code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import numpy as np
def __lowerCamelCase ( UpperCAmelCase_ : str , UpperCAmelCase_ : Union[str, Any] ):
"""simple docstring"""
return np.where(vector > 0 , _lowerCAmelCase , (alpha * (np.exp(_lowerCAmelCase ) - 1)) )
if __name__ == "__main__":
i... | 354 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __lowerCamelCase ( UpperCAmelCase_ : dict ):
"""... | 281 | 0 |
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
import s... | 355 |
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
snake_case : Optional[Any] = logging.get_logger(__name__)
snake_case : Dict = {
... | 281 | 0 |
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def __lowerCamelCase ( UpperCAmelCase_ : Union[str, Any] ):
"""simple docstring"""
return 1... | 356 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case : Any = {'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}
try:
if not is_torch_available():
raise... | 281 | 0 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.robe... | 357 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 100 ):
"""simple docstring"""
a :List[Any] = 0
a :List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_int... | 281 | 0 |
import math
def __lowerCamelCase ( UpperCAmelCase_ : List[str] = 100 ):
"""simple docstring"""
a :Any = sum(i * i for i in range(1 , n + 1 ) )
a :Union[str, Any] = int(math.pow(sum(range(1 , n + 1 ) ... | 358 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case : List[str] = logging.get_logger(__name__)
snake_case : Optional[Any] = {
'''vocab_file''': '''vocab... | 281 | 0 |
from __future__ import annotations
from typing import Any
class _snake_case ( SCREAMING_SNAKE_CASE__ ):
pass
class _snake_case :
def __init__( self , _lowerCamelCase ):
a :Any = data
a :Node | None = None
def __iter__( self ):
... | 359 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 281 | 0 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
snake_case : str = 10
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : int , Upp... | 360 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...tes... | 281 | 0 |
import argparse
import datetime
def __lowerCamelCase ( UpperCAmelCase_ : str ):
"""simple docstring"""
a :List[str] = {
'''0''': '''Sunday''',
'''1''': '''Monday''',
'''2''': '''Tuesday''',
'''3''': '''Wednesday''',
... | 361 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
depreca... | 281 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension... | 362 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, tor... | 281 | 0 |
from ....utils import logging
snake_case : Optional[int] = logging.get_logger(__name__)
class _snake_case ( _A ):
def __init__( self , _lowerCamelCase , _lowerCamelCase=None , _lowerCamelCase=2048 ):
a :Any = config.__dict__
a :Optional[Any] ... | 363 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 281 | 0 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _snake_case ( yaml.SafeLoader ):
def SCREAMING_SNAKE_CASE__ ( self , _lowerCamelCase ):
a :Dict = [self.constructed_objects[key_node] for key_node, _ in ... | 364 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _sn... | 281 | 0 |
from __future__ import annotations
snake_case : List[str] = list[list[int]]
# assigning initial values to the grid
snake_case : str = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3... | 365 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case : List[Any] = get_tests_dir('''fixtures/test_sentenc... | 281 | 0 |
from math import log
from scipy.constants import Boltzmann, physical_constants
snake_case : Any = 3_00 # TEMPERATURE (unit = K)
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : Tuple , UpperCAmelCase_ : Tuple , ):
"""simple docstring"""
... | 366 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils impo... | 281 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
snake_case : Any = logging.get_logger(__name__)
snake_case : List[Any] = {
'''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.js... | 367 |
def __lowerCamelCase ( UpperCAmelCase_ : int ):
"""simple docstring"""
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise TypeError('''Input value must be an \'int\' type''' )
a :Optional[int] = 0
while number:
... | 281 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
snake_case : Optional[Any] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechC... | 368 |
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.data import DataLoader, Rand... | 281 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class _snake_case ( _snake_case ):
def __init__( self , _lowerCamelCase , _lowerCamelCase ):
a :List[str] = params
a :Optional[int] ... | 369 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
