code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
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 = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[int]:
# This defines a "chinese character" as anything in the CJK Unicode block:
# htt... | 627 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 1 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def _UpperCamelCase ( lowerCAmelCase_ ) ->Dict:
# A local function to see if a dot lands in the circle.
def is_in_circle(lowerCAmelCase_ , lowerCAmelCase_ ) ... | 627 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 | 1 |
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transformers.uti... | 627 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 1 |
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
__a = namedtuple(
"""_TestCommandArgs""",
[
"""dataset... | 627 |
import argparse
__a = """docs/source/_static/js/custom.js"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
with open(lowerCAmelCase_ , encoding="""utf-8""" , newline="""\n""" ) as f:
UpperCAmelCase = f.readlines()
UpperCAmelCase ... | 627 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""bert-base-uncased""": """https://huggingface.co/bert-base-unca... | 627 |
import math
class __lowercase :
def _lowercase ( self : Union[str, Any] , __lowerCamelCase : list[list[float]] , __lowerCamelCase : list[int] ) -> int:
"""simple docstring"""
... | 627 | 1 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params impo... | 627 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = {}
UpperCAmelCase = tok... | 627 | 1 |
import math
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
assert isinstance(lowerCAmelCase_ , lowerCAmelCase_ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 627 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__a = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksach... | 627 | 1 |
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTokenizer, HfArgu... | 627 |
import math
import qiskit
def _UpperCamelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 ) ->qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ ... | 627 | 1 |
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 1 / sqrt(2 ) ) ->IIRFilter:
UpperCAmelCase = tau * frequency / samplerate
UpperCAmelCase = ... | 627 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __lowercase ( __snake_case ):
UpperCamelCase = '''ct... | 627 | 1 |
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
__a = re.compile(R"""^(?P<major>\d+)""" R"""\.(?P<minor>\d+)""" R"""\.(?P<patch>\d+)$""")
@total_ordering
@dataclass
class __lo... | 627 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 | 1 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def _Uppe... | 627 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_available():
raise OptionalDepen... | 627 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__a = logging.get_logger(__name__)
__a = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformable-detr/resolve/main/config.json""",
... | 627 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 | 1 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __lowercase ( yaml.SafeLoader ):
def _lowercase ( self : str , __lowerCamelCase : List[str] ) -> Tuple:
... | 627 |
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 = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 | 1 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 | 1 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.par... | 627 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from trans... | 627 | 1 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
__a = pd.read_csv("""sample_data.csv""", header=None)
__a = df.shape[:1][0]
# If ... | 627 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproc... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->List[str]:
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(lowerCAmelCase_ , n - 1 , lowerCAmelCase_ ) * a) % mod
else:
UpperCAmelCase ... | 627 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 1 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_v... | 627 |
from math import isqrt
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase_ ) + 1 ) )
def _UpperCamelCase ( lowerCAmelCase_ = 1_0**6 ) ->int:
UpperCAmelCase = 0
UpperCAm... | 627 | 1 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_=False ) ->Any:
UpperCAmelCase = OmegaConf.load(lowerCAmelCase_ )
if display:
print(yaml... | 627 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 | 1 |
from timeit import timeit
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
if number < 0:
raise ValueError("""the value of input must not be negative""" )
UpperCAmelCase = 0
while number:
number &= number - 1
result += 1
return result
def _UpperC... | 627 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 1 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __lowercase ( unittest.TestCas... | 627 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 1 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
... | 627 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 | 1 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __lowercase ( unittest.TestCase ):
... | 627 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__a = {
"""configuration_wav2vec2""": ["""WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Wav2Vec2Config"""],... | 627 |
import argparse
__a = """docs/source/_static/js/custom.js"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
with open(lowerCAmelCase_ , encoding="""utf-8""" , newline="""\n""" ) as f:
UpperCAmelCase = f.readlines()
UpperCAmelCase ... | 627 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json""",
}
class __lowercase ( __snake_... | 627 |
import math
class __lowercase :
def _lowercase ( self : Union[str, Any] , __lowerCamelCase : list[list[float]] , __lowerCamelCase : list[int] ) -> int:
"""simple docstring"""
... | 627 | 1 |
__a = range(2, 20 + 1)
__a = [10**k for k in range(ks[-1] + 1)]
__a = {}
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->Union[str, Any]:
UpperCAmelCase = sum(a_i[j] for j in range(lowerCAmelCase_... | 627 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = {}
UpperCAmelCase = tok... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->str:
UpperCAmelCase = [0] * len(lowerCAmelCase_ )
UpperCAmelCase = []
UpperCAmelCase = []
UpperCAmelCase = 0
for values in graph.values():
for i in values:
indegree[i] += 1
... | 627 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__a = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksach... | 627 | 1 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__a = """\
"""
__a = """
Perplexity (PPL) is one of the most common metrics for evaluating language models.
