code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.util... | 701 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _a ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : List[Any] = 0
if start < end:
... | 47 | 0 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_... | 702 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 47 | 0 |
'''simple docstring'''
import operator as op
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : Union[str, Any] = []
_snake_case : Dict = lambda lowerCAmelCase_ , lowerCAmelCase_ : int(x / y ) # noqa: E731 integer divisio... | 703 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_t... | 47 | 0 |
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCamelCase (tf.keras.layers.Layer ):
def __init__( self , ... | 704 |
'''simple docstring'''
from collections.abc import Generator
def _a ( ):
"""simple docstring"""
_snake_case , _snake_case : Union[str, Any] = 0, 1
while True:
_snake_case , _snake_case : List[str] = b, a + b
... | 47 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=lowercase__ )
class lowerCamelCase (lowercase__ ):
_lowercase : Dict = field(defa... | 705 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCAmelCase : str = logging.getLogger(__name__)
UpperCAmelCas... | 47 | 0 |
'''simple docstring'''
class lowerCamelCase :
def __init__( self ) -> Tuple:
"""simple docstring"""
_snake_case : Union[str, Any] = 0
_snake_case : Any = 0
_snake_case : int = ... | 706 |
'''simple docstring'''
from __future__ import annotations
def _a ( lowerCAmelCase_ , lowerCAmelCase_ = None , lowerCAmelCase_ = None ):
"""simple docstring"""
if start is None:
_snake_case : Optional[Any] = 0
if end is None:
... | 47 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : List[str] = {"configuration_plbart": ["PLBART_PRETRAINED_CONFI... | 707 |
'''simple docstring'''
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers i... | 47 | 0 |
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_enforce_args(__A , __A )
if n == 0:
return 0
_snake_case : List[str] = float('''-inf''' )
for i in range(1 , n + 1 ):
_snake_case : Li... | 708 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCamelCase (unittest.TestCase ):
def UpperCAmelCase_ ( self ) ... | 47 | 0 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : str = 0
while len(__lowerCAmelCase ) > 1:
_snake_case : str = 0
# Consider two files with minimum cost to be merged
for _ i... | 709 |
'''simple docstring'''
UpperCAmelCase : Union[str, Any] = tuple[float, float, float]
UpperCAmelCase : int = tuple[float, float, float]
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : str = end_poin... | 47 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, 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()... | 710 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
UpperCAmelCase : List[st... | 47 | 0 |
'''simple docstring'''
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 fas... | 711 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if n == 1 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
return 0
elif n == 2:
return 1
else:
_snake_case : Union[str, Any] = [0, ... | 47 | 0 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class lowerCamelCase (unittest.TestCase ):
... | 712 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase : Any = TypeVar('T')
UpperCAmelCase : str = TypeVar('U')
class lowerCamelCase (Generic[T, U] ):
def __init__( self ... | 47 | 0 |
'''simple docstring'''
UpperCAmelCase : Optional[int] = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import... | 713 |
'''simple docstring'''
import os
import numpy
import onnx
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : List[Any] = a.name
_snake_case : List[Any] = b.name
_snake_case : Tuple = ... | 47 | 0 |
'''simple docstring'''
from scipy.stats import spearmanr
import datasets
UpperCAmelCase : str = '\nThe Spearman rank-order correlation coefficient is a measure of the\nrelationship between two datasets. Like other correlation coefficients,\nthis one varies between -1 and +1 with 0 implying no corr... | 714 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : int = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available()... | 47 | 0 |
'''simple docstring'''
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 Back... | 715 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImage... | 47 | 0 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class lowerCamelCase (unittest.TestCase ):
def UpperCAmelCase_ ( self ) -> str:
"""simple docstring"""
_snake_case :... | 716 |
'''simple docstring'''
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... | 47 | 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
if ... | 717 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 47 | 0 |
'''simple docstring'''
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configurat... | 718 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowerCAmelCase_ , 0 , lowerCAmelCa... | 47 | 0 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase : Optional[int] = '''\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing... | 719 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
... | 47 | 0 |
'''simple docstring'''
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 lowerCamelCase (_... | 720 |
'''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
#
... | 47 | 0 |
'''simple docstring'''
import os
from typing import Dict, List, Tuple, TypeVar, Union
UpperCAmelCase : int = TypeVar('T')
UpperCAmelCase : Optional[int] = Union[List[T], Tuple[T, ...]]