FEATURE... | 281 | 0 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import C... | 370 |
import math
def __lowerCamelCase ( UpperCAmelCase_ : float , UpperCAmelCase_ : float ):
"""simple docstring"""
return math.pow(UpperCAmelCase_ , 2 ) - a
def __lowerCamelCase ( UpperCAmelCase_ : float ):
"""simple docstring"""... | 281 | 0 |
import warnings
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
snake_case : str = logging.get_logger(__name__)
snake_case : List[str] ... | 371 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : List[str] ... | 281 | 0 |
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 _snake_case ( unittest.TestCase ):
@property
... | 350 |
def __lowerCamelCase ( UpperCAmelCase_ : str ):
"""simple docstring"""
if n_term == "":
return []
a :list = []
for temp in range(int(UpperCAmelCase_ ) ):
series.append(F'''1/{temp + 1}''' if series else '''1''' ... | 281 | 0 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class _snake_case ( nn.Module ... | 351 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffuse... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : int ):
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def __lowerCamelCase ( ):
"""simple docstring"""
assert or_gate(0 , 0 ) =... | 352 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
snake_case : Any = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ['''paws''', ''... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 50 ):
"""simple docstring"""
a :Tuple = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_leng... | 353 |
from ...configuration_utils import PretrainedConfig
class _snake_case ( _snake_case ):
SCREAMING_SNAKE_CASE__ = 'bert-generation'
def __init__( self , _lowerCamelCase=5_0358 , _lowerCamelCase=1024 , _lowerCamelCase=24 , _lowerCamelCase=16 , _lowerCamelCase=4096 , _lowerCamelCase="g... | 281 | 0 |
from __future__ import annotations
def __lowerCamelCase ( UpperCAmelCase_ : list[int | float] , UpperCAmelCase_ : int , UpperCAmelCase_ : int ):
"""simple docstring"""
if len(_lowerCAmelCase ) == 0:
raise ValueError('''find_max() arg is an... | 354 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __lowerCamelCase ( UpperCAmelCase_ : dict ):
"""... | 281 | 0 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is_vision_avail... | 355 |
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
snake_case : Optional[Any] = logging.get_logger(__name__)
snake_case : Dict = {
... | 281 | 0 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
snake_case : Optional[int] = 'sshleifer/bart-tiny-random'... | 356 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case : Any = {'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}
try:
if not is_torch_available():
raise... | 281 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case : Dict = {
'''configuration_blenderbot_small''': [
'''BLENDERBOT_SMALL... | 357 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 100 ):
"""simple docstring"""
a :List[Any] = 0
a :List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_int... | 281 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : List[Any] = {
'''configuration_nllb_moe''': [
'''NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''NllbMoeConfig''',
]
}
try:
if... | 358 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case : List[str] = logging.get_logger(__name__)
snake_case : Optional[Any] = {
'''vocab_file''': '''vocab... | 281 | 0 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
snake_case : Dict = logging.get_logger(__name__)
snake_case : int = [
['''attention''', '''attn'''],
['... | 359 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 281 | 0 |
from __future__ import annotations
def __lowerCamelCase ( UpperCAmelCase_ : tuple[int, int] , UpperCAmelCase_ : int ):
"""simple docstring"""
a :Optional[int] = position
a :str = [
(y + 1, x + 2),
(y - 1, x + 2)... | 360 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...tes... | 281 | 0 |
from collections import Counter
from timeit import timeit
def __lowerCamelCase ( UpperCAmelCase_ : str = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(''' ''' , '''''' ).lower() ).values() ) < 2
def __lowerCamelCase ... | 361 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
depreca... | 281 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
snake_case : str = logging.get_logger(__name__)
def __lowerCamelCase ( UpperCAmelCase_ : int ):
"""simple docstring"""
... | 362 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, tor... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : int ):
"""simple docstring"""
return int((input_a, input_a).count(0 ) == 0 )
def __lowerCamelCase ( ):
"""simple docstring"""
