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 |
|---|---|---|---|---|
def lowerCamelCase__ ( UpperCamelCase__ : int , UpperCamelCase__ : int ) -> int:
'''simple docstring'''
return x if y == 0 else greatest_common_divisor(UpperCamelCase__ , x % y )
def lowerCamelCase__ ( UpperCamelCase__ : ... | 295 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCamelCase_ ( enum.Enum ):
... | 295 | 1 |
from PIL import Image
def lowerCamelCase__ ( UpperCamelCase__ : Image , UpperCamelCase__ : float ) -> Image:
'''simple docstring'''
def brightness(UpperCamelCase__ : int ) -> float:
return 128 + level + (c - 128)
if not -255.0 ... | 295 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase_ = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author={Yonghui W... | 295 | 1 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class UpperCamelCase_ :
@property
def lowerCAmelCase ( self )... | 295 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {"""voca... | 295 | 1 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
UpperCAmelCase_ = logging.get_logger(__name__... | 295 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as Pr... | 295 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCamelCase_ ( _lowerCamelCase )... | 295 |
import random
def lowerCamelCase__ ( UpperCamelCase__ : int , UpperCamelCase__ : float , UpperCamelCase__ : bool = False ) -> dict:
'''simple docstring'''
_snake_case = {i: [] for i in range(UpperCamelCase__ )}
# if... | 295 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
UpperCAmelCase_ = {
"""albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/config.json""",
"""albert-large-v1""": """https:... | 295 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common... | 295 | 1 |
from ..utils import DummyObject, requires_backends
class UpperCamelCase_ ( metaclass=_lowerCamelCase ):
lowerCAmelCase_ = ['''sentencepiece''']
def __init__( self , *lowerCAmelCase_ , **lowerCAmelCase_ ) -> Dict:
requires_backends(self , ... | 295 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test... | 295 | 1 |
from __future__ import annotations
from typing import Any
class UpperCamelCase_ :
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = 0 ) -> None:
_snake_case , _snake_case = row, column
_snake_ca... | 295 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import re... | 295 | 1 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart ... | 295 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
UpperCAmelCase_ = logging.get_logger(__name__)
class UpperCamelCase_ ( _lowerCamelCase ):
def __init__( self , *lowerCAmelCase_ , **lowerCAmelCase_ ) ->... | 295 | 1 |
def lowerCamelCase__ ( UpperCamelCase__ : Tuple , UpperCamelCase__ : Optional[int] ) -> Tuple:
'''simple docstring'''
_snake_case = [0 for i in range(r + 1 )]
# nc0 = 1
_snake_case = 1
for i in range(1 , ... | 295 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fro... | 295 | 1 |
def lowerCamelCase__ ( UpperCamelCase__ : int , UpperCamelCase__ : int ) -> int:
'''simple docstring'''
return number | (1 << position)
def lowerCamelCase__ ( UpperCamelCase__ : int , UpperCamelCase__ : int ) -... | 295 |
def lowerCamelCase__ ( ) -> int:
'''simple docstring'''
return 1
def lowerCamelCase__ ( UpperCamelCase__ : int ) -> int:
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def lowerCamelCase__ ... | 295 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator,... | 295 |
def lowerCamelCase__ ( UpperCamelCase__ : Tuple , UpperCamelCase__ : Optional[int] ) -> Tuple:
'''simple docstring'''
_snake_case = [0 for i in range(r + 1 )]
# nc0 = 1
_snake_case = 1
for i in range(1 , ... | 295 | 1 |
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
UpperCAmelCase_ = '''scheduler_config.json'''
class UpperCamelCase_ ( SCREAMING_SNAKE_CASE_ ):
lowerCAm... | 350 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class UpperCamelCase_ ( _lowerCamelCase , _lowe... | 295 | 0 |
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 351 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
UpperCAmelCase_ = logging.get_lo... | 295 | 0 |
class UpperCamelCase_ :
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) -> Any:
_snake_case = name
_snake_case = value
_snake_case = weight
def __repr__( ... | 352 |
from cva import destroyAllWindows, imread, imshow, waitKey
