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 |
|---|---|---|---|---|
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 ( _lowerCamelCase ,_low... | 701 | 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
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
lowerCAmelCase__ : int = ... | 699 | 0 |
# Copyright 2021 The HuggingFace 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... | 702 | import numpy as np
import qiskit
def UpperCamelCase__ ( A__ = 8 , A__ = None ) -> str:
snake_case__ : Optional[int] = np.random.default_rng(seed=A__ )
# Roughly 25% of the qubits will contribute to the key.
# So we take more than we need.
sn... | 699 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 703 | def UpperCamelCase__ ( A__ , A__ , A__ ) -> int:
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case__ : Dict = _modexpt(A__ , exponent // 2 , A__ ) % modulo_value
return (x * x) % modulo_value
... | 699 | 0 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate im... | 704 | # 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 c... | 699 | 0 |
class __snake_case :
def __init__( self , __UpperCamelCase ) -> None:
'''simple docstring'''
snake_case__ : Tuple = len(__UpperCamelCase )
snake_case__ : List[Any] = [0] * len_array
... | 705 | def UpperCamelCase__ ( A__ ) -> list[int]:
if length <= 0 or not isinstance(A__ , A__ ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(A__ )]
if __name__ == "__main__":
print(hexagonal_numbers(lengt... | 699 | 0 |
import torch
from transformers import AutoModel
class __snake_case ( torch.nn.Module ):
def __init__( self , __UpperCamelCase="sayef/fsner-bert-base-uncased" ) -> List[str]:
'''simple docstring'''
super(__UpperCamelCase ... | 706 | import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmen... | 699 | 0 |
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase__ : List[Any] = ... | 707 | from collections import namedtuple
lowerCAmelCase__ : Union[str, Any] = namedtuple('''from_to''', '''from_ to''')
lowerCAmelCase__ : Tuple = {
'''cubicmeter''': from_to(1, 1),
'''litre''': from_to(0.0_01, 10_00),
'''kilolitre''': from_to(1, 1),
'''gallon''': from_to(0.0_04_54... | 699 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __snake_case ( _lowerCamelCase ):
__lowerCamelCase = ["""image_processor""", """tokenizer"""]
__lowerCamelCase = """CLIPIma... | 708 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Tuple = logging.get_logger(__name__)
lowerCAmelCase__ : Union[str, An... | 699 | 0 |
from __future__ import annotations
import math
def UpperCamelCase__ ( A__ , A__ ) -> float:
snake_case__ : Dict = u
for i in range(1 , A__ ):
snake_case__ : List[str] = temp * (u - i)
return temp
def Upper... | 709 | import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer,... | 699 | 0 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
lowerCAmelCase__ : Any = logging.getLogger(__name__)
@dataclass
class __snak... | 710 | import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMSchedul... | 699 | 0 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerCAmelCase__ : List[Any] = datasets.utils.logging.get... | 711 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 699 | 0 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmentation,
C... | 712 | from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class __snake_case :
__lowerCamelCase = field(
metadata={"""help""": ... | 699 | 0 |
from math import sqrt
def UpperCamelCase__ ( A__ ) -> bool:
assert isinstance(A__ , A__ ) and (
number >= 0
), "'number' must been an int and positive"
snake_case__ : List[Any] = True
# 0 and 1 are none primes.
if number <= 1:
... | 713 | import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModel... | 699 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase__ : int = {
'''configuration_swiftformer''': [
'''SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SwiftFormerConfig''',
... | 714 | from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
lowerCAmelCase__ : List[Any] = datasets.utils.logging.get_logger(__name__)
class __snake_case ( folder_based_builder.FolderBasedBuild... | 699 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import... | 715 | 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_GUIDED_IM... | 699 | 0 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer,... | 716 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase__ : List[Any] = ... | 699 | 0 |
import datasets
lowerCAmelCase__ : str = '''\
@InProceedings{conneau2018xnli,
author = "Conneau, Alexis
and Rinott, Ruty
and Lample, Guillaume
and Williams, Adina
and Bowman, Samuel R.
