code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__UpperCAmelCase = logging.get_logger(__name__)
class __a... | 367 |
from datetime import datetime as dt
import os
from github import Github
__UpperCAmelCase = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def __UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
... | 28 | 0 |
import inspect
import unittest
from transformers import YolosConfig
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 ...test_mo... | 368 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 28 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__UpperCAmelCase = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenization_m2m_100': ['M... | 369 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 28 | 0 |
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : List[str] ) -> Union[str, Any]:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 0.00
lowerCAmelCase_ : Tuple = 0
for resistor in resistors:
if resistor <= 0:
... | 370 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class __a ( __Upper... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : str ) -> Tuple:
'''simple docstring'''
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(lowerCamelCase__ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__('doctes... | 371 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for non-integers""" )
eli... | 28 | 0 |
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, 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():
import j... | 350 |
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 ... | 28 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slo... | 351 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmelC... | 28 | 0 |
import math
import sys
def __UpperCamelCase ( lowercase__ : int ) -> Optional[Any]:
'''simple docstring'''
if number != int(UpperCAmelCase_ ):
raise ValueError("""the value of input must be a natural number""" )
if number < 0:
raise ValueError("""the... | 352 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get... | 353 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, ... | 354 |
from __future__ import annotations
from typing import Any
class __a :
def __init__( self : Dict , UpperCAmelCase : int = 6 ):
lowerCAmelCase_ : Node | None = None
lowerCAmelCase_ : Node | None = None
self.... | 28 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils im... | 355 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 28 | 0 |
from typing import Any
class __a :
def __init__( self : Optional[int] , UpperCAmelCase : int ):
lowerCAmelCase_ : Tuple = data
lowerCAmelCase_ : str = None
class __a :
... | 356 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__UpperCAmelCase = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioGptToke... | 357 |
from math import factorial, pi
def __UpperCamelCase ( lowercase__ : float , lowercase__ : int = 30 ) -> float:
'''simple docstring'''
if not isinstance(lowercase__ , (int, float) ):
raise ValueError("""maclaurin_sin() requires either an int or... | 28 | 0 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__UpperCAmelCase = 2_00
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and must be s... | 358 |
# 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... | 28 | 0 |
from collections.abc import Sequence
def __UpperCamelCase ( lowercase__ : Sequence[float] , lowercase__ : bool = False ) -> Optional[Any]:
'''simple docstring'''
if not arr:
return 0
lowerCAmelCase_ : str = 0 if allow_empty_subarrays else ... | 359 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig... | 28 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransformerConfig',
],
}
tr... | 360 |
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 Co... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowercase__ : Tuple ) -> str:
'''simple docstring'''
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__lowerCAmelCase , int(b / 2 ) ) * actual_power(__lowerCAmelCas... | 361 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Optional[Any] , *... | 28 | 0 |
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
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_confi... | 362 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __a ( __UpperCa... | 28 | 0 |
"""simple docstring"""
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : list[list[int]] ) -> bool:
'''simple docstring'''
lowerCAmelCase_ : str = len(lowercase__ )
# We need to create solution object to save path.
lowerCAmelCa... | 363 |
from math import ceil
def __UpperCamelCase ( lowercase__ : int = 1001 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : Optional[Any] = 2 ... | 28 | 0 |
import math
import random
def __UpperCamelCase ( lowercase__ : float , lowercase__ : bool = False ) -> float:
'''simple docstring'''
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
__UpperCAmelCase =... | 364 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowe... | 28 | 0 |
"""simple docstring"""
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
__UpperCAmelCase = logging.get_logger(__name__)
cl... | 365 |
def __UpperCamelCase ( lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase_ : Any = 0
for ch in input_str:
lowerCAmelCase_ : Any = ord(lowercase__ )
lowerCAmelCase_ : Dict = pow(2 , lowerc... | 28 | 0 |
class __a :
def __init__( self : List[Any] , UpperCAmelCase : list[int] ):
lowerCAmelCase_ : List[Any] = len(UpperCamelCase__ )
lowerCAmelCase_ : Tuple = [0] * len_array
if len_array > 0:
... | 366 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__UpperCAmelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__UpperCAmelCase... | 28 | 0 |
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from transformers.file_uti... | 367 |
from datetime import datetime as dt
import os
from github import Github
__UpperCAmelCase = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def __UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
... | 28 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json',
# See all GPTNeoX models at https://h... | 368 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 28 | 0 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.config... | 369 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 28 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'asapp/sew-tiny-100k': 'https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json',
# See all... | 370 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class __a ( __Upper... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : Union[str, Any] ) -> Optional[int]:
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = abs(__a )