def lowerCamelCase__ ( UpperCamelCase__ : Dict ) -> Optional[Any]:
'''simple docstring'''
_snake_case , _snake_case = img.shape[0], img.shape[1]
# converting each pixel's colo... | 295 | 0 |
from collections.abc import Callable
def lowerCamelCase__ ( UpperCamelCase__ : Callable[[float], float] , UpperCamelCase__ : float , UpperCamelCase__ : float ) -> float:
'''simple docstring'''
_snake_case = a
_snake_c... | 353 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def lowerCamelCase__ ( UpperCamelCa... | 295 | 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... | 354 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttention,
BaseModelOutputWit... | 295 | 0 |
"""simple docstring"""
from typing import Any
import numpy as np
def lowerCamelCase__ ( UpperCamelCase__ : np.ndarray ) -> Tuple:
'''simple docstring'''
return np.array_equal(__a , matrix.conjugate().T )
def lowerCamelCase__ ( UpperC... | 355 |
def lowerCamelCase__ ( UpperCamelCase__ : list[list[int]] , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : list[int] ) -> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
... | 295 | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, Flax... | 356 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def lowerCamelCase__ ( UpperCamelCase__ : Dict , UpperCamelCase__ : List[str] , UpperCamelCase__ : Dict ) -> List[Any]:
'''si... | 295 | 0 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
UpperCAmelCase_ = version.parse(version.parse(torch.__version__).base_version) < version.parse("""1.11""")
def lowerCamelCase__ ( ... | 357 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class UpperCamelCase_ :
@property
def lowerCAmelCase ( self )... | 295 | 0 |
from numpy import exp, pi, sqrt
def lowerCamelCase__ ( UpperCamelCase__ : Dict , UpperCamelCase__ : float = 0.0 , UpperCamelCase__ : float = 1.0 ) -> Tuple:
'''simple docstring'''
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) **... | 358 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowerCamelCase__ ( ) -> List[str]:
'''simple docstring'''
_snake_case , _snake_case = 9, 14 # noqa: F841
_snake_case =... | 295 | 0 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import ... | 359 |
from collections.abc import Sequence
def lowerCamelCase__ ( UpperCamelCase__ : Sequence[float] , UpperCamelCase__ : bool = False ) -> float:
'''simple docstring'''
if not arr:
return 0
_snake_case = 0 if allow_empty_subar... | 295 | 0 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCamelCase__ ( UpperCamelCase__ : Dict , UpperCamelCase__ : Dict ... | 360 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCamelCase_ ( enum.Enum ):
... | 295 | 0 |
import math
from collections import defaultdict
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 KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def lowerCamelCase__ ... | 361 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase_ = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author={Yonghui W... | 295 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 362 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {"""voca... | 295 | 0 |
"""simple docstring"""
from math import sqrt
def lowerCamelCase__ ( UpperCamelCase__ : Any ) -> bool:
'''simple docstring'''
assert isinstance(_lowerCamelCase , _lowerCamelCase ) and (
number >= 0
), "'number' must been an int and positive... | 363 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as Pr... | 295 | 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... | 364 |
import random
def lowerCamelCase__ ( UpperCamelCase__ : int , UpperCamelCase__ : float , UpperCamelCase__ : bool = False ) -> dict:
'''simple docstring'''
_snake_case = {i: [] for i in range(UpperCamelCase__ )}
# if... | 295 | 0 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
UpperCAmelCase_ = version.parse(version.parse(torch.__version__).base_version) < version.parse("""1.11""")
def lowerCamelCase__ ( ... | 365 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common... | 295 | 0 |
from ...configuration_utils import PretrainedConfig
UpperCAmelCase_ = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
"""https://huggingface.co/google/t... | 366 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test... | 295 | 0 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class UpperCamelCase_ :