UpperCAmelCase : List[Any] = Union[T, List[T], Dict[str, T]]
UpperCAmelCase : Dict ... | 721 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoM... | 47 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def _a ( ):
"""simple docstring"""
_snake_case : Tuple = {
'''repo_name''': ['''test_repo1'... | 700 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : Dict = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d... | 47 | 0 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gp... | 701 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _a ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : List[Any] = 0
if start < end:
... | 47 | 0 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class lowerCamelCase (unittest.TestCase ):
def UpperCAmelC... | 702 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 47 | 0 |
'''simple docstring'''
def _a ( lowerCAmelCase_ = 4_000_000 ):
"""simple docstring"""
_snake_case : Any = []
_snake_case : Optional[int] = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(snake_case_ )
... | 703 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_t... | 47 | 0 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fr... | 704 |
'''simple docstring'''
from collections.abc import Generator
def _a ( ):
"""simple docstring"""
_snake_case , _snake_case : Union[str, Any] = 0, 1
while True:
_snake_case , _snake_case : List[str] = b, a + b
... | 47 | 0 |
'''simple docstring'''
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
UpperCAmelCa... | 705 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCAmelCase : str = logging.getLogger(__name__)
UpperCAmelCas... | 47 | 0 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMSc... | 706 |
'''simple docstring'''
from __future__ import annotations
def _a ( lowerCAmelCase_ , lowerCAmelCase_ = None , lowerCAmelCase_ = None ):
"""simple docstring"""
if start is None:
_snake_case : Optional[Any] = 0
if end is None:
... | 47 | 0 |
'''simple docstring'''
import torch
from diffusers import StableDiffusionPipeline
UpperCAmelCase : int = 'path-to-your-trained-model'
UpperCAmelCase : Dict = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('cuda')
UpperCAmelCase : Dict = 'A ... | 707 |
'''simple docstring'''
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers i... | 47 | 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 : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase :... | 708 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCamelCase (unittest.TestCase ):
def UpperCAmelCase_ ( self ) ... | 47 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def _a ( lowerCAmelCase_ = 2_000_000 ):
"""simple docstring"""
_snake_case : list[int] = [0]
_snake_case : int
for idx in range(1 , ceil(sqrt(target... | 709 |
'''simple docstring'''
UpperCAmelCase : Union[str, Any] = tuple[float, float, float]
UpperCAmelCase : int = tuple[float, float, float]
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : str = end_poin... | 47 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
UpperCAmelC... | 710 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
UpperCAmelCase : List[st... | 47 | 0 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
fro... | 711 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if n == 1 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
return 0
elif n == 2:
return 1
else:
_snake_case : Union[str, Any] = [0, ... | 47 | 0 |
'''simple docstring'''
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
... | 712 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase : Any = TypeVar('T')
UpperCAmelCase : str = TypeVar('U')
class lowerCamelCase (Generic[T, U] ):
def __init__( self ... | 47 | 0 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(__UpperCamelCase , __UpperCamelCase ):
raise TypeError('''Input value must be a ... | 713 |
'''simple docstring'''
import os
import numpy
import onnx
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : List[Any] = a.name
_snake_case : List[Any] = b.name
_snake_case : Tuple = ... | 47 | 0 |
'''simple docstring'''
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 : Optional[int] = logging.get_logger(__name__)... | 714 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : int = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available()... | 47 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.... | 715 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImage... | 47 | 0 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : Optional[Any] = ... | 716 |
'''simple docstring'''
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... | 47 | 0 |
'''simple docstring'''
from math import factorial
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
if n < k or k < 0:
raise ValueError('''Please enter positive integers for n and k where n >= k''' )
return factorial(lowerCAmelCase_ ... | 717 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 47 | 0 |
'''simple docstring'''
import os
import textwrap
import pyarrow as pa
import pytest
from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv
from ..utils import require_pil
@pytest.fixture
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
... | 718 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowerCAmelCase_ , 0 , lowerCAmelCa... | 47 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase (__a ):
def __init__( self , *lowercase__ , *... | 719 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
... | 47 | 0 |
'''simple docstring'''
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 lo... | 720 |
'''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
#
... | 47 | 0 |
'''simple docstring'''
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
UpperCAmelCase : List[Any] = object()
