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'''
def lowercase (_A ):
"""simple docstring"""
if not isinstance(_A , _A ) or number < 0:
raise ValueError('Input must be a non-negative integer' )
_lowerCAmelCase : Union[str,... | 630 |
'''simple docstring'''
from typing import Any
def lowercase (_A ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase : Optional[int] = [input_list.count(_A ) for value... | 630 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : List[str] = logging.get_logger(__name__)
lowerCAmelCase : Optional[Any] = {
"""facebook/xglm-564M""": """https://huggingface.co/face... | 630 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 | 1 |
'''simple docstring'''
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
lowerCAmelCase : str = {
"""E""": 12.70,
"""T""": 9.06,
"""A""": 8.17,
"""O""": 7.51,
"""I""": 6.97,
"""N""": 6.75,
"""S""": 6.33,
"... | 630 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 1 |
'''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransfor... | 630 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 1 |
'''simple docstring'''
import qiskit
def lowercase (_A = 2 ):
"""simple docstring"""
_lowerCAmelCase : str = qubits
# Using Aer's simulator
_lowerCAmelCase : Any = qiskit.Aer... | 630 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcess... | 630 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = 42
__magic_name__ = 42
def lowercase (_A... | 630 |
'''simple docstring'''
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 UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 1 |
'''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/lic... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_si... | 630 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 1 |
'''simple docstring'''
def lowercase ():
"""simple docstring"""
return 1
def lowercase (_A ):
"""simple docstring"""
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
... | 630 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, ... | 630 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 1 |
'''simple docstring'''
def lowercase (_A = 4_0_0_0_0_0_0 ):
"""simple docstring"""
_lowerCAmelCase : int = [0, 1]
_lowerCAmelCase : Union[str, Any] = 0
while fib[i] <= n:
fib... | 630 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 1 |
'''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
... | 630 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...util... | 630 | 1 |
'''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 1 |
'''simple docstring'''
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers ... | 630 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 | 1 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
def a ( self ):
'''simple docstring'''
_lowerCAmelCase : Union[str, ... | 630 | 1 |
'''simple docstring'''
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
lowerCAmelCase : Dict = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.a... | 630 |
'''simple docstring'''
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = (boundary[1] - boundary[0]) / steps
_lowerCAmelCase : Any = boundary[0]
_low... | 630 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImag... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase : int = {
"""configuration_trocr""... | 630 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler... | 630 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase (_A = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values()... | 630 | 1 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCAmelCase : int = False... | 630 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase :... | 630 | 1 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInp... | 630 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowercase (_A , _A ):
... | 630 | 1 |
'''simple docstring'''
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_a... | 630 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 630 | 1 |
'''simple docstring'''
from __future__ import annotations
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case__ , snake_case__ ):
'''simple docstring'''
_lowerCAmelCase , _lowerCAmelCase ... | 630 |
'''simple docstring'''
from typing import Any
def lowercase (_A ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase : Optional[int] = [input_list.count(_A ) for value... | 630 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 | 1 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase : ... | 630 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case__ ):
'''simple docstring'''
_lowerCAmelCase :... | 630 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 1 |
'''simple docstring'''
import qiskit
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit act... | 630 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 1 |
'''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... | 630 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = ["transformers", "torch", "note_seq"]
def __init__( self ... | 630 |
'''simple docstring'''
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 UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, tor... | 630 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 1 |
'''simple docstring'''
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCAmelCase : Union[str, Any] = version.parse(importlib_metadata.version("""nltk"""))
if NLTK_VERSION >= version.Ve... | 630 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 1 |
'''simple docstring'''
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import data... | 630 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 1 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers,... | 630 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class UpperCamelCase__ :
"""simple docstring"""
__magic_name__ = None
__magic_name__ = Fa... | 630 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...util... | 630 | 1 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
if edge <= 0 or not isinstance(_A , _A ):
raise ValueError('Length must be a positive.' )
return 3 * ((2_5 + 1_0 * (5 ** (1 / 2))) ** (1 / 2... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 1 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 | 1 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
def a ( self ):
'''simple docstring'''
_lowerCAmelCase : Union[str, ... | 630 | 1 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenizatio... | 630 |
'''simple docstring'''
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = (boundary[1] - boundary[0]) / steps
_lowerCAmelCase : Any = boundary[0]
_low... | 630 | 1 |
'''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
lowerCAmelCase : Union[str, Any] = object()
# For specifying empty leaf dic... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase : int = {
"""configuration_trocr""... | 630 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : List[Any] = [True] * limit