assert and_gate(0 , 0 ) ... | 363 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 281 | 0 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
snake_case : int = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow('''''', '''|''', '''|'''),
... | 364 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _sn... | 281 | 0 |
from __future__ import annotations
snake_case : List[str] = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
snake_case : Union[str, Any] = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def __lowerCamelCase ( UpperCAmelCase_ : list[float] ):
... | 365 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case : List[Any] = get_tests_dir('''fixtures/test_sentenc... | 281 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice... | 366 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils impo... | 281 | 0 |
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...te... | 367 |
def __lowerCamelCase ( UpperCAmelCase_ : int ):
"""simple docstring"""
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise TypeError('''Input value must be an \'int\' type''' )
a :Optional[int] = 0
while number:
... | 281 | 0 |
from statistics import mean
import numpy as np
def __lowerCamelCase ( UpperCAmelCase_ : List[str] , UpperCAmelCase_ : Optional[Any] , UpperCAmelCase_ : Any , UpperCAmelCase_ : Dict ):
a :Dict = 0
# Number of processes finished
a :... | 368 |
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.data import DataLoader, Rand... | 281 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 369 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
FEATURE... | 281 | 0 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _snake_case ( _lowerCAmelCase , unittest.TestCase ):
SCREAMING_SNAKE_CASE__ = CTRLTokenizer
... | 370 |
import math
def __lowerCamelCase ( UpperCAmelCase_ : float , UpperCAmelCase_ : float ):
"""simple docstring"""
return math.pow(UpperCAmelCase_ , 2 ) - a
def __lowerCamelCase ( UpperCAmelCase_ : float ):
"""simple docstring"""... | 281 | 0 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MAX_SHARD_SIZE
from data... | 371 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : List[str] ... | 281 | 0 |
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
class _snake_case (... | 350 |
def __lowerCamelCase ( UpperCAmelCase_ : str ):
"""simple docstring"""
if n_term == "":
return []
a :list = []
for temp in range(int(UpperCAmelCase_ ) ):
series.append(F'''1/{temp + 1}''' if series else '''1''' ... | 281 | 0 |
def __lowerCamelCase ( ):
"""simple docstring"""
a :Tuple = []
a :Dict = 1
while len(A__ ) < 1E6:
constant.append(str(A__ ) )
i += 1
a :Tuple = """""".join(A__ )
return (
... | 351 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffuse... | 281 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def __lowerCamelCase ( UpperCAmelCase_ : str ):
"""simple docstring"""
if (
(cp >= 0x4_E00 and cp <= 0x9_FFF)
o... | 352 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
snake_case : Any = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ['''paws''', ''... | 281 | 0 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _snake_case ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self ):
debug_launcher(test_script.main )
def SCREAMING_SNAKE_CA... | 353 |
from ...configuration_utils import PretrainedConfig
class _snake_case ( _snake_case ):
SCREAMING_SNAKE_CASE__ = 'bert-generation'
def __init__( self , _lowerCamelCase=5_0358 , _lowerCamelCase=1024 , _lowerCamelCase=24 , _lowerCamelCase=16 , _lowerCamelCase=4096 , _lowerCamelCase="g... | 281 | 0 |
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : int , UpperCAmelCase_ : float = 1 / sqrt(2 ) ):
"""simple docstring"""
a :int = tau * f... | 354 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __lowerCamelCase ( UpperCAmelCase_ : dict ):
"""... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : Tuple , UpperCAmelCase_ : Union[str, Any] ):
"""simple docstring"""
a :Optional[int] = len(UpperCAmelCase_ ) + 1
a :Optional[Any] = len(UpperCAmelCase_ ) + 1
# dp is a 2d ma... | 355 |
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
snake_case : Optional[Any] = logging.get_logger(__name__)
snake_case : Dict = {
... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 1000 ):
"""simple docstring"""
a :int = 1, 1
a :Any = 2
while True:
a :Optional[Any] = 0
a :Any = fa + fa
a :Optional[... | 356 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case : Any = {'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}
try:
if not is_torch_available():
raise... | 281 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVe... | 357 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 100 ):
"""simple docstring"""
a :List[Any] = 0