# For specifying empty leaf dict `{}`
UpperCAmelCase : str ... | 721 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoM... | 47 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_a... | 700 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : Dict = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d... | 47 | 0 |
'''simple docstring'''
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,... | 701 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _a ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : List[Any] = 0
if start < end:
... | 47 | 0 |
'''simple docstring'''
import operator as op
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : int = []
_snake_case : Any = lambda lowerCAmelCase_ , lowerCAmelCase_ : int(x / y ) # noqa: E731 integer division operation
... | 702 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 47 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : int = logging.get_logger(__name__)
UpperCAmelCase : Dict = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwritt... | 703 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_t... | 47 | 0 |
# Imports
import numpy as np
class lowerCamelCase :
def __init__( self , lowercase__=None , lowercase__=None , lowercase__=None , lowercase__=None , lowercase__=None ) -> List[Any]:
"""simple docstring"""
self.set_matric... | 704 |
'''simple docstring'''
from collections.abc import Generator
def _a ( ):
"""simple docstring"""
_snake_case , _snake_case : Union[str, Any] = 0, 1
while True:
_snake_case , _snake_case : List[str] = b, a + b
... | 47 | 0 |
'''simple docstring'''
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 (
CommonSchedulerState,
FlaxKarrasDiffusionSchedulers,
... | 705 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCAmelCase : str = logging.getLogger(__name__)
UpperCAmelCas... | 47 | 0 |
'''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCamelCase (_UpperCamelCase ):
_lowercase : List[Any] = "EncodecFeatureExtractor"
_lowercase ... | 706 |
'''simple docstring'''
from __future__ import annotations
def _a ( lowerCAmelCase_ , lowerCAmelCase_ = None , lowerCAmelCase_ = None ):
"""simple docstring"""
if start is None:
_snake_case : Optional[Any] = 0
if end is None:
... | 47 | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from .... | 707 |
'''simple docstring'''
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers i... | 47 | 0 |
import logging
from transformers import PretrainedConfig
UpperCAmelCase : Union[str, Any] = logging.getLogger(__name__)
UpperCAmelCase : Tuple = {
"""bertabs-finetuned-cnndm""": """https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/mai... | 708 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCamelCase (unittest.TestCase ):
def UpperCAmelCase_ ( self ) ... | 47 | 0 |
'''simple docstring'''
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
UpperCAmelCase : List[str] = (
'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... | 709 |
'''simple docstring'''
UpperCAmelCase : Union[str, Any] = tuple[float, float, float]
UpperCAmelCase : int = tuple[float, float, float]
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : str = end_poin... | 47 | 0 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
_snake_case : Dict = f'''Input value of [number={number}] must be an integer'''
raise TypeError(__UpperCa... | 710 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
UpperCAmelCase : List[st... | 47 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
UpperCAmelCase : Optional[int] = logging.get_... | 711 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if n == 1 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
return 0
elif n == 2:
return 1
else:
_snake_case : Union[str, Any] = [0, ... | 47 | 0 |
'''simple docstring'''
# 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/lice... | 712 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase : Any = TypeVar('T')
UpperCAmelCase : str = TypeVar('U')
class lowerCamelCase (Generic[T, U] ):
def __init__( self ... | 47 | 0 |
'''simple docstring'''
import math
from collections.abc import Iterator
from itertools import takewhile
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or nu... | 713 |
'''simple docstring'''
import os
import numpy
import onnx
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : List[Any] = a.name
_snake_case : List[Any] = b.name
_snake_case : Tuple = ... | 47 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCAmelCase : List[str] = {
'configuration_gpt_neo': ['GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoConfig', 'GPTNeoOnnxConfig'],... | 714 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : int = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available()... | 47 | 0 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCamelCase (__UpperCAmelCase ):
def __lt__( self , lowercase__ ) -> str:
"""simple ... | 715 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImage... | 47 | 0 |
'''simple docstring'''
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... | 716 |
'''simple docstring'''
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... | 47 | 0 |
'''simple docstring'''
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 ... | 717 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 47 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTes... | 718 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowerCAmelCase_ , 0 , lowerCAmelCa... | 47 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImage... | 719 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
... | 47 | 0 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_gr... | 720 |
'''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
#
... | 47 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.... | 721 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoM... | 47 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeli... | 700 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : Dict = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d... | 47 | 0 |
'''simple docstring'''
