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 hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_timm,... | 713 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 77 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDI... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcessor, BlipImageProcess... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''U... | 77 | 0 |
from __future__ import annotations
from collections.abc import Iterator
class _A:
"""simple docstring"""
def __init__( self , _A ):
__A : str = value
__A : Dict = None
__A : Tuple = None
class _A:... | 716 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 0 |
'''simple docstring'''
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from acceler... | 717 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> list:
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
__A : Optional[int] ... | 77 | 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
UpperCAmelCase : Dict = '▁'
UpperCAmelCase : List[str] = {'vocab_file': 'spiec... | 718 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priori... | 77 | 0 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
UpperCAmelCase : ... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, req... | 720 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 0 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
r... | 721 |
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 _A( nn.Module ):
... | 77 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( a , a ) -> float:
if digit_amount > 0:
return round(number - int(a ) , a )
return number - int(a )
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolat... | 700 |
# 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 app... | 77 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils im... | 701 |
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
UpperCAmelCase : Dic... | 77 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import logging
... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : list[list[int]] = [[0 for _ in range(a )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__A : Optional[int] = 1
for n in range(m + 1 ):
for k in range(1 , a ):
... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
UpperCAmelCase : Lis... | 704 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, 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 ConfigTester
fr... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a = 10**12 ) -> int:
__A : Union[str, Any] = 1
__A : Optional[int] = 0
__A : int = 1
__A : Optional[int] = 1
while numerator <= 2 * min_total - 1:
prev_nu... | 705 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase : str = HfApi()
UpperCAmelCase : List[str] = {}
# fmt: off
UpperCAmelCase : Optional[Any] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1... | 77 | 0 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def _SCREAMING_SNAKE_CASE ( a , a ... | 706 |
import numpy as np
from PIL import Image
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> np.ndarray:
__A : Union[str, Any] = np.array(a )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is not a square matrix' ... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a ) -> str:
__A : List[str] = ''
for word_or_phrase in separated:
if not isinstance(a , a ):
raise Exception('join() accepts only strings to be joined' )
joined += word_or_ph... | 707 |
from __future__ import annotations
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( a , a , a , a = 1_00 , ) -> float:
__A : Any = x_start
__A : List[str] = fnc(a )
__A : Optional[Any] ... | 77 | 0 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def _SCREAMING_SNAKE_CASE ( a ) -> Any:
__A : str = [
'decoder.version',
'decoder.output_projection.weight'... | 708 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _SCREAMING_SNAKE_CASE ( ) -> None:
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print(... | 77 | 0 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = ... | 709 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 77 | 0 |
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
if is_torch_available():
import t... | 710 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelC... | 77 | 0 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, t... | 711 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
debug_launcher(test_script.main )
de... | 77 | 0 |
from collections import namedtuple
UpperCAmelCase : Any = namedtuple('''from_to''', '''from_ to''')
UpperCAmelCase : Any = {
'''cubicmeter''': from_to(1, 1),
'''litre''': from_to(0.001, 10_00),
'''kilolitre''': from_to(1, 1),
'''gallon''': from_to(0.00454, 264.172),... | 712 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 77 | 0 |
import math
def _SCREAMING_SNAKE_CASE ( a = 1_00 ) -> int:
__A : Union[str, Any] = sum(i * i for i in range(1 , n + 1 ) )
__A : Optional[int] = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
r... | 713 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 77 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_camembert i... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 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
UpperCAmelCase : str = '''sshleifer/bart-tiny-random'''... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''U... | 77 | 0 |
import torch
from diffusers import DiffusionPipeline
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , _A , _A ):
super().__init__()
self.register_modules(unet=_A , scheduler=_A )
def __call__( self ):
... | 716 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 0 |
'''simple docstring'''
from __future__ import annotations
UpperCAmelCase : int = list[list[int]]
# assigning initial values to the grid
UpperCAmelCase : Matrix = [