a :List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_int... | 281 | 0 |
import math
def __lowerCamelCase ( UpperCAmelCase_ : int ):
"""simple docstring"""
return math.sqrt(_A ) * math.sqrt(_A ) == num
def __lowerCamelCase ( UpperCAmelCase_ : Union[str, Any] ):
"""simple docstring"""... | 358 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case : List[str] = logging.get_logger(__name__)
snake_case : Optional[Any] = {
'''vocab_file''': '''vocab... | 281 | 0 |
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Im... | 359 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 281 | 0 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'''files''' , [
['''full:README.md''', '''dataset_infos.json'''],
['''empty:README.md''', '''dataset_infos.json'''],
... | 360 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...tes... | 281 | 0 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
snake_case : List[str] = {
"tiny.en": "https://openaipublic.azureedge.net/main/whisper/models/d3d... | 361 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
depreca... | 281 | 0 |
"""simple docstring"""
def __lowerCamelCase ( UpperCAmelCase_ : Union[str, Any] ):
"""simple docstring"""
if isinstance(__snake_case , __snake_case ):
raise TypeError('''\'float\' object cannot be interpreted as an integer''' )
if isinstan... | 362 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, tor... | 281 | 0 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
snake_case : Tuple = object()
# For specifying empty leaf dict `{}`
snake_case : int = object()
def __lowerCamelCase ... | 363 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 281 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils import patch_environ... | 364 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _sn... | 281 | 0 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkou... | 365 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case : List[Any] = get_tests_dir('''fixtures/test_sentenc... | 281 | 0 |
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_pytorch_model
from transformers.u... | 366 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils impo... | 281 | 0 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():... | 367 |
def __lowerCamelCase ( UpperCAmelCase_ : int ):
"""simple docstring"""
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise TypeError('''Input value must be an \'int\' type''' )
a :Optional[int] = 0
while number:
... | 281 | 0 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
snake_case : int = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies # noqa: E402
# This is the refere... | 368 |
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.data import DataLoader, Rand... | 281 | 0 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_co... | 369 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
FEATURE... | 281 | 0 |
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class _snake_case :
SCREAMING_SNAKE_CASE__ = 42
SCREAMING_SNAKE_CASE__ = None
SCREAMING_SNAKE_CASE__ = None
snake_case : int = namedtuple('''CoinsDistribResult... | 370 |
import math
def __lowerCamelCase ( UpperCAmelCase_ : float , UpperCAmelCase_ : float ):
"""simple docstring"""
return math.pow(UpperCAmelCase_ , 2 ) - a
def __lowerCamelCase ( UpperCAmelCase_ : float ):
"""simple docstring"""... | 281 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.ut... | 371 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : List[str] ... | 281 | 0 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
_lowerCamelCase : Union[str, Any] = logging.getLogger(__name__)
@dataclass
class _snake_case ( _snake_case ):... | 350 |
def __lowerCamelCase ( UpperCAmelCase_ : str ):
"""simple docstring"""
if n_term == "":
return []
a :list = []
for temp in range(int(UpperCAmelCase_ ) ):
series.append(F'''1/{temp + 1}''' if series else '''1''' ... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 50 ):
"""simple docstring"""
a :str = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length... | 351 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffuse... | 281 | 0 |
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
snake_ca... | 352 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
snake_case : Any = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ['''paws''', ''... | 281 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_t... | 353 |
from ...configuration_utils import PretrainedConfig
class _snake_case ( _snake_case ):
SCREAMING_SNAKE_CASE__ = 'bert-generation'
def __init__( self , _lowerCamelCase=5_0358 , _lowerCamelCase=1024 , _lowerCamelCase=24 , _lowerCamelCase=16 , _lowerCamelCase=4096 , _lowerCamelCase="g... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : int ):
"""simple docstring"""