@property
def lowerCAmelCase ( self )... | 367 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import re... | 295 | 0 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
UpperCAmelCase_ = HfApi()
UpperCAmelCase_ = {}
# fmt: off
UpperCAmelCase_ = torch.tensor([
-0.75_15, -1.68_83, 0.24_20, 0.03_00, 0.63_47, 1.34_33, -1.17_43, -3.74_67,
... | 368 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
UpperCAmelCase_ = logging.get_logger(__name__)
class UpperCamelCase_ ( _lowerCamelCase ):
def __init__( self , *lowerCAmelCase_ , **lowerCAmelCase_ ) ->... | 295 | 0 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase_ ( a__ , unittest.TestCase ):
"""simple docstring"""
lowerCAm... | 369 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fro... | 295 | 0 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tenso... | 370 |
def lowerCamelCase__ ( ) -> int:
'''simple docstring'''
return 1
def lowerCamelCase__ ( UpperCamelCase__ : int ) -> int:
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def lowerCamelCase__ ... | 295 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
else:
UpperCAmelCase... | 371 |
def lowerCamelCase__ ( UpperCamelCase__ : Tuple , UpperCamelCase__ : Optional[int] ) -> Tuple:
'''simple docstring'''
_snake_case = [0 for i in range(r + 1 )]
# nc0 = 1
_snake_case = 1
for i in range(1 , ... | 295 | 0 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT... | 350 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class UpperCamelCase_ ( _lowerCamelCase , _lowe... | 295 | 0 |
def lowerCamelCase__ ( UpperCamelCase__ : Tuple , UpperCamelCase__ : List[Any] ) -> Optional[Any]:
'''simple docstring'''
if mass < 0:
raise ValueError('The mass of a body cannot be negative' )
return 0.5 * mass * abs(__lowerCamelCase ) * ... | 351 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
UpperCAmelCase_ = logging.get_lo... | 295 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
UpperCAmelCase_ = {
"""albert-base-v1""": """https://huggingface.co/albert-base-v1/resolve/main/config.json""",
"""albert-large-v1""": """htt... | 352 |
from cva import destroyAllWindows, imread, imshow, waitKey
def lowerCamelCase__ ( UpperCamelCase__ : Dict ) -> Optional[Any]:
'''simple docstring'''
_snake_case , _snake_case = img.shape[0], img.shape[1]
# converting each pixel's colo... | 295 | 0 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
fr... | 353 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def lowerCamelCase__ ( UpperCamelCa... | 295 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator,... | 354 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttention,
BaseModelOutputWit... | 295 | 0 |
"""simple docstring"""
import os
import sys
import unittest
UpperCAmelCase_ = 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
... | 355 |
def lowerCamelCase__ ( UpperCamelCase__ : list[list[int]] , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : list[int] ) -> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
... | 295 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( UpperCamelCase__ : list[int] , UpperCamelCase__ : list[int] , UpperCamelCase__ : list[int] , UpperCamelCase__ : list[list[str]] , UpperCamelCase__ : int , ) -> No... | 356 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def lowerCamelCase__ ( UpperCamelCase__ : Dict , UpperCamelCase__ : List[str] , UpperCamelCase__ : Dict ) -> List[Any]:
'''si... | 295 | 0 |
def lowerCamelCase__ ( UpperCamelCase__ : str , UpperCamelCase__ : str = " " ) -> Optional[Any]:
'''simple docstring'''
_snake_case = []
_snake_case = 0
for index, char in enumerate(A__ ):
if char == separa... | 357 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class UpperCamelCase_ :
@property
def lowerCAmelCase ( self )... | 295 | 0 |
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from transformers.utils import W... | 358 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowerCamelCase__ ( ) -> List[str]:
'''simple docstring'''
_snake_case , _snake_case = 9, 14 # noqa: F841
_snake_case =... | 295 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json",
}
clas... | 359 |
from collections.abc import Sequence
def lowerCamelCase__ ( UpperCamelCase__ : Sequence[float] , UpperCamelCase__ : bool = False ) -> float:
