len(__A) == 0:
return []
_a , _a = min(__A), max(__A)
_a = int(max_value - min_value) + 1
_a = [[] for _ ... | 11 |
'''simple docstring'''
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowerCAmelCase (__A = "laptop"):
"""simple docstring"""
_a = F'''https://www.amazon.in/laptop/s?k={product}'''
_a = {
... | 11 | 1 |
'''simple docstring'''
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
f... | 11 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoen... | 11 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase_ = {
"configuration_conditional_detr": [
"CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP",
"ConditionalDe... | 11 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __A ( A , unittest.TestCase ):
'''simple docstring'''
__lowerCame... | 11 | 1 |
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tenso... | 0 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pyto... | 11 | 0 |
def _A ( _lowercase , _lowercase ) -> float:
"""simple docstring"""
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modulus / density) ** 0.5
if ... | 1 |
'''simple docstring'''
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A) , __A)
return number - int(__A)
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolate(35.345, 1))
... | 11 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE_ ( _snake_case :int = 4 ) -> list[list[int]]:
_A = abs(_snake_case ) or 4
return [[1 + x + y * row_size for x in range(_snake_case )] for y in range(_snake_case )]
def SCREAMING_SNAKE_CASE_ ( _sna... | 2 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Th... | 11 | 0 |
'''simple docstring'''
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
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_... | 3 |
'''simple docstring'''
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerat... | 11 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : float , _UpperCAmelCase : float ):
if mass < 0:
raise ValueError('The mass of a body cannot be negative' )
return 0.5 * mass * abs(_UpperCAmelCase ) * abs(_UpperCAmelCase )
if __name__ == "__main__":
im... | 4 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipelin... | 11 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
_lowercase ... | 5 |
'''simple docstring'''
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTeste... | 11 | 0 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: float , UpperCamelCase__: float ):
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 * mass * abs(UpperCamelCase__ ) * abs(UpperCamelCase__ )
if __name__ == "__main__":
import d... | 6 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
return len(set(__A)) == len(__A)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 11 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from .... | 7 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if len(__A) == 0:
return False
_a = len(__A) // 2
if a_list[midpoint] == item:
return True
if item < a_list[midpoint]:
... | 11 | 0 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.nu... | 8 |
'''simple docstring'''
class __A :
'''simple docstring'''
def __init__(self , A ) -> None:
"""simple docstring"""
_a = len(A )
_a = [0] * len_array
if len_array > 0:
_a = array[0]
for i in rang... | 11 | 0 |
import heapq as hq
import math
from collections.abc import Iterator
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : List[Any] , _snake_case : Tuple ):
"""simple docstring"""
A__ = str(id_ )
... | 9 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
_a = 2
_a = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_... | 11 | 0 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
_lowerCAmelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( ... | 10 |
'''simple docstring'''
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
lowercase_ = {
# 1536-bit
5: {
"prime": int... | 11 | 0 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def UpperCamelCase ( lowercase_ , lowercase_... | 12 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
lowercase_ = log... | 11 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ (metaclass=_UpperCAmelCase ):
"""simple docstring"""
lowerCamelCase : Optional[int] = ['note_seq']
def __init__( self , *SCREAMING_SNAKE_CASE_ , **SCRE... | 13 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
if not isinstance(__A , __A):
raise ValueError('''multiplicative_persistence() only accepts integral values''')
if num < 0:
raise ValueError('''multiplicative_persistence() does not accep... | 11 | 0 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase_ ( __lowercase... | 14 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_... | 11 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def UpperCamelCase ( __magic_name__ : Lis... | 15 |
'''simple docstring'''
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_... | 11 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : Union[str, Any] = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/m... | 16 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 11 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase_ : Optional[int] = {
'''funnel-transformer/small''': '''https://huggingface.co/funnel-transformer/small/resolve/main/config.... | 17 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax... | 11 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class lowerCAmelCase_ ( __magic_name__ ):
def __init__( self , *_lowerCAmelCase , **_lowerCAmelC... | 18 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6'''))
def lowerCAmelCase (__A):
"""simple docstring"""
_a = credit_card_number
_a ... | 11 | 0 |
"""simple docstring"""
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowerCamelCase__ ( __snake_case ) -> Union[str, Any]:
"""simple docstring"""
return x + 2
... | 19 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase_ = {
"configuration_blip": [
"BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 11 | 0 |
def _lowercase( __a : int ):
a__ =(1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def _lowercase( __a : int = 5000 ):