It... | 627 |
import math
import qiskit
def _UpperCamelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 ) ->qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ ... | 627 | 1 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUI... | 627 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __lowercase ( __snake_case ):
UpperCamelCase = '''ct... | 627 | 1 |
import os
from distutils.util import strtobool
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->Any:
for e in env_keys:
UpperCAmelCase = int(os.environ.get(lowerCAmelCase_ , -1 ) )
if val >= 0:
return val
return default
def ... | 627 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->Dict:
if not head:
return True
# split the list to two parts
UpperCAmelCase , UpperCAmelCase = head.next, head
while fast and fast.next:
UpperCAmelCase = fast.next.next
UpperCAmelCase = ... | 627 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_available():
raise OptionalDepen... | 627 | 1 |
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
__a = TypeVar("""T""")
class __lowercase ( Generic[T] ):
def __init... | 627 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 | 1 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTok... | 627 |
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 = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 | 1 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 | 1 |
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen
from... | 627 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from trans... | 627 | 1 |
from statistics import mean, stdev
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ = 3 ) ->list:
UpperCAmelCase = min(lowerCAmelCase_ )
UpperCAmelCase = max(lowerCAmelCase_ )
# normalize data
return [round((x - x_min) / (x_max - x_min) , ... | 627 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproc... | 627 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json""",
}
class __lowercase ( __sn... | 627 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 1 |
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=__snake_case ):
UpperCamelCase = ['''torch''', '''scipy''']
def __init__( self : List[str] , *__lowerCamelCase : Tuple , **__lowerCamelCa... | 627 |
from math import isqrt
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase_ ) + 1 ) )
def _UpperCamelCase ( lowerCAmelCase_ = 1_0**6 ) ->int:
UpperCAmelCase = 0
UpperCAm... | 627 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_sew""": ["""SEW_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except O... | 627 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 1 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import Iterable... | 627 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 | 1 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class __lowercase ( __snake_case ):
UpperCamelCase ... | 627 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 1 |
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 transformers.models.switch_transformers.c... | 627 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ = 2_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = [0 for i in range(n + 1 )]
UpperCAmelCase = 1
UpperCAmelCase = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
for j in ... | 627 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__a = R"""
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model outputs. Read the documen... | 627 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str:
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
UpperCAmelCase = str(bin(lowerCAmelCase_ ) )[2:] # remove the leading "0b"
UpperCAmelCase = ... | 627 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->list[int]:
if length <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("""Length must be a positive integer.""" )
return [n * (2 * n - 1) for n in range(lowerCAmelCase_ )]
if __name__ == "__main... | 627 |
import argparse
__a = """docs/source/_static/js/custom.js"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
with open(lowerCAmelCase_ , encoding="""utf-8""" , newline="""\n""" ) as f:
UpperCAmelCase = f.readlines()
UpperCAmelCase ... | 627 | 1 |
import math
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
UpperCAmelCase = len(lowerCAmelCase_ )
UpperCAmelCase = int(math.floor(math.sqrt(lowerCAmelCase_ ) ) )
UpperCAmelCase = 0
while arr[min(lowerCAmelCase_ , ... | 627 |
import math
class __lowercase :
def _lowercase ( self : Union[str, Any] , __lowerCamelCase : list[list[float]] , __lowerCamelCase : list[int] ) -> int:
"""simple docstring"""
... | 627 | 1 |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import Gradie... | 627 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = {}
UpperCAmelCase = tok... | 627 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__a = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}
__a ... | 627 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__a = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksach... | 627 | 1 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return len(set(lowerCAmelCase_ ) ) == len(lowerCAmelCase_ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 627 |
import math
import qiskit
def _UpperCamelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 ) ->qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ ... | 627 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {
"""configuration_clipseg""": [
"""CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""CLIPSegConfig""",