'''simple docstring'''
if not arr:
return 0
_snake_case = 0 if allow_empty_subar... | 295 | 0 |
from PIL import Image
def lowerCamelCase__ ( UpperCamelCase__ : Image ) -> Image:
'''simple docstring'''
_snake_case , _snake_case = image.size
_snake_case = 0
_snake_case = image.load()
for i in r... | 360 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCamelCase_ ( enum.Enum ):
... | 295 | 0 |
from collections import Counter
from timeit import timeit
def lowerCamelCase__ ( UpperCamelCase__ : List[Any] = "" , ) -> bool:
'''simple docstring'''
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values() ) < 2
def ... | 361 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase_ = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author={Yonghui W... | 295 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ = {
"""configuration_pix2struct""": [
"""PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Pix2Str... | 362 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {"""voca... | 295 | 0 |
"""simple docstring"""
# Function to print upper half of diamond (pyramid)
def lowerCamelCase__ ( UpperCamelCase__ : Dict ) -> str:
'''simple docstring'''
for i in range(0 , UpperCamelCase__ ):
for _ in range(0 , n - i - 1 ): #... | 363 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as Pr... | 295 | 0 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
UpperCAmelCase_ = {
'''n_samples''': 64,
'''horizon''': 32,
'''num_inference_steps''': 20,
'''n_guide_steps''': 2, # can set to 0 for faster sampling, does not use value network
... | 364 |
import random
def lowerCamelCase__ ( UpperCamelCase__ : int , UpperCamelCase__ : float , UpperCamelCase__ : bool = False ) -> dict:
'''simple docstring'''
_snake_case = {i: [] for i in range(UpperCamelCase__ )}
# if... | 295 | 0 |
def lowerCamelCase__ ( UpperCamelCase__ : Optional[int] = "The quick brown fox jumps over the lazy dog" , ) -> List[str]:
'''simple docstring'''
_snake_case = set()
# Replace all the whitespace in our sentence
_snake_case = i... | 365 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common... | 295 | 0 |
def lowerCamelCase__ ( UpperCamelCase__ : list[list[int]] , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : list[int] ) -> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
retu... | 366 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test... | 295 | 0 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'post_extract_proj': 'feature_projecti... | 367 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import re... | 295 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json""",
}
class Up... | 368 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
UpperCAmelCase_ = logging.get_logger(__name__)
class UpperCamelCase_ ( _lowerCamelCase ):
def __init__( self , *lowerCAmelCase_ , **lowerCAmelCase_ ) ->... | 295 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
"google/fnet-large": "https://huggingface... | 369 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fro... | 295 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase = {
"""configuration_resnet""": ["""RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ResNetConfig""", """ResN... | 370 |
def lowerCamelCase__ ( ) -> int:
'''simple docstring'''
return 1
def lowerCamelCase__ ( UpperCamelCase__ : int ) -> int:
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def lowerCamelCase__ ... | 295 | 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.t... | 371 |
def lowerCamelCase__ ( UpperCamelCase__ : Tuple , UpperCamelCase__ : Optional[int] ) -> Tuple:
'''simple docstring'''
_snake_case = [0 for i in range(r + 1 )]
# nc0 = 1
_snake_case = 1
for i in range(1 , ... | 295 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( UpperCamelCase__ : Dict ) -> bool:
'''simple docstring'''
_snake_case = str(__lowerCAmelCase )
return n == n[::-1]
def lowerCamelCase__ ( UpperCamelCase__ : Optional[int]... | 350 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class UpperCamelCase_ ( _lowerCamelCase , _lowe... | 295 | 0 |
import torch
from torch import nn
class UpperCamelCase_ ( nn.Module ):
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_=1 , lowerCAmelCase_=False ) -> Tuple:
super().__init__()
... | 351 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