and Schwenk, Holger
... | 717 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCAmelCase__ : List[str] = HfApi()
lowerCAmelCase__ : str = {}
# fmt: off
lowerCAmelCase__ : int = torch.tensor([
-0.75_15, -1.68_83, 0.24_20, 0.03_00, 0.63_47, 1.34_33, -1... | 699 | 0 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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, random_attention_ma... | 718 | import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
class __snake_case ( _lowerCamelCase ):
def __init__( self , *__UpperCamelCase , **__Up... | 699 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
lowerCAmelCase... | 719 | import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerCAmelCase__ : List[Any] = datasets.uti... | 699 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add_start_docstrings_to_... | 720 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ : Any = {'''configuration_xglm''': [''... | 699 | 0 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCamelCase__ ( A__ , A__ , A__ ) -> Any:
# Initialise PyTorch model
snake_case__ :... | 721 | from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCAmelCase__ : Dict = 2_00
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and ... | 699 | 0 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_com... | 700 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
lowerCAmelCase__ : Optional[int] = TypeVar('''T''')
class __snake_case ( Generic[T] ):
def __init__( self , __UpperCamelCase ) -> Any:
... | 699 | 0 |
import random
from typing import Any
def UpperCamelCase__ ( A__ ) -> list[Any]:
for _ in range(len(A__ ) ):
snake_case__ : List[Any] = random.randint(0 , len(A__ ) - 1 )
snake_case__ : Union[str, Any] = rand... | 701 | 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
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
lowerCAmelCase__ : int = ... | 699 | 0 |
from math import isqrt
def UpperCamelCase__ ( A__ ) -> list[int]:
snake_case__ : Optional[Any] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , A__ , A__ ... | 702 | import numpy as np
import qiskit
def UpperCamelCase__ ( A__ = 8 , A__ = None ) -> str:
snake_case__ : Optional[int] = np.random.default_rng(seed=A__ )
# Roughly 25% of the qubits will contribute to the key.
# So we take more than we need.
sn... | 699 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( A__ , A__ ) -> str:
return "\n".join(
F"""{number} * {i} = {number * i}""" for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication_table(number=5, number_of_ter... | 703 | def UpperCamelCase__ ( A__ , A__ , A__ ) -> int:
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case__ : Dict = _modexpt(A__ , exponent // 2 , A__ ) % modulo_value
return (x * x) % modulo_value
... | 699 | 0 |
from timeit import timeit
def UpperCamelCase__ ( A__ ) -> int:
'''simple docstring'''
if number < 0:
raise ValueError('the value of input must not be negative' )
snake_case__ : Optional[Any] = 0
while number:
number &= n... | 704 | # 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 c... | 699 | 0 |
def UpperCamelCase__ ( A__ = 1000 ) -> int:
return sum(e for e in range(3 , A__ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F'''{solution() = }''')
| 705 | def UpperCamelCase__ ( A__ ) -> list[int]:
if length <= 0 or not isinstance(A__ , A__ ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(A__ )]
if __name__ == "__main__":
print(hexagonal_numbers(lengt... | 699 | 0 |
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
lowerCAmelCase__ : List[Any] = datasets.utils.logging.get_logger(__name__)
class __snake_case ( folder_based_builder.FolderBasedBuild... | 706 | import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmen... | 699 | 0 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_... | 707 | from collections import namedtuple
lowerCAmelCase__ : Union[str, Any] = namedtuple('''from_to''', '''from_ to''')
lowerCAmelCase__ : Tuple = {
'''cubicmeter''': from_to(1, 1),
'''litre''': from_to(0.0_01, 10_00),
'''kilolitre''': from_to(1, 1),
'''gallon''': from_to(0.0_04_54... | 699 | 0 |
from __future__ import annotations
def UpperCamelCase__ ( A__ , A__ ) -> bool:
snake_case__ : Optional[Any] = get_failure_array(A__ )
# 2) Step through text searching for pattern
snake_case__ : Any = 0, 0 # inde... | 708 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Tuple = logging.get_logger(__name__)
lowerCAmelCase__ : Union[str, An... | 699 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def UpperCamelCase__ ( A__ , A__=1000 ) -> int:
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
snake_case__ : Optional[int] = n - 1
snake... | 709 | import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer,... | 699 | 0 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
cla... | 710 | import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMSchedul... | 699 | 0 |
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_available():
from transfo... | 711 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 699 | 0 |
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from tran... | 712 | from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class __snake_case :
__lowerCamelCase = field(
metadata={"""help""": ... | 699 | 0 |
from copy import deepcopy
class __snake_case :
def __init__( self , __UpperCamelCase = None , __UpperCamelCase = None ) -> None:
'''simple docstring'''
if arr is None and size is not None:
snake_case__ : List[Any] = s... | 713 | import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModel... | 699 | 0 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCAmelCase__ : List[str] = HfApi()
lowerCAmelCase__ : str = {}
# fmt: off
lowerCAmelCase__ : int = torch.tensor([