"""CLIPSegTextConfig""",
"""CLIPSegV... | 627 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __lowercase ( __snake_case ):
UpperCamelCase = '''ct... | 627 | 1 |
import os
__a = {"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1000}
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
while index < len(lowerCAmelCase_ ) - 1:
UpperCAm... | 627 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 | 1 |
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
__a = """<<<<<<< This should probably be modified because it mentions: """
__a = """=======
>>>>>>>
"""
... | 627 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_available():
raise OptionalDepen... | 627 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {
"""configuration_xlm_roberta_xl""": [
"""XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XLMRobertaXLConfig""",
"""XLMRobertaXLOnnxConfig"... | 627 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 | 1 |
from math import factorial
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->float:
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
raise ValueError("""the f... | 627 |
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 = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 | 1 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import Tok... | 627 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 | 1 |
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->tuple[int | None, int | None, float]:
if not a... | 627 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from trans... | 627 | 1 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import tor... | 627 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproc... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
if exponent == 1:
return base
if exponent % 2 == 0:
UpperCAmelCase = _modexpt(lowerCAmelCase_ , exponent // 2 , lowerCAmelCase_ ) % modulo_value
re... | 627 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->bool:
UpperCAmelCase = len(lowerCAmelCase_ ) + 1
UpperCAmelCase = len(lowerCAmelCase_ ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
# length i of input_string ma... | 627 |
from math import isqrt
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase_ ) + 1 ) )
def _UpperCamelCase ( lowerCAmelCase_ = 1_0**6 ) ->int:
UpperCAmelCase = 0
UpperCAm... | 627 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
__a = logging.get_logger(__name__)
__a = {"""voc... | 627 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 | 1 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
Ju... | 627 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 1 |
import math
import sys
import cva
import numpy as np
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->np.ndarray:
# For applying gaussian function for each element in matrix.
UpperCAmelCase = math.sqrt(lowerCAmelCase_ )
UpperCAmelCase = 1 /... | 627 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 1 |
import inspect
import unittest
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : int ) -> Tuple:
"""simple docstring"""
try:
import diffusers # noqa: F401
excep... | 627 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from... | 627 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 | 1 |
from __future__ import annotations
from typing import Any
class __lowercase :
def __init__( self : List[Any] , __lowerCamelCase : int ) -> None:
"""simple docstring"""
UpperCAmelCase =... | 627 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 1 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_obj... | 627 |
import argparse
__a = """docs/source/_static/js/custom.js"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
with open(lowerCAmelCase_ , encoding="""utf-8""" , newline="""\n""" ) as f:
UpperCAmelCase = f.readlines()
UpperCAmelCase ... | 627 | 1 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 |
import math
class __lowercase :
def _lowercase ( self : Union[str, Any] , __lowerCamelCase : list[list[float]] , __lowerCamelCase : list[int] ) -> int:
"""simple docstring"""
... | 627 | 1 |
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.numpy as jnp
... | 627 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = {}
UpperCAmelCase = tok... | 627 | 1 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.mode... | 627 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__a = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksach... | 627 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {
"""configuration_trajectory_transformer""": [
"""TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""TrajectoryTransformerConfig""",
],
... | 627 |
import math
import qiskit
def _UpperCamelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 ) ->qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ ... | 627 | 1 |
from collections.abc import Sequence
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ = False ) ->float:
if not arr:
return 0
UpperCAmelCase = 0 if allow_empty_subarrays else float("""-inf""" )
UpperCAmelCase = 0.0
for num in arr:
... | 627 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __lowercase ( __snake_case ):
UpperCamelCase = '''ct... | 627 | 1 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[int]:
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class __lowercase ( __s... | 627 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->str:
return "".join([hex(lowerCAmelCase_ )[2:].zfill(2 ).upper() for byte in list(lowerCAmelCase_ )] )