return int(input_a == input_a == 0 )
def __lowerCamelCase ( ):
"""simple docstring"""
print('''Truth Table of NOR Gate:''' )
... | 354 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __lowerCamelCase ( UpperCAmelCase_ : dict ):
"""... | 281 | 0 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
snake_case : Any = '''\
'''
snake_case : int = '''
Perplexity (PPL) is one of the most common metrics for eval... | 355 |
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
snake_case : Optional[Any] = logging.get_logger(__name__)
snake_case : Dict = {
... | 281 | 0 |
from __future__ import annotations
class _snake_case :
def __init__( self , _lowerCamelCase ):
a :List[str] = data
a :Node | None = None
a :Node | None = None
def __lowerCamelCase ( UpperCAmelCase_ : Node | None... | 356 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case : Any = {'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}
try:
if not is_torch_available():
raise... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : list[int] , UpperCAmelCase_ : int ):
"""simple docstring"""
def count_of_possible_combinations(UpperCAmelCase_ : int ) -> int:
if target < 0:
return 0... | 357 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 100 ):
"""simple docstring"""
a :List[Any] = 0
a :List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_int... | 281 | 0 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
Ope... | 358 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case : List[str] = logging.get_logger(__name__)
snake_case : Optional[Any] = {
'''vocab_file''': '''vocab... | 281 | 0 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( UpperCAmelCase_ : Any ):
"""simple docstring"""
a :int = {}
a :List[Any] = job['''started_at''']
a :List[... | 359 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 281 | 0 |
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_torch_available():
impor... | 360 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...tes... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : list ):
"""simple docstring"""
def merge(UpperCAmelCase_ : list , UpperCAmelCase_ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0]... | 361 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
depreca... | 281 | 0 |
"""simple docstring"""
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@data... | 362 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, tor... | 281 | 0 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
snake_case : ... | 363 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 281 | 0 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
snake_case : Tuple = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''attn''': '''attention.self''',
... | 364 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _sn... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int ):
"""simple docstring"""
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise TypeError('''Input value must be an \'int\' type''' )
a :Optional[int] = 0
while number:
... | 365 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case : List[Any] = get_tests_dir('''fixtures/test_sentenc... | 281 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _snake_case ( _snake_case ):
SCREAMING_SNAKE_C... | 366 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils impo... | 281 | 0 |
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class _snake_case :
SCREAMING_SNAKE_CASE__ = 42
SCREAMING_SNAKE_CASE__ = None
SCREAMING_SNAKE_CASE__ = None
def __lowerCamelCase ( UpperCAmelCase_ : TreeNode | None ):
"""simp... | 367 |
def __lowerCamelCase ( UpperCAmelCase_ : int ):
"""simple docstring"""
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise TypeError('''Input value must be an \'int\' type''' )
a :Optional[int] = 0
while number:
... | 281 | 0 |
from __future__ import annotations
def __lowerCamelCase ( UpperCAmelCase_ : float , UpperCAmelCase_ : float , UpperCAmelCase_ : float , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('''You cannot supply more or less... | 368 |
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.data import DataLoader, Rand... | 281 | 0 |
"""simple docstring"""
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa:... | 369 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
FEATURE... | 281 | 0 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeniz... | 370 |
import math
def __lowerCamelCase ( UpperCAmelCase_ : float , UpperCAmelCase_ : float ):
"""simple docstring"""
return math.pow(UpperCAmelCase_ , 2 ) - a
def __lowerCamelCase ( UpperCAmelCase_ : float ):