lowerCAmelCase_ : Dict = 0
while n > 0:
res += n % 10
n //= 10
return ... | 371 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for non-integers""" )
eli... | 28 | 0 |
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : int | float | str , lowercase__ : int | float | str ) -> Tuple:
'''simple docstring'''
if nth_term == "":
return [""]
lowerCAmelCase_ : str = int(A__ )
lowerCA... | 350 |
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 ... | 28 | 0 |
import argparse
import gc
import json
import os
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 Accele... | 351 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmelC... | 28 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class __a ( __UpperCamelCase ):
__snake_case : Union[List[... | 352 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 0 |
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoModelForMaskedLM... | 353 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 | 0 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 354 |
from __future__ import annotations
from typing import Any
class __a :
def __init__( self : Dict , UpperCAmelCase : int = 6 ):
lowerCAmelCase_ : Node | None = None
lowerCAmelCase_ : Node | None = None
self.... | 28 | 0 |
import mpmath # for roots of unity
import numpy as np
class __a :
def __init__( self : List[str] , UpperCAmelCase : Union[str, Any]=None , UpperCAmelCase : Any=None ):
lowerCAmelCase_ : Optional[Any] = list(poly_a or [0] )[:]
... | 355 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 28 | 0 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : int , *UpperCAmelCase : str , ... | 356 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 0 |
import functools
from typing import Any
def __UpperCamelCase ( lowercase__ : List[str] , lowercase__ : List[Any] ) -> Optional[Any]:
'''simple docstring'''
if not isinstance(_A , _A ) or len(_A ) == 0:
raise ValueError("""the string should be... | 357 |
from math import factorial, pi
def __UpperCamelCase ( lowercase__ : float , lowercase__ : int = 30 ) -> float:
'''simple docstring'''
if not isinstance(lowercase__ , (int, float) ):
raise ValueError("""maclaurin_sin() requires either an int or... | 28 | 0 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Union[str, Any] , lo... | 358 |
# 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... | 28 | 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, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor, ... | 359 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig... | 28 | 0 |
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__UpperCAmelCase = get_tests_dir('fixtures/spiece.model')
... | 360 |
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 Co... | 28 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__UpperCAmelCase = {
'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}
try:
if not is_torch_available():
... | 361 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Optional[Any] , *... | 28 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailab... | 362 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __a ( __UpperCa... | 28 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__UpperCAmelCase = '\\n\n'
__UpperCAmelCase = '\nPerplexity (PPL) is one of the most common... | 363 |
from math import ceil
def __UpperCamelCase ( lowercase__ : int = 1001 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : Optional[Any] = 2 ... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : int ) -> list[int]:
'''simple docstring'''
if num <= 0:
raise ValueError("""Input must be a positive integer""" )
lowerCAmelCase_ : Union[str, Any] = [True] * (num + 1)
lowerCAmelCase_ : int = ... | 364 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowe... | 28 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __a ( unittest.Te... | 365 |
def __UpperCamelCase ( lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase_ : Any = 0
for ch in input_str:
lowerCAmelCase_ : Any = ord(lowercase__ )
lowerCAmelCase_ : Dict = pow(2 , lowerc... | 28 | 0 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __a ( UpperCAmelCase_ ):
@require_torch
def A ( self : List[str] ):
# this t... | 366 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__UpperCAmelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__UpperCAmelCase... | 28 | 0 |
import os
# Precomputes a list of the 100 first triangular numbers
__UpperCAmelCase = [int(0.5 * n * (n + 1)) for n in range(1, 1_01)]
def __UpperCamelCase ( ) -> Tuple:
'''simple docstring'''
lowerCAmelCase_ : List[Any] = os.path.dirname(os.path.realpath(snake_case... | 367 |
from datetime import datetime as dt
import os
from github import Github
__UpperCAmelCase = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def __UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
... | 28 | 0 |
import math
import sys
def __UpperCamelCase ( lowercase__ : Any ) -> int:
'''simple docstring'''
if number != int(lowerCAmelCase_ ):
raise ValueError("""the value of input must be a natural number""" )
if number < 0:
raise ValueError("""the value of in... | 368 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 28 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
__UpperCAmelCase = {
'configuration_speecht5': [
'SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SPEECHT5_PRETRAINED_HIFI... | 369 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 28 | 0 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_acce... | 370 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class __a ( __Upper... | 28 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image... | 371 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for non-integers""" )
eli... | 28 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
class __a ... | 350 |
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 ... | 28 | 0 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def __UpperCamelCase ( lowercase__ : BertModel , lowercase__ : str , lowercase__ : str ) -> Union[str, Any]:
'''simple docstring'''
l... | 351 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmelC... | 28 | 0 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