UpperCAmelCase_ = logging.get_lo... | 295 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( UpperCamelCase__ : List[Any] , UpperCamelCase__ : Optional[Any] ) -> bool:
'''simple docstring'''
_snake_case = get_failure_array(UpperCamelCase__ )
# 2) Step through text ... | 352 |
from cva import destroyAllWindows, imread, imshow, waitKey
def lowerCamelCase__ ( UpperCamelCase__ : Dict ) -> Optional[Any]:
'''simple docstring'''
_snake_case , _snake_case = img.shape[0], img.shape[1]
# converting each pixel's colo... | 295 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
UpperCAmelCase_ = logging.get_logger(__name__... | 353 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def lowerCamelCase__ ( UpperCamelCa... | 295 | 0 |
def lowerCamelCase__ ( UpperCamelCase__ : Dict ) -> int:
'''simple docstring'''
if n_term == "":
return []
_snake_case = []
for temp in range(int(_lowerCAmelCase ) ):
series.append(F'''1/{temp + 1}''' if series else '1' )
... | 354 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttention,
BaseModelOutputWit... | 295 | 0 |
"""simple docstring"""
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_ = logging.get_l... | 355 |
def lowerCamelCase__ ( UpperCamelCase__ : list[list[int]] , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : list[int] ) -> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
... | 295 | 0 |
def lowerCamelCase__ ( UpperCamelCase__ : int ) -> Optional[int]:
'''simple docstring'''
_snake_case = abs(UpperCamelCase__ )
_snake_case = 0
while n > 0:
res += n % 10
n //= 10
return res
def lowerCamelC... | 356 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def lowerCamelCase__ ( UpperCamelCase__ : Dict , UpperCamelCase__ : List[str] , UpperCamelCase__ : Dict ) -> List[Any]:
'''si... | 295 | 0 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class UpperCamelCase_ (... | 357 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class UpperCamelCase_ :
@property
def lowerCAmelCase ( self )... | 295 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.set_verb... | 358 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowerCamelCase__ ( ) -> List[str]:
'''simple docstring'''
_snake_case , _snake_case = 9, 14 # noqa: F841
_snake_case =... | 295 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ..... | 359 |
from collections.abc import Sequence
def lowerCamelCase__ ( UpperCamelCase__ : Sequence[float] , UpperCamelCase__ : bool = False ) -> float:
'''simple docstring'''
if not arr:
return 0
_snake_case = 0 if allow_empty_subar... | 295 | 0 |
import torch
from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
from .base import PipelineTool
class UpperCamelCase_ ( _lowercase ):
lowerCAmelCase_ = '''facebook/bart-large-mnli'''
lowerCAmelCase_ = (
'''This is a tool that classifies... | 360 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCamelCase_ ( enum.Enum ):
... | 295 | 0 |
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCamelCase_ ( __lowercase ):
def __init__( self ) -> Tuple:
# test for the above condition
self.test()
def lowerCAmelCase ( self ) -> ... | 361 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase_ = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author={Yonghui W... | 295 | 0 |
"""simple docstring"""
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool
class UpperCamelCase_ ( UpperCamelCase_ ):
lowerCAmelCase_ = """openai/whisper-base"""
lowerCAmelCase_ = (
"""This is a tool tha... | 362 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {"""voca... | 295 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',... | 363 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as Pr... | 295 | 0 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
UpperCAmelCase_ = ['small', 'medium', 'large']
UpperCAmelCase_ = 'lm_head.decoder.weight'
UpperCAmelCase_ = 'lm_head.weight'
def lowerCamelCase__ ( UpperCamelCase__ ... | 364 |
import random
def lowerCamelCase__ ( UpperCamelCase__ : int , UpperCamelCase__ : float , UpperCamelCase__ : bool = False ) -> dict:
'''simple docstring'''
_snake_case = {i: [] for i in range(UpperCamelCase__ )}
# if... | 295 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tok... | 365 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common... | 295 | 0 |
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pipeline_mixin import... | 366 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test... | 295 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