-0.75_15, -1.68_83, 0.24_20, 0.03_00, 0.63_47, 1.34_33, -1... | 714 | from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
lowerCAmelCase__ : List[Any] = datasets.utils.logging.get_logger(__name__)
class __snake_case ( folder_based_builder.FolderBasedBuild... | 699 | 0 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig... | 715 | 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_GUIDED_IM... | 699 | 0 |
class __snake_case :
def __init__( self ) -> List[str]:
'''simple docstring'''
snake_case__ : str = 0
snake_case__ : int = 0
snake_case__ : int = {}
d... | 716 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase__ : List[Any] = ... | 699 | 0 |
import numpy
class __snake_case :
def __init__( self , __UpperCamelCase , __UpperCamelCase ) -> None:
'''simple docstring'''
snake_case__ : Dict = input_array
# Random initial weights are assig... | 717 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCAmelCase__ : List[str] = HfApi()
lowerCAmelCase__ : str = {}
# fmt: off
lowerCAmelCase__ : int = torch.tensor([
-0.75_15, -1.68_83, 0.24_20, 0.03_00, 0.63_47, 1.34_33, -1... | 699 | 0 |
def UpperCamelCase__ ( A__ ) -> list[int]:
if length <= 0 or not isinstance(A__ , A__ ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(A__ )]
if __name__ == "__main__":
print(hexagonal_numbers(length=5... | 718 | import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
class __snake_case ( _lowerCamelCase ):
def __init__( self , *__UpperCamelCase , **__Up... | 699 | 0 |
from cva import destroyAllWindows, imread, imshow, waitKey
def UpperCamelCase__ ( A__ ) -> str:
# getting number of pixels in the image
snake_case__ : int = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
for i in range(A__ ):
... | 719 | import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerCAmelCase__ : List[Any] = datasets.uti... | 699 | 0 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...test_c... | 720 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ : Any = {'''configuration_xglm''': [''... | 699 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, ski... | 721 | from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCAmelCase__ : Dict = 2_00
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and ... | 699 | 0 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __snake_case ( yaml.SafeLoader ):
def __a ( self , __UpperCamelCase ) -> Any:
'''simple docstring'''
... | 700 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
lowerCAmelCase__ : Optional[int] = TypeVar('''T''')
class __snake_case ( Generic[T] ):
def __init__( self , __UpperCamelCase ) -> Any:
... | 699 | 0 |
from __future__ import annotations
import math
from collections.abc import Callable
def UpperCamelCase__ ( A__ , A__ , A__ , A__ = 100 , ) -> float:
snake_case__ : Optional[int] = x_start
snake_case__ : Any = fnc(A__ ... | 701 | 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
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
lowerCAmelCase__ : int = ... | 699 | 0 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import C... | 702 | import numpy as np
import qiskit
def UpperCamelCase__ ( A__ = 8 , A__ = None ) -> str:
snake_case__ : Optional[int] = np.random.default_rng(seed=A__ )
# Roughly 25% of the qubits will contribute to the key.
# So we take more than we need.
sn... | 699 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, 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()... | 703 | def UpperCamelCase__ ( A__ , A__ , A__ ) -> int:
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case__ : Dict = _modexpt(A__ , exponent // 2 , A__ ) % modulo_value
return (x * x) % modulo_value
... | 699 | 0 |
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ..... | 704 | # 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 c... | 699 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ : Dict = {
'''configuration_funnel''': ['''FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Fun... | 705 | def UpperCamelCase__ ( A__ ) -> list[int]:
if length <= 0 or not isinstance(A__ , A__ ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(A__ )]
if __name__ == "__main__":
print(hexagonal_numbers(lengt... | 699 | 0 |
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tests
from os.path import j... | 706 | import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmen... | 699 | 0 |
from collections import namedtuple
lowerCAmelCase__ : Union[str, Any] = namedtuple('''from_to''', '''from_ to''')
lowerCAmelCase__ : Tuple = {
'''cubicmeter''': from_to(1, 1),
'''litre''': from_to(0.0_01, 10_00),
'''kilolitre''': from_to(1, 1),
'''gallon''': from_to(0.0_04_54... | 707 | from collections import namedtuple
lowerCAmelCase__ : Union[str, Any] = namedtuple('''from_to''', '''from_ to''')
lowerCAmelCase__ : Tuple = {
'''cubicmeter''': from_to(1, 1),
'''litre''': from_to(0.0_01, 10_00),
'''kilolitre''': from_to(1, 1),
'''gallon''': from_to(0.0_04_54... | 699 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
... | 708 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Tuple = logging.get_logger(__name__)
lowerCAmelCase__ : Union[str, An... | 699 | 0 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand... | 709 | import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer,... | 699 | 0 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch... | 710 | import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMSchedul... | 699 | 0 |
from typing import Dict, Optional
import numpy as np
import datasets
lowerCAmelCase__ : Optional[Any] = '''
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or mu... | 711 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 699 | 0 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('''Googling.....''')