def _a ( lowerCAmelCase_ = 3 , lowerCAmelCase_ = 7 , lowerCAmelCase_ = 1_000_000 ):
"""simple docstring"""
_snake_case : Dict = 0
_snake_case : List[str] = 1
for current_denominator ... | 701 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _a ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : List[Any] = 0
if start < end:
... | 47 | 0 |
'''simple docstring'''
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def _a ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : Union[str, Any] ... | 702 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 47 | 0 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 703 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_t... | 47 | 0 |
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
MusicgenProcesso... | 704 |
'''simple docstring'''
from collections.abc import Generator
def _a ( ):
"""simple docstring"""
_snake_case , _snake_case : Union[str, Any] = 0, 1
while True:
_snake_case , _snake_case : List[str] = b, a + b
... | 47 | 0 |
'''simple docstring'''
import argparse
import os
import re
UpperCAmelCase : Optional[Any] = '''src/transformers/models/auto'''
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCAmelCase : int = re.c... | 705 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCAmelCase : str = logging.getLogger(__name__)
UpperCAmelCas... | 47 | 0 |
'''simple docstring'''
import itertools
import math
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 706 |
'''simple docstring'''
from __future__ import annotations
def _a ( lowerCAmelCase_ , lowerCAmelCase_ = None , lowerCAmelCase_ = None ):
"""simple docstring"""
if start is None:
_snake_case : Optional[Any] = 0
if end is None:
... | 47 | 0 |
'''simple docstring'''
class lowerCamelCase :
def __init__( self , lowercase__ ) -> Optional[int]:
"""simple docstring"""
_snake_case : Union[str, Any] = arr.split(''',''' )
def UpperCAmelCase_ ( self ) -> Dict:
... | 707 |
'''simple docstring'''
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers i... | 47 | 0 |
from __future__ import annotations
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
return [ord(_A ) - 96 for elem in plain]
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
return "".join(chr(elem + 96 ) for elem in encoded )
def ... | 708 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCamelCase (unittest.TestCase ):
def UpperCAmelCase_ ( self ) ... | 47 | 0 |
'''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class lowerCamelCase (_A ):
def __init__( self , *lowercase__ , **lowercase__ ) -> Any:
"""simple docstring"""
super().__init__(*UpperCamelCase__ ... | 709 |
'''simple docstring'''
UpperCAmelCase : Union[str, Any] = tuple[float, float, float]
UpperCAmelCase : int = tuple[float, float, float]
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : str = end_poin... | 47 | 0 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : list[list[int]] = [[0 for _ in range(lowerCAmelCase_ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
_snake_case : Optional[int] = 1
for ... | 710 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
UpperCAmelCase : List[st... | 47 | 0 |
'''simple docstring'''
import qiskit
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : Tuple = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
_snake_case : Tup... | 711 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if n == 1 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
return 0
elif n == 2:
return 1
else:
_snake_case : Union[str, Any] = [0, ... | 47 | 0 |
'''simple docstring'''
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class lowerCamelCase :
def UpperCAmelCase_ ( self , lowercase__ ) -> Dict:
... | 712 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase : Any = TypeVar('T')
UpperCAmelCase : str = TypeVar('U')
class lowerCamelCase (Generic[T, U] ):
def __init__( self ... | 47 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class lowerCamelCase ( unittest.TestCase ):
def UpperCAmelCase_ ( self ) -> int:
"... | 713 |
'''simple docstring'''
import os
import numpy
import onnx
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : List[Any] = a.name
_snake_case : List[Any] = b.name
_snake_case : Tuple = ... | 47 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@... | 714 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : int = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available()... | 47 | 0 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase (a__ ):
_lowercase : List[str] = ["""image_processor""", """tokenizer"""]
_lowercase : Optional[Any] = "... | 715 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImage... | 47 | 0 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_... | 716 |
'''simple docstring'''
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... | 47 | 0 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteSch... | 717 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 47 | 0 |
'''simple docstring'''
def _a ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def _a ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""si... | 718 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if num <= 0:
raise ValueError('''math domain error''' )
return quad(lowerCAmelCase_ , 0 , lowerCAmelCa... | 47 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 719 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
... | 47 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependen... | 720 |
'''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
#
... | 47 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : int = logging.get_logger(__name__)
UpperCAmelCase : List[str] = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/confi... | 721 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoM... | 47 | 0 |
'''simple docstring'''
import requests
UpperCAmelCase : List[str] = '' # <-- Put your OpenWeatherMap appid here!