a__ =[(i * (3 * i - 1)) // 2 for i in range(1 , __a )]
for i, pentagonal_i in enumerate(__a ):
... | 20 |
'''simple docstring'''
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowerCAmelCase (__A = "laptop"):
"""simple docstring"""
_a = F'''https://www.amazon.in/laptop/s?k={product}'''
_a = {
... | 11 | 0 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Any = logging.get_logger(__name__)
UpperCAmelCase_ : List[Any] = {
"facebook/encodec_24khz": "https:/... | 21 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoen... | 11 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_a )
class A ( _a ):
lowercase_ = field(default='language... | 22 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __A ( A , unittest.TestCase ):
'''simple docstring'''
__lowerCame... | 11 | 0 |
from __future__ import annotations
def _snake_case (__lowercase , __lowercase , __lowercase):
if (voltage, current, resistance).count(0) != 1:
raise ValueError('One and only one argument must be 0')
if resistance < 0:
raise ValueError('Resistance can... | 23 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pyto... | 11 | 0 |
'''simple docstring'''
UpperCAmelCase_ : List[Any] = {
0: '''0''',
1: '''1''',
2: '''2''',
3: '''3''',
4: '''4''',
5: '''5''',
6: '''6''',
7: '''7''',
8: '''8''',
9: '''9''',
1_0: '''a''',
1_1: '''b''',
1_2: '''c''',
1_3: '''d''',
1_4: '''e... | 24 |
'''simple docstring'''
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if digit_amount > 0:
return round(number - int(__A) , __A)
return number - int(__A)
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolate(35.345, 1))
... | 11 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 25 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Th... | 11 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase = {"configurati... | 26 |
'''simple docstring'''
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerat... | 11 | 0 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
_A = int(number**0.5 )
return number == sq * sq
... | 27 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipelin... | 11 | 0 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate impor... | 28 |
'''simple docstring'''
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTeste... | 11 | 0 |
"""simple docstring"""
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def lowercase ( lowerCAmelCase_... | 29 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
return len(set(__A)) == len(__A)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 11 | 0 |
__a = 'Input must be a string of 8 numbers plus letter'
__a = 'TRWAGMYFPDXBNJZSQVHLCKE'
def lowerCamelCase__ ( _lowercase ):
'''simple docstring'''
if not isinstance(_lowercase , _lowercase ):
UpperCAmelCase_ : List[Any] = f'''Expect... | 30 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if len(__A) == 0:
return False
_a = len(__A) // 2
if a_list[midpoint] == item:
return True
if item < a_list[midpoint]:
... | 11 | 0 |
from __future__ import annotations
from functools import lru_cache
from math import ceil
lowerCamelCase__ : Any = 100
lowerCamelCase__ : Optional[Any] = set(range(3, NUM_PRIMES, 2))
primes.add(2)
lowerCamelCase__ : int
for prime in range(3, ceil(NUM_PRIMES**0.5), 2)... | 31 |
'''simple docstring'''
class __A :
'''simple docstring'''
def __init__(self , A ) -> None:
"""simple docstring"""
_a = len(A )
_a = [0] * len_array
if len_array > 0:
_a = array[0]
for i in rang... | 11 | 0 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
UpperCAmelCase_ = logging.get_logger(__name__)
UpperC... | 32 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase (__A):
"""simple docstring"""
_a = 2
_a = []
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.append(_... | 11 | 0 |
import argparse
import os
import re
lowerCamelCase__ : Optional[int] = """src/transformers/models/auto"""
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
lowerCamelCase__ : List[Any]... | 33 |
'''simple docstring'''
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
lowercase_ = {
# 1536-bit
5: {
"prime": int... | 11 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE_ = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
t... | 34 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
lowercase_ = log... | 11 | 0 |
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import ... | 35 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
if not isinstance(__A , __A):
raise ValueError('''multiplicative_persistence() only accepts integral values''')
if num < 0:
raise ValueError('''multiplicative_persistence() does not accep... | 11 | 0 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _A ( unittest.TestCase ):
'''sim... | 36 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_... | 11 | 0 |
from __future__ import annotations
from typing import Generic, TypeVar
UpperCamelCase : Optional[Any] = TypeVar("""T""")
class A__ ( Generic[T] ):
"""simple docstring"""
def __init__( self : Tuple , lowerCamelCase__ : T ):
a__ : int = data
... | 37 |
'''simple docstring'''
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_... | 11 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( __magic_name__ : str , __magic_name__ : str ) -> bool:
'''simple docstring'''
snake_case__ : Union[str, Any] = get_failure_array(__magic_name__ )
# 2) Step throu... | 38 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 11 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase_ = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''MobileNetV2Config''',
... | 39 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax... | 11 | 0 |
from collections import Counter
from timeit import timeit
def UpperCamelCase ( snake_case__ : str = "" , ) -> bool:
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values() ) < 2
def UpperCamelCase ( snake_case__ : str = "" ... | 40 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6'''))
def lowerCAmelCase (__A):
"""simple docstring"""
_a = credit_card_number
_a ... | 11 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.