lowerCAmelCase__ : Tuple = '''https://www.google.com/search?q=''' + ''' '''.join(sys.argv[1:])
lowerCAmelCase__ : List[Any] = ... | 712 | from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class __snake_case :
__lowerCamelCase = field(
metadata={"""help""": ... | 699 | 0 |
def UpperCamelCase__ ( A__ ) -> bool:
snake_case__ : Optional[int] = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 713 | import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModel... | 699 | 0 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_... | 714 | from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
lowerCAmelCase__ : List[Any] = datasets.utils.logging.get_logger(__name__)
class __snake_case ( folder_based_builder.FolderBasedBuild... | 699 | 0 |
def UpperCamelCase__ ( ) -> int:
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(A__ , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(F'''{solution() = }''... | 715 | 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_GUIDED_IM... | 699 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enabl... | 716 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase__ : List[Any] = ... | 699 | 0 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='''%(message)s''')
def UpperCamelCase__ ( A__ ) -> np.ndarray:
return input_array.reshape((input_array.size, 1) )
def UpperCamelCase__ ( A_... | 717 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCAmelCase__ : List[str] = HfApi()
lowerCAmelCase__ : str = {}
# fmt: off
lowerCAmelCase__ : int = torch.tensor([
-0.75_15, -1.68_83, 0.24_20, 0.03_00, 0.63_47, 1.34_33, -1... | 699 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : str = logging.get_logger(__name__)
lowerCAmelCase__ : List[str] = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
# See all Cvt model... | 718 | import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
class __snake_case ( _lowerCamelCase ):
def __init__( self , *__UpperCamelCase , **__Up... | 699 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ : Tuple = {
'''configuration_distilbert''': [
'''DISTILBERT_PRETRAINED_... | 719 | import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerCAmelCase__ : List[Any] = datasets.uti... | 699 | 0 |
# Copyright 2023 The HuggingFace 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 applicabl... | 720 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ : Any = {'''configuration_xglm''': [''... | 699 | 0 |
import os
from distutils.util import strtobool
def UpperCamelCase__ ( A__ , A__ ) -> Optional[int]:
for e in env_keys:
snake_case__ : Optional[int] = int(os.environ.get(A__ , -1 ) )
if val >= 0:
return val
return... | 721 | from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCAmelCase__ : Dict = 2_00
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and ... | 699 | 0 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowerCAmelCase__ : List[str] = 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: E... | 700 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
lowerCAmelCase__ : Optional[int] = TypeVar('''T''')
class __snake_case ( Generic[T] ):
def __init__( self , __UpperCamelCase ) -> Any:
... | 699 | 0 |
import numpy as np
import qiskit
def UpperCamelCase__ ( A__ = 8 , A__ = None ) -> str:
snake_case__ : Optional[int] = np.random.default_rng(seed=A__ )
# Roughly 25% of the qubits will contribute to the key.
# So we take more than we need.
sn... | 701 | 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
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
lowerCAmelCase__ : int = ... | 699 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 702 | import numpy as np
import qiskit
def UpperCamelCase__ ( A__ = 8 , A__ = None ) -> str:
snake_case__ : Optional[int] = np.random.default_rng(seed=A__ )