[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, ... | 717 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> list:
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
__A : Optional[int] ... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCAmelCase : List[str] = {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
Upper... | 718 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priori... | 77 | 0 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Fla... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _A( yaml.SafeLoader ):
"""simple docstring"""
def UpperCAmelCase_ ( self , _A ):
__A : Optional[Any] = [self.constructed_objects[key... | 720 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 0 |
import os
from collections.abc import Iterator
def _SCREAMING_SNAKE_CASE ( a = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(a ):
__A : Optional[Any] = [d for d in dir_names if d != 'scripts' and d[0] not in '._']
... | 721 |
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 _A( nn.Module ):
... | 77 | 0 |
'''simple docstring'''
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from p... | 700 |
# 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 app... | 77 | 0 |
from __future__ import annotations
from random import random
class _A:
"""simple docstring"""
def __init__( self , _A = None ):
__A : List[Any] = value
__A : Any = random()
__A : Node | None = None
... | 701 |
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
UpperCAmelCase : Dic... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priority... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a ) -> str:
__A : list[list[str]] = [[] for _ in range(a )]
__A : Optional[Any] = key - 1
if key <= 0:
raise ValueError('Height of grid can\'t be 0 or negative' )
if key == 1 o... | 704 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, 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 ConfigTester
fr... | 77 | 0 |
from __future__ import annotations
from random import choice
def _SCREAMING_SNAKE_CASE ( a ) -> int:
return choice(a )
def _SCREAMING_SNAKE_CASE ( a , a ) -> int:
__A : int = random_pivot(a )
# partition... | 705 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase : str = HfApi()
UpperCAmelCase : List[str] = {}
# fmt: off
UpperCAmelCase : Optional[Any] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1... | 77 | 0 |
# Copyright 2021 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 b... | 706 |
import numpy as np
from PIL import Image
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> np.ndarray:
__A : Union[str, Any] = np.array(a )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is not a square matrix' ... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a ) -> str:
__A : int = len(a )
__A : int = len(a )
__A : int = (
first_str_length if first_str_length > second_str_length else second_str_length
)
__A :... | 707 |
from __future__ import annotations
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( a , a , a , a = 1_00 , ) -> float:
__A : Any = x_start
__A : List[str] = fnc(a )
__A : Optional[Any] ... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase : Tuple = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritte... | 708 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _SCREAMING_SNAKE_CASE ( ) -> None:
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print(... | 77 | 0 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelC... | 709 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ : Any = logging.get_logger(__name__)
UpperCAmelCase__ : Dict = {
'''uw-madison/mra-base-512-4''': '''https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json''',
... | 710 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelC... | 77 | 0 |
from __future__ import annotations
UpperCAmelCase : Tuple = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
UpperCAmelCase : List[Any] = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def _SCREAMING_SNAKE_CASE ( a ) -> list[float... | 711 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
debug_launcher(test_script.main )
de... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( ) -> int:
return [
a * b * (10_00 - a - b)
for a in range(1 , 9_99 )
for b in range(a , 9_99 )
if (a * a + b * b == (10_00 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(F"""{solution() = }... | 712 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 77 | 0 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers.models.b... | 713 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 77 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Any = {
'''configuration_deberta''': ['''DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Deberta... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''U... | 77 | 0 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 716 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _A( metaclass=snake_case__ ):
"""simple docstring"""
UpperCamelCase : Optional[Any] = ['''torch''']
def __init__( self , *_A , **_A ):
requires_back... | 717 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> list:
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
__A : Optional[int] ... | 77 | 0 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
from diffuse... | 718 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priori... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
'''... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
__A : Any = get_activation('swish' )
self.asse... | 720 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 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_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCas... | 721 |
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 _A( nn.Module ):