UpperCAmelCase : Optional[Any] = 'https://api.openweathermap.org/data/2.5/'
def _a ( lowerCAmelCase_ = "Chicago" , lowerCAmelCase_ = APPID ):
... | 700 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[str] = logging.get_logger(__name__)
UpperCAmelCase : Dict = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d... | 47 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Union[str, Any] = {'c... | 701 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _a ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : List[Any] = 0
if start < end:
... | 47 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase : Dict = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
... | 702 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 47 | 0 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : int = logging.get_logger(__name__)
# TODO Update this
UpperCAmelCase : Optional[int] = {
'... | 703 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_t... | 47 | 0 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_available():
import torch
f... | 704 |
'''simple docstring'''
from collections.abc import Generator
def _a ( ):
"""simple docstring"""
_snake_case , _snake_case : Union[str, Any] = 0, 1
while True:
_snake_case , _snake_case : List[str] = b, a + b
... | 47 | 0 |
'''simple docstring'''
from __future__ import annotations
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : Tuple = position
_snake_case : List[Any] = [
(y + 1, x + 2),
(y - 1, x + 2)... | 705 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCAmelCase : str = logging.getLogger(__name__)
UpperCAmelCas... | 47 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool
if TYPE_CHECKING:
from PIL import Image
class lowerCamelCase (a__ ):
_lowercase : int ... | 706 |
'''simple docstring'''
from __future__ import annotations
def _a ( lowerCAmelCase_ , lowerCAmelCase_ = None , lowerCAmelCase_ = None ):
"""simple docstring"""
if start is None:
_snake_case : Optional[Any] = 0
if end is None:
... | 47 | 0 |
'''simple docstring'''
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust... | 707 |
'''simple docstring'''
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers i... | 47 | 0 |
from __future__ import annotations
from collections import Counter
from random import random
class lowerCamelCase :
def __init__( self ) -> str:
"""simple docstring"""
_snake_case : List[str] = {}
def UpperCAmelCase_ ( self ... | 708 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class lowerCamelCase (unittest.TestCase ):
def UpperCAmelCase_ ( self ) ... | 47 | 0 |
'''simple docstring'''
from PIL import Image
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
_snake_case , _snake_case : Optional[int] = image.size
_snake_case : Optional[Any] = 0
_snake_case : Any = image.load... | 709 |
'''simple docstring'''
UpperCAmelCase : Union[str, Any] = tuple[float, float, float]
UpperCAmelCase : int = tuple[float, float, float]
def _a ( lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case : str = end_poin... | 47 | 0 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class lowerCamelCase (unittest.TestCase ):
_lowercase : Tuple... | 710 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
UpperCAmelCase : List[st... | 47 | 0 |
'''simple docstring'''
import warnings
from typing import List
from unittest.mock import Mock
import torch
from torch.utils.data import DataLoader, IterableDataset, TensorDataset
from accelerate.accelerator import Accelerator
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase ... | 711 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if n == 1 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
return 0
elif n == 2:
return 1
else:
_snake_case : Union[str, Any] = [0, ... | 47 | 0 |
'''simple docstring'''
def _a ( lowerCAmelCase_ ):
"""simple docstring"""
if not isinstance(a_ , a_ ):
raise ValueError('''multiplicative_persistence() only accepts integral values''' )
if num < 0:
raise ValueError('''multi... | 712 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCAmelCase : Any = TypeVar('T')
UpperCAmelCase : str = TypeVar('U')
class lowerCamelCase (Generic[T, U] ):
def __init__( self ... | 47 | 0 |
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