# Roughly 25% of the qubits will contribute to the key.
# So we take more than we need.
sn... | 699 | 0 |
'''simple docstring'''
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
t... | 703 | def UpperCamelCase__ ( A__ , A__ , A__ ) -> int:
if exponent == 1:
return base
if exponent % 2 == 0:
snake_case__ : Dict = _modexpt(A__ , exponent // 2 , A__ ) % modulo_value
return (x * x) % modulo_value
... | 699 | 0 |
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
requi... | 704 | # 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 c... | 699 | 0 |
import random
def UpperCamelCase__ ( A__ , A__ ) -> tuple:
snake_case__ : Tuple = [], [], []
for element in data:
if element < pivot:
less.append(A__ )
elif element > pivot:
greater.append(A__ )
el... | 705 | def UpperCamelCase__ ( A__ ) -> list[int]:
if length <= 0 or not isinstance(A__ , A__ ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(A__ )]
if __name__ == "__main__":
print(hexagonal_numbers(lengt... | 699 | 0 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCAmelCase__ : List[str] = {
'''text_branch''': '''text_model''',
'''audio_branch''': '''audio_model.audio_encoder''',
'''attn''': '''attenti... | 706 | import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmen... | 699 | 0 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
lowerCAmelCase__ : ... | 707 | from collections import namedtuple
lowerCAmelCase__ : Union[str, Any] = namedtuple('''from_to''', '''from_ to''')
lowerCAmelCase__ : Tuple = {
'''cubicmeter''': from_to(1, 1),
'''litre''': from_to(0.0_01, 10_00),
'''kilolitre''': from_to(1, 1),
'''gallon''': from_to(0.0_04_54... | 699 | 0 |
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def UpperCamelCase__ ( A__ , A__ , A__ = 10**-10 ) -> float:
snake_case__ : List[Any] = a
while True:
s... | 708 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Tuple = logging.get_logger(__name__)
lowerCAmelCase__ : Union[str, An... | 699 | 0 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCamelCase__ ( A__ , A__ , A__ ) -> List[str]:
# Initialise PyTorch model
... | 709 | import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer,... | 699 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( A__ , A__ ) -> str:
if not (isinstance(A__ , A__ ) and isinstance(A__ , A__ )):
raise ValueError('longest_common_substring() takes two strings for inputs' )
snake_case__ : Optiona... | 710 | import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMSchedul... | 699 | 0 |
from __future__ import annotations
lowerCAmelCase__ : str = 1.6_021E-19 # units = C
def UpperCamelCase__ ( A__ , A__ , A__ , ) -> tuple[str, float]:
if (conductivity, electron_conc, mobility).count(0 ) != 1:
raise ValueError('You cannot supply more or les... | 711 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 699 | 0 |
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from torch.utils.data import DataLoade... | 712 | from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class __snake_case :
__lowerCamelCase = field(
metadata={"""help""": ... | 699 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, tor... | 713 | import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModel... | 699 | 0 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase__ : List[Any] = get_tests_dir('''fixt... | 714 | from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
lowerCAmelCase__ : List[Any] = datasets.utils.logging.get_logger(__name__)
class __snake_case ( folder_based_builder.FolderBasedBuild... | 699 | 0 |
class __snake_case :
def __init__( self , __UpperCamelCase ) -> List[Any]:
'''simple docstring'''
snake_case__ : Optional[int] = val
snake_case__ : Dict = None
snake_case__ ... | 715 | 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_GUIDED_IM... | 699 | 0 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
lowerCAmelCase__ : int = logging.get_logger(__name__)
lowerCAmelCase__ : Any = {
'''post_extract_proj''': '... | 716 | import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase__ : List[Any] = ... | 699 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Tuple = logging.get_logger(__name__)
lowerCAmelCase__ : Union[str, ... | 717 | import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCAmelCase__ : List[str] = HfApi()
lowerCAmelCase__ : str = {}
# fmt: off
lowerCAmelCase__ : int = torch.tensor([
-0.75_15, -1.68_83, 0.24_20, 0.03_00, 0.63_47, 1.34_33, -1... | 699 | 0 |
import numpy as np
lowerCAmelCase__ : Any = [
['''a''', '''b''', '''c''', '''d''', '''e'''],
['''f''', '''g''', '''h''', '''i''', '''k'''],
['''l''', '''m''', '''n''', '''o''', '''p'''],
['''q''', '''r''', '''s''', '''t''', '''u'''],
['''v''', '''w''', '''x''', '''y''', '''z'''],
]... | 718 | import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
lowerCAmelCase__ : Dict = logging.get_logger(__name__)
class __snake_case ( _lowerCamelCase ):
def __init__( self , *__UpperCamelCase , **__Up... | 699 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
... | 719 | import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerCAmelCase__ : List[Any] = datasets.uti... | 699 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, Distr... | 720 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ : Any = {'''configuration_xglm''': [''... | 699 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ : List[str] = {'''configuration_plbart''': ['''PLBART_PRETRAINED_CONFIG_ARCHIVE_MA... | 721 | from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCAmelCase__ : Dict = 2_00
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and ... | 699 | 0 |
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