__UpperCAmelCase = (7_20, 12_80) # Height, Width
__UpperCAmelCase = (0.4, 0.6) # if height or width lower than this scale, drop it.
__UpperCAmelCase = 1 / 1_00
__U... | 352 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : bytes ) -> str:
'''simple docstring'''
return "".join([hex(lowercase__ )[2:].zfill(2 ).upper() for byte in list(lowercase__ )] )
def __UpperCamelCase ( lowercase__ : str ) -> bytes:
'''simple docstr... | 353 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 | 0 |
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : list[int] , lowercase__ : list[int] , lowercase__ : list[int] , lowercase__ : list[list[str]] , lowercase__ : int , ) -> None:
'''simple docstring'''
... | 354 |
from __future__ import annotations
from typing import Any
class __a :
def __init__( self : Dict , UpperCAmelCase : int = 6 ):
lowerCAmelCase_ : Node | None = None
lowerCAmelCase_ : Node | None = None
self.... | 28 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCAmelCase = {
'configuration_groupvit': [
'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'GroupViTConfig',
'GroupViTOnnxConfig',
'... | 355 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 28 | 0 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('3.8'):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
__UpperCAmel... | 356 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 0 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def __UpperCamelCase ( lowercase__ : dict ) -> tuple:
'''simple do... | 357 |
from math import factorial, pi
def __UpperCamelCase ( lowercase__ : float , lowercase__ : int = 30 ) -> float:
'''simple docstring'''
if not isinstance(lowercase__ , (int, float) ):
raise ValueError("""maclaurin_sin() requires either an int or... | 28 | 0 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 358 |
# 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... | 28 | 0 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( lowercase__ : Optional[Any] ) -> int:
'''simple d... | 359 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig... | 28 | 0 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 360 |
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 Co... | 28 | 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 ...... | 361 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Optional[Any] , *... | 28 | 0 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
import... | 362 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __a ( __UpperCa... | 28 | 0 |
"""simple docstring"""
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_c... | 363 |
from math import ceil
def __UpperCamelCase ( lowercase__ : int = 1001 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : Optional[Any] = 2 ... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : int = 10**9 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : Any = 1
lowerCAmelCase_ : Dict = 2
lowerCAmelCase_ : str = 0
lowerCAmelCase_ : Optional[Any] = 0
lowerCAmel... | 364 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowe... | 28 | 0 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 365 |
def __UpperCamelCase ( lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase_ : Any = 0
for ch in input_str:
lowerCAmelCase_ : Any = ord(lowercase__ )
lowerCAmelCase_ : Dict = pow(2 , lowerc... | 28 | 0 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowercase__ : Any , lowercase__ : int , lowercase__ : int ) -> List[Any]:
'''simple docstring'''
lowerCAmelCas... | 366 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__UpperCAmelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__UpperCAmelCase... | 28 | 0 |
from math import ceil
def __UpperCamelCase ( lowercase__ : int = 1001 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : Optional[Any] = 2 ... | 367 |
from datetime import datetime as dt
import os
from github import Github
__UpperCAmelCase = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def __UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase_ : Any = 0
for ch in input_str:
lowerCAmelCase_ : Any = ord(lowercase__ )
lowerCAmelCase_ : Dict = pow(2 , lowercas... | 368 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : int ) -> list[int]:
'''simple docstring'''
if num <= 0:
raise ValueError("""Input must be a positive integer""" )
lowerCAmelCase_ : Union[str, Any] = [True] * (num + 1)
lowerCAmelCase_ : List[str] ... | 369 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 28 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__UpperCAmelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__UpperCAmelCase... | 370 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class __a ( __Upper... | 28 | 0 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __a ( __UpperCamelCase ,__UpperCamelCase ):
__snake_case : ... | 371 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for non-integers""" )
eli... | 28 | 0 |
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformer... | 350 |
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 ... | 28 | 0 |
from __future__ import annotations
class __a :
def __init__( self : Union[str, Any] , UpperCAmelCase : list[list[int]] ):
lowerCAmelCase_ : Tuple = TypeError(
"""Matrices must be formed from a list of zero or more lists contain... | 351 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmelC... | 28 | 0 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 352 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 0 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def __UpperCamelCase ( lowercase__ : Any , lowercase__ : bool = True , lowercase__ : float = math.inf , lowercase__ : float = -math.inf , lowercase__ : ... | 353 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 | 0 |
from __future__ import annotations
__UpperCAmelCase = [True] * 1_00_00_01
__UpperCAmelCase = 2
while i * i <= 1_00_00_00:
if seive[i]:
for j in range(i * i, 1_00_00_01, i):
__UpperCAmelCase = False
i += 1
def __UpperCamelCase ( lowercase__ : int ) -> boo... | 354 |
from __future__ import annotations
from typing import Any
class __a :
def __init__( self : Dict , UpperCAmelCase : int = 6 ):
lowerCAmelCase_ : Node | None = None