"""simple docstring"""... | 281 | 0 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( _snake_case , _snake_case ... | 371 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : List[str] ... | 281 | 0 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _snake_case ( _snake_case , unittest.TestCase ):
SCREAMING_SNAKE_CASE__ = CTRLTokenizer
SCR... | 350 |
def __lowerCamelCase ( UpperCAmelCase_ : str ):
"""simple docstring"""
if n_term == "":
return []
a :list = []
for temp in range(int(UpperCAmelCase_ ) ):
series.append(F'''1/{temp + 1}''' if series else '''1''' ... | 281 | 0 |
import string
def __lowerCamelCase ( UpperCAmelCase_ : str ):
"""simple docstring"""
a :Optional[Any] = ''''''
for i in sequence:
a :List[Any] = ord(UpperCAmelCase_ )
if 65 <= extract <= 90:
ou... | 351 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffuse... | 281 | 0 |
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from transformers.utils import... | 352 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
snake_case : Any = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ['''paws''', ''... | 281 | 0 |
from timeit import timeit
snake_case : Tuple = {
'''MALAYALAM''': True,
'''String''': False,
'''rotor''': True,
'''level''': True,
'''A''': True,
'''BB''': True,
'''ABC''': False,
'''amanaplanacanalpanama''': True, # "a man a plan a canal panama"
}
# Ensure our test dat... | 353 |
from ...configuration_utils import PretrainedConfig
class _snake_case ( _snake_case ):
SCREAMING_SNAKE_CASE__ = 'bert-generation'
def __init__( self , _lowerCamelCase=5_0358 , _lowerCamelCase=1024 , _lowerCamelCase=24 , _lowerCamelCase=16 , _lowerCamelCase=4096 , _lowerCamelCase="g... | 281 | 0 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepInverseScheduler,
DPM... | 354 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __lowerCamelCase ( UpperCAmelCase_ : dict ):
"""... | 281 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : Any = logging.get_logger(__name__)
snake_case : Tuple = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/m... | 355 |
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
snake_case : Optional[Any] = logging.get_logger(__name__)
snake_case : Dict = {
... | 281 | 0 |
import math
def __lowerCamelCase ( UpperCAmelCase_ : float , UpperCAmelCase_ : float ):
"""simple docstring"""
return math.pow(UpperCAmelCase_ , 2 ) - a
def __lowerCamelCase ( UpperCAmelCase_ : float ):
"""simple docstring"""... | 356 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case : Any = {'''configuration_van''': ['''VAN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VanConfig''']}
try:
if not is_torch_available():
raise... | 281 | 0 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...tes... | 357 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 100 ):
"""simple docstring"""
a :List[Any] = 0
a :List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_int... | 281 | 0 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torc... | 358 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case : List[str] = logging.get_logger(__name__)
snake_case : Optional[Any] = {
'''vocab_file''': '''vocab... | 281 | 0 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'''kwargs, expected''' , [
({'''num_shards''': 0, '''max_num_jobs''': 1}, []),
({'''num_shards''': 10, '''max_num_jobs''': 1}, [range(10 )]),... | 359 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 281 | 0 |
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 SPIECE_UNDERLINE, logging
snake_case : Dict = logging.get_logger(__name__)
... | 360 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...tes... | 281 | 0 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
snake_case : Tuple = logging.get_logger(__name__)
class _snake_case ( _snake_case ):
def __init__( self , *_lowerCamelCase , **_lowerCamelCase ):
warnings.warn(
... | 361 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
depreca... | 281 | 0 |
"""simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils... | 362 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, tor... | 281 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class _snake_case ( _snak... | 363 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 281 | 0 |
import json
import sys
def __lowerCamelCase ( UpperCAmelCase_ : Dict , UpperCAmelCase_ : Optional[int] ):
"""simple docstring"""
with open(UpperCAmelCase_ , encoding='''utf-8''' ) as f:
a :List[str] = json.load(UpperCAmelCase_ ... | 364 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _sn... | 281 | 0 |
def __lowerCamelCase ( UpperCAmelCase_ : int = 100_0000 ):
"""simple docstring"""
a :int = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit ... | 365 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
snake_case : List[Any] = get_tests_dir('''fixtures/test_sentenc... | 281 | 0 |
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