"""configuration_convbert""": ["""CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ConvBertC... | 367 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import re... | 295 | 0 |
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCAmelCase_ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0... | 368 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
UpperCAmelCase_ = logging.get_logger(__name__)
class UpperCamelCase_ ( _lowerCamelCase ):
def __init__( self , *lowerCAmelCase_ , **lowerCAmelCase_ ) ->... | 295 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class UpperCamelCase_ ( _lowerCamelCase ... | 369 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fro... | 295 | 0 |
from __future__ import annotations
from statistics import mean
def lowerCamelCase__ ( UpperCamelCase__ : list[int] , UpperCamelCase__ : list[int] , UpperCamelCase__ : int ) -> list[int]:
'''simple docstring'''
_snake_case =... | 370 |
def lowerCamelCase__ ( ) -> int:
'''simple docstring'''
return 1
def lowerCamelCase__ ( UpperCamelCase__ : int ) -> int:
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def lowerCamelCase__ ... | 295 | 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 |
def lowerCamelCase__ ( UpperCamelCase__ : Tuple , UpperCamelCase__ : Optional[int] ) -> Tuple:
'''simple docstring'''
_snake_case = [0 for i in range(r + 1 )]
# nc0 = 1
_snake_case = 1
for i in range(1 , ... | 295 | 0 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('socket.socket' )
@patch('builtins.open' )
def lowerCamelCase__ ( UpperCamelCase__ : Optional[Any] , UpperCamelCase__ : Dict ) -> List[Any]:
'''simple docstring'''
... | 350 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class UpperCamelCase_ ( _lowerCamelCase , _lowe... | 295 | 0 |
def lowerCamelCase__ ( UpperCamelCase__ : List[Any] ) -> Any:
'''simple docstring'''
_snake_case = []
_snake_case = set({'(', '[', '{'} )
_snake_case = set({')', ']', '}'} )
_snake_case = {"{": "}",... | 351 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
UpperCAmelCase_ = logging.get_lo... | 295 | 0 |
from functools import reduce
UpperCAmelCase_ = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'668966489504452... | 352 |
from cva import destroyAllWindows, imread, imshow, waitKey
def lowerCamelCase__ ( UpperCamelCase__ : Dict ) -> Optional[Any]:
'''simple docstring'''
_snake_case , _snake_case = img.shape[0], img.shape[1]
# converting each pixel's colo... | 295 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
from... | 353 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def lowerCamelCase__ ( UpperCamelCa... | 295 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface import Hug... | 354 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttention,
BaseModelOutputWit... | 295 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
UpperCAmelCase_ = 1.054571817E-34 # unit of ℏ : J * s
UpperCAmelCase_ = 3E8 # unit of c : m * s^-1
... | 355 |
def lowerCamelCase__ ( UpperCamelCase__ : list[list[int]] , UpperCamelCase__ : int , UpperCamelCase__ : int , UpperCamelCase__ : list[int] ) -> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
... | 295 | 0 |
import os
def lowerCamelCase__ ( ) -> Any:
'''simple docstring'''
_snake_case = os.path.dirname(os.path.realpath(__UpperCAmelCase ) )
_snake_case = os.path.join(__UpperCAmelCase , 'triangle.txt' )
with open(__UpperCAmelCase ) a... | 356 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def lowerCamelCase__ ( UpperCamelCase__ : Dict , UpperCamelCase__ : List[str] , UpperCamelCase__ : Dict ) -> List[Any]:
'''si... | 295 | 0 |
from random import shuffle
import tensorflow as tf
from numpy import array
def lowerCamelCase__ ( UpperCamelCase__ : str , UpperCamelCase__ : List[str] ) -> Optional[Any]:
'''simple docstring'''
_snake_case = int(lowercase_ )
asse... | 357 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class UpperCamelCase_ :
@property
def lowerCAmelCase ( self )... | 295 | 0 |
from ...processing_utils import ProcessorMixin
class UpperCamelCase_ ( a_ ):
lowerCAmelCase_ = '''SpeechT5FeatureExtractor'''
lowerCAmelCase_ = '''SpeechT5Tokenizer'''