lowerCAmelCase_ : Node | None = None
self.... | 28 | 0 |
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_tor... | 355 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 28 | 0 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def __UpperCamelCase ( lowercase__ : list[list[float]] ) -> list[list[float]]:
'''simple docstring'''
lowerCAmelCase_ : Any = Decimal
# Check if the pro... | 356 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 0 |
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : list[float] ) -> float:
'''simple docstring'''
lowerCAmelCase_ : Tuple = 0.00
lowerCAmelCase_ : List[Any] = 0
for resistor in resistors:
if resistor <= 0:
l... | 357 |
from math import factorial, pi
def __UpperCamelCase ( lowercase__ : float , lowercase__ : int = 30 ) -> float:
'''simple docstring'''
if not isinstance(lowercase__ , (int, float) ):
raise ValueError("""maclaurin_sin() requires either an int or... | 28 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 358 |
# 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... | 28 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {'vocab_file'... | 359 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig... | 28 | 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 ... | 360 |
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 Co... | 28 | 0 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
__UpperCAmelCase = (
'4S 3H 2C 7S 5H',
'9D 8H 2C 6S 7H',
'2D 6D 9D TH 7D',
'TC 8C 2S JH 6C',
'JH 8S TH AH QH',
'TS KS 5S 9S AC',
'KD 6S 9D TH AD',
'KS 8D... | 361 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Optional[Any] , *... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : int , lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstance(lowercase__... | 362 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __a ( __UpperCa... | 28 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'andreasmadsen/effi... | 363 |
from math import ceil
def __UpperCamelCase ( lowercase__ : int = 1001 ) -> int:
'''simple docstring'''
lowerCAmelCase_ : List[str] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowerCAmelCase_ : Optional[Any] = 2 ... | 28 | 0 |
import os
def __UpperCamelCase ( lowercase__ : str = "input.txt" ) -> int:
'''simple docstring'''
with open(os.path.join(os.path.dirname(lowercase__ ) , lowercase__ ) ) as input_file:
lowerCAmelCase_ : Optional[Any] = [
[... | 364 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( lowercase__ : Optional[Any] , lowe... | 28 | 0 |
"""simple docstring"""
# 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... | 365 |
def __UpperCamelCase ( lowercase__ : str ) -> bool:
'''simple docstring'''
lowerCAmelCase_ : Any = 0
for ch in input_str:
lowerCAmelCase_ : Any = ord(lowercase__ )
lowerCAmelCase_ : Dict = pow(2 , lowerc... | 28 | 0 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __UpperCamelCase ( lowercase__ : int ) -> int:
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = prime_factors(lowercase__ )
if is_square_free(lowercase... | 366 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__UpperCAmelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__UpperCAmelCase... | 28 | 0 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
W... | 367 |
from datetime import datetime as dt
import os
from github import Github
__UpperCAmelCase = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def __UpperCamelCase ( ) -> List[Any]:
'''simple docstring'''
... | 28 | 0 |
__UpperCAmelCase = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', 'U': '..-',
'V': '...-', 'W': '... | 368 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __a ( unittest.TestCase ):
def A ( self : List[Any] ):
lowerCAmelCase_ : Dict = Vector([1, 2, 3] )... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : int , lowercase__ : int ) -> str:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
lowerCAmelCase_ : str = str(bin(lowercase__ ) ... | 369 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 28 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
f... | 370 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class __a ( __Upper... | 28 | 0 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_available()... | 371 |
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( lowercase__ : int ) -> str:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
raise TypeError("""Undefined for non-integers""" )
eli... | 28 | 0 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 350 |
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 ... | 28 | 0 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class __a ( unittest.TestCa... | 351 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
__UpperCAmelC... | 28 | 0 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
blenderbot,
blend... | 352 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGenerationTesterMixi... | 28 | 0 |
def __UpperCamelCase ( lowercase__ : int ) -> bool:
'''simple docstring'''
if not isinstance(lowercase__ , lowercase__ ):
lowerCAmelCase_ : Dict = f'Input value of [number={number}] must be an integer'
raise TypeError(lowercase__ ... | 353 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __a ( __UpperCame... | 28 | 0 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __a ( __UpperCamelCase ):
def A ( self : str , UpperCAmelCase : str=None , UpperCAmelCase : Union[str, Any]=None , UpperCAmelCase : str=None , **UpperCAmelCase : ... | 354 |
from __future__ import annotations
from typing import Any
class __a :
def __init__( self : Dict , UpperCAmelCase : int = 6 ):
lowerCAmelCase_ : Node | None = None
lowerCAmelCase_ : Node | None = None
self.... | 28 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'tanreinama/GPTSAN-2.8B-spout_is_uniform': (
'https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json... | 355 |
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase ( lowercase__ : Optio... | 28 | 0 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class __a ( __UpperCamelCase ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Optio... | 356 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 0 |
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