... | 77 | 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
if is_tor... | 700 |
# 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 app... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a ) -> str:
if not isinstance(a , a ):
raise ValueError('iterations must be defined as integers' )
if not isinstance(a , a ) or not number >= 1:
raise ValueError(
'starting number mu... | 701 |
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
UpperCAmelCase : Dic... | 77 | 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,... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
import os
import sys
import unittest
UpperCAmelCase : 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 get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_ma... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
DPR_CONTEXT_EN... | 704 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, 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 ConfigTester
fr... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase : Tuple = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json''',... | 705 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase : str = HfApi()
UpperCAmelCase : List[str] = {}
# fmt: off
UpperCAmelCase : Optional[Any] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1... | 77 | 0 |
from __future__ import annotations
from cmath import sqrt
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> tuple[complex, complex]:
if a == 0:
raise ValueError('Coefficient \'a\' must not be zero.' )
__A : List[str] = b * b - 4 * a *... | 706 |
import numpy as np
from PIL import Image
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> np.ndarray:
__A : Union[str, Any] = np.array(a )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is not a square matrix' ... | 77 | 0 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> Union[str, Any]:
__A : int = ('dense.weight', 'attention.self.query', 'attention.self.k... | 707 |
from __future__ import annotations
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( a , a , a , a = 1_00 , ) -> float:
__A : Any = x_start
__A : List[str] = fnc(a )
__A : Optional[Any] ... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[Any] = [1]
__A : Union[str, Any] = 0, 0, 0
__A : Optional[int] = ugly_nums[ia] * 2
__A : Any = ugly_nums[ia] * 3
__A : str = ... | 708 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _SCREAMING_SNAKE_CASE ( ) -> None:
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print(... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a ) -> bool:
if p < 2:
raise ValueError('p should not be less than 2!' )
elif p == 2:
return True
__A : List[Any] = 4
__A : Any = (1 << p) - 1
for _ in range(p ... | 709 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 77 | 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
UpperCAmelCase__ : D... | 710 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelC... | 77 | 0 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _A( snake_case__ , unittest.TestCase ):
"... | 711 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
debug_launcher(test_script.main )
de... | 77 | 0 |
from __future__ import annotations
from math import gcd
def _SCREAMING_SNAKE_CASE ( a , a = 2 , a = 1 , a = 3 , ) -> int | None:
# A value less than 2 can cause an infinite loop in the algorithm.
if num < 2:
raise ValueError('The input value ca... | 712 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 77 | 0 |
from __future__ import annotations
import time
UpperCAmelCase : Optional[int] = list[tuple[int, int]]
UpperCAmelCase : str = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1... | 713 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a ) -> str:
return " ".join(
''.join(word[::-1] ) if len(a ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words('''Hey wollef sroirraw'''))
... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 0 |
import sys
def _SCREAMING_SNAKE_CASE ( a ) -> Dict:
__A : List[Any] = len(a )
__A : int = [[0 for x in range(a )] for x in range(a )]
__A : Any = [[0 for x in range(a )] for x in range(a )]
... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''U... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Union[str, Any] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-... | 716 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod... | 717 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> list:
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
__A : Optional[int] ... | 77 | 0 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
UpperCAmelCase : Optional[int] = logging.getLogger(__name__)
class _A:
"""simple docstring"""
def __init__( ... | 718 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priori... | 77 | 0 |
# 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 b... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase : Union[str, Any] = {
'''configuration_maskformer''': ['''MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MaskFormerConfig'''],
'''c... | 720 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 0 |
import requests
from bsa import BeautifulSoup
def _SCREAMING_SNAKE_CASE ( a = "AAPL" ) -> str:
__A : int = F"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
__A : Any = BeautifulSoup(requests.get(a ).text , 'html.pa... | 721 |
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 _A( nn.Module ):
... | 77 | 0 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_avail... | 700 |
# 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 app... | 77 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 701 |
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