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_ ) -> Optional[in... | 358 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowerCamelCase__ ( ) -> List[str]:
'''simple docstring'''
_snake_case , _snake_case = 9, 14 # noqa: F841
_snake_case =... | 295 | 0 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCamelCase__ ( *UpperCamelCase__ : Tuple , UpperCamelCase__ : Dict = None , UpperCamelCase__ : str=True , UpperCamelCa... | 359 |
from collections.abc import Sequence
def lowerCamelCase__ ( UpperCamelCase__ : Sequence[float] , UpperCamelCase__ : bool = False ) -> float:
'''simple docstring'''
if not arr:
return 0
_snake_case = 0 if allow_empty_subar... | 295 | 0 |
from __future__ import annotations
UpperCAmelCase_ = list[tuple[int, int]]
UpperCAmelCase_ = [
[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, 0, 1, 0, 0, 0, 0],
[0, 0, ... | 360 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCamelCase_ ( enum.Enum ):
... | 295 | 0 |
import argparse
import os
import re
import packaging.version
UpperCAmelCase_ = """examples/"""
UpperCAmelCase_ = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.compile(R"""^__ve... | 361 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase_ = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},
author={Yonghui W... | 295 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json""",
... | 362 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {"""voca... | 295 | 0 |
"""simple docstring"""
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIP... | 363 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as Pr... | 295 | 0 |
def lowerCamelCase__ ( UpperCamelCase__ : int ) -> "list[int]":
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
_snake_case = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) ... | 364 |
import random
def lowerCamelCase__ ( UpperCamelCase__ : int , UpperCamelCase__ : float , UpperCamelCase__ : bool = False ) -> dict:
'''simple docstring'''
_snake_case = {i: [] for i in range(UpperCamelCase__ )}
# if... | 295 | 0 |
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fastapi.routing impor... | 365 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common... | 295 | 0 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def lowerCamelCase__ ( UpperCamelCase__ : NDArray[floataa] , UpperCamelCase__ : NDArray[floataa] , UpperCamelCase__ : list[int] , UpperCamelCa... | 366 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test... | 295 | 0 |
def lowerCamelCase__ ( UpperCamelCase__ : Tuple ) -> Optional[int]:
'''simple docstring'''
_snake_case = [False] * len(SCREAMING_SNAKE_CASE__ )
_snake_case = [-1] * len(SCREAMING_SNAKE_CASE__ )
def dfs(UpperCamelCase__ : Op... | 367 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import re... | 295 | 0 |
import baseaa
def lowerCamelCase__ ( UpperCamelCase__ : List[str] ) -> bytes:
'''simple docstring'''
return baseaa.aaaencode(string.encode('utf-8' ) )
def lowerCamelCase__ ( UpperCamelCase__ : List[str] ) -> str:
'''simple do... | 368 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
UpperCAmelCase_ = logging.get_logger(__name__)
class UpperCamelCase_ ( _lowerCamelCase ):
def __init__( self , *lowerCAmelCase_ , **lowerCAmelCase_ ) ->... | 295 | 0 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class UpperCamelCase_ ( unittest.TestCase ):
"""simple docstring"""
def lowerCAmelCase ( self ) -> None:
_... | 369 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
fro... | 295 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def lowerCamelCase__ ( UpperCamelCase__ : Union[str, Any] , UpperCamelCase__ : Any=1_000 ) -> Tuple:
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
return n... | 370 |
def lowerCamelCase__ ( ) -> int:
'''simple docstring'''
return 1
def lowerCamelCase__ ( UpperCamelCase__ : int ) -> int:
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def lowerCamelCase__ ... | 295 | 0 |
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCAmelCase_ = """\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models fo... | 371 |
def lowerCamelCase__ ( UpperCamelCase__ : Tuple , UpperCamelCase__ : Optional[int] ) -> Tuple:
'''simple docstring'''
_snake_case = [0 for i in range(r + 1 )]
# nc0 = 1
_snake_case = 1
for i in range(1 , ... | 295 | 0 |
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