def _UpperCamelCase ( lowerCAmelCase_ ) ->bytes:
# Check data validity, following RFC3548
# https://www.ietf.org/r... | 627 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_available():
raise OptionalDepen... | 627 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers... | 627 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 | 1 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
__a = {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DPTConfig"""]}
try:
if not i... | 627 |
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 = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__a = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""PoolFormerConfig""",
"""PoolFormerOn... | 627 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 | 1 |
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_pyazr, re... | 627 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from trans... | 627 | 1 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->list[str]:
if nth_term == "":
return [""]
UpperCAmelCase = int(lowerCAmelCase_ )
UpperCAmelCase = int(lowerCAmelCase_ )
UpperCAmelCase = [... | 627 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproc... | 627 | 1 |
# Lint as: python3
import itertools
import os
import re
__a = re.compile(R"""([A-Z]+)([A-Z][a-z])""")
__a = re.compile(R"""([a-z\d])([A-Z])""")
__a = re.compile(R"""(?<!_)_(?!_)""")
__a = re.compile(R"""(_{2,})""")
__a = R"""^\w+(\.\w+)*$"""
__a = R"""<>:/\|?... | 627 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 1 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 |
from math import isqrt
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase_ ) + 1 ) )
def _UpperCamelCase ( lowerCAmelCase_ = 1_0**6 ) ->int:
UpperCAmelCase = 0
UpperCAm... | 627 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0 ) ->int:
UpperCAmelCase = 2**power
UpperCAmelCase = 0
while n:
UpperCAmelCase , UpperCAmelCase = r + n % 1_0, n // 1_0
return r
if __name__ == "__main__":
print(solution(int(str(input()... | 627 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 1 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __lowercase ( __snake_case ):
UpperCamelCase = (EulerDiscreteScheduler,)
UpperCamelCase = 10
... | 627 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 | 1 |
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils imp... | 627 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 1 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_vis... | 700 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->Any:
if number > 0:
raise ValueError("""input must be a negative integer""" )
UpperCAmelCase = len(bin(__A )[3:] )
UpperCAmelCase = bin(abs(__A ) - (1 << binary_number_length) )[3:]
UpperCAmelCase ... | 701 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 0 |
__a = {
'meter': 'm',
'kilometer': 'km',
'megametre': 'Mm',
'gigametre': 'Gm',
'terametre': 'Tm',
'petametre': 'Pm',
'exametre': 'Em',
'zettametre': 'Zm',
'yottametre': 'Ym',
}
# Exponent of the factor(meter)
__a = {
'm': 0,
'km': 3,
'Mm':... | 702 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 | 0 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils i... | 703 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->Union[str, Any]:
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(_lowercase , int(b / 2 ) ) * actual_power(_lowercase , int(b / 2 ) )
else:
return a * actual_power(_lowerc... | 704 |
import argparse
__a = """docs/source/_static/js/custom.js"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
with open(lowerCAmelCase_ , encoding="""utf-8""" , newline="""\n""" ) as f:
UpperCAmelCase = f.readlines()
UpperCAmelCase ... | 627 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__a = {
"configuration_roc_bert": ["ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RoCBertConfig"],
"tokenization_roc_... | 705 |
import math
class __lowercase :
def _lowercase ( self : Union[str, Any] , __lowerCamelCase : list[list[float]] , __lowerCamelCase : list[int] ) -> int:
"""simple docstring"""
... | 627 | 0 |
'''simple docstring'''
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->float:
if discount_rate < 0:
raise ValueError("""Discount rate cannot be negative""" )
if not cash_flows:
raise ValueError("""Cash flows list cannot be empty""" )
Uppe... | 706 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = {}
UpperCAmelCase = tok... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->float:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) = }""")
| 707 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__a = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksach... | 627 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __lowercase ( unittest.TestCase ):
... | 708 |
import math
import qiskit
def _UpperCamelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 ) ->qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ ... | 627 | 0 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_=7 ):
UpperCAmelCase = None
if token is not None:
UpperCAmelCase = {"""Accept""": ""... | 709 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __lowercase ( __snake_case ):
UpperCamelCase = '''ct... | 627 | 0 |
import logging
import os
from .state import PartialState
class __lowercase ( logging.LoggerAdapter ):
@staticmethod
def _lowercase ( __lowerCamelCase : Optional[Any] ) -> Dict:
"""simple docstring"""
... | 710 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 | 0 |
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