UpperCAmelCase : Dic... | 77 | 0 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import torc... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .to... | 703 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
UpperCAmelCase : Dict = ''''''
UpperCAmelCase : Union[str, Any] = ''''''
UpperCAmelCase : Optional[int] = ''''''
UpperCAmelCase : Union[str, Any] = 1 # (0 is vert... | 77 | 0 |
import re
def _SCREAMING_SNAKE_CASE ( a ) -> list:
return [char.split() for char in re.split(r'[^ a-z A-Z 0-9 \s]' , str_ )]
def _SCREAMING_SNAKE_CASE ( a ) -> str:
__A : Optional[Any] = split_input(str_ )
... | 704 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, 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 ConfigTester
fr... | 77 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
... | 705 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase : str = HfApi()
UpperCAmelCase : List[str] = {}
# fmt: off
UpperCAmelCase : Optional[Any] = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1... | 77 | 0 |
import requests
UpperCAmelCase : Dict = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def _SCREAMING_SNAKE_CASE ( a ) -> None:
# fetching a list of articles in json format
__A : Any = requests.get(_NEWS_API + bbc_... | 706 |
import numpy as np
from PIL import Image
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> np.ndarray:
__A : Union[str, Any] = np.array(a )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The input array is not a square matrix' ... | 77 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
'''google/realm-cc-news-pretrained-embedder''': (
'''https://huggingface.co/google/realm-cc-news-pretra... | 707 |
from __future__ import annotations
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( a , a , a , a = 1_00 , ) -> float:
__A : Any = x_start
__A : List[str] = fnc(a )
__A : Optional[Any] ... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
UpperCAmelCase : Optional[Any] = {
'''configuration_trocr''': ['''TROCR_PRETRAINED_CONFIG_ARCHIVE_MA... | 708 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _SCREAMING_SNAKE_CASE ( ) -> None:
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print(... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a ) -> str:
__A : Any = ''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def _SCREAMING_SNAKE_CASE ( a ... | 709 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 77 | 0 |
import math
import unittest
from transformers import BioGptConfig, 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_common import Mode... | 710 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelC... | 77 | 0 |
print((lambda quine: quine % quine)('''print((lambda quine: quine %% quine)(%r))'''))
| 711 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _A( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
debug_launcher(test_script.main )
de... | 77 | 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_av... | 712 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 77 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)... | 713 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 77 | 0 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 714 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _A( snake_case__ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase_ ( _A ):
raise NotImplementedError()
@abstractmethod
def UpperCAmelCas... | 77 | 0 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : List[st... | 715 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''U... | 77 | 0 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
UpperCAmelCase : int = logging.get_logger(__name__)
def _SCREAMING_SNAKE_CASE ( a , a ) ... | 716 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, ... | 77 | 0 |
'''simple docstring'''
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
UpperCAmelCase : Optional[int] = logging.getLogger()
... | 717 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( a , a ) -> list:
if len(a ) != 2 or len(a[0] ) != 2 or len(a ) != 2 or len(b[0] ) != 2:
raise Exception('Matrices are not 2x2' )
__A : Optional[int] ... | 77 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class _A( nn.Module ):
"""simple docstring"""
def __init__( self , _A = 16 , _A = 88 , _A = None , _A = 1 , _A = 0.0 , _A =... | 718 |
def _SCREAMING_SNAKE_CASE ( a ) -> int:
__A : List[str] = []
__A : Tuple = []
__A : Union[str, Any] = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
} # Priori... | 77 | 0 |
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
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
UpperCAmelCase : Dict ... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import TokenizerTesterMixi... | 720 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : List[str] = logging.get_log... | 77 | 0 |
def _SCREAMING_SNAKE_CASE ( a , a ) -> int:
if len(a ) != len(a ):
raise ValueError('String lengths must match!' )
__A : Tuple = 0
for chara, chara in zip(a , a ):
if chara != chara:
count ... | 721 |
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 _A( nn.Module ):
... | 77 | 0 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from... | 700 |
# 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 app... | 77 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Any = logging.get_logger(__name__)
UpperCAmelCase : Optional[int] = {
'''microsoft/unispeech-sat-base-100h-libri-ft''': (
'''https://hugg... | 701 |
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
UpperCAmelCase : Dic... | 77 | 0 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def _SCREAMING_SNAKE_CASE ( a , a , a ) -> Optional[int]:
__A : int = AutoConfig.from_pretrained(a )
__A : Union[str, Any] ... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
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