_lowerCAmelCase : Optional[int] = Fal... | 630 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase (_A = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values()... | 630 | 1 |
'''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... | 630 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase :... | 630 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : ... | 630 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowercase (_A , _A ):
... | 630 | 1 |
'''simple docstring'''
lowerCAmelCase : Dict = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],
"""G"""... | 630 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 630 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,... | 630 |
'''simple docstring'''
from typing import Any
def lowercase (_A ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase : Optional[int] = [input_list.count(_A ) for value... | 630 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
lowerCAmelCase : Dict = logging.get_logger(__name__)
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
... | 630 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 | 1 |
'''simple docstring'''
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,
BaseMo... | 630 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 1 |
'''simple docstring'''
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
... | 630 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 1 |
'''simple docstring'''
from collections import deque
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case__ , snake_case__ , snake_case__ ):
'''simple docstring'''
_lowerCAmelCase : ... | 630 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowercase (_A ): # This function is recursive
"""simple docstring"""
_lowerCAmelCase : List[str] = len(_A )
# If the array contains only ... | 630 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 1 |
'''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
lowerCAmelCase : Optional[int] = logging.... | 630 |
'''simple docstring'''
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 UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 1 |
'''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.j... | 630 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate i... | 630 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 1 |
'''simple docstring'''
from __future__ import annotations
import queue
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , snake_case__ ):
'''simple docstring'''
_lowerCAmelCase : int = ... | 630 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import ... | 630 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase : Dict = {
"""configuration_swiftformer""": [
"""SWIFTFORMER_PRETRAINED_CONFIG_ARCHI... | 630 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...util... | 630 | 1 |
'''simple docstring'''
# flake8: noqa
# Lint as: python3
lowerCAmelCase : Optional[Any] = [
"""VerificationMode""",
"""Version""",
"""disable_progress_bar""",
"""enable_progress_bar""",
"""is_progress_bar_enabled""",
"""experimental""",
]
from .in... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_i... | 630 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : List[str] = {
"""configuration_deberta"... | 630 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
def a ( self ):
'''simple docstring'''
_lowerCAmelCase : Union[str, ... | 630 | 1 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
if not isinstance(_A , _A ):
raise ValueError('Input must be an integer' )
if input_num <= 0:
raise ValueError('Input must be... | 630 |
'''simple docstring'''
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = (boundary[1] - boundary[0]) / steps
_lowerCAmelCase : Any = boundary[0]
_low... | 630 | 1 |
'''simple docstring'''
def lowercase (_A , _A = False ):
"""simple docstring"""
if not isinstance(_A , _A ):
_lowerCAmelCase : Optional[Any] = f'Expected string as input, found {type(_A )}... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase : int = {
"""configuration_trocr""... | 630 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 630 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase (_A = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values()... | 630 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipelin... | 630 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase :... | 630 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...util... | 630 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowercase (_A , _A ):
... | 630 | 1 |
'''simple docstring'''
def lowercase (_A , _A ):
"""simple docstring"""
def get_matched_characters(_A , _A ) -> str:
_lowerCAmelCase : List[str] = []
_lowerCAmelCase : ... | 630 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 630 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowerCAmelCase : Tuple = logging.get_logger(__name__)
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
... | 630 |
'''simple docstring'''
from typing import Any
def lowercase (_A ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase : Optional[int] = [input_list.count(_A ) for value... | 630 | 1 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 | 1 |
'''simple docstring'''
from __future__ import annotations
lowerCAmelCase : Tuple = tuple[int, int, int]
lowerCAmelCase : Optional[Any] = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
lowerCAmelCase : L... | 630 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_... | 630 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 1 |
'''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.or... | 630 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 1 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase (_A = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values()... | 630 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 1 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
assert (
isinstance(_A , _A ) and number_of_steps > 0
), f'number_of_steps needs to be positive integer, your input {number_of_steps}'
if n... | 630 |
'''simple docstring'''
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 UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 1 |
'''simple docstring'''
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
f... | 630 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDCondition... | 630 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
lowerCAmelCase : Optional[Any] = {"""tokenization_byt5""": ["""ByT5Tokenizer"""]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
... | 630 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
... | 630 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 1 |
'''simple docstring'''
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
... | 630 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...util... | 630 | 1 |
'''simple docstring'''
def lowercase (_A = 5_0 ):
"""simple docstring"""
_lowerCAmelCase : List[str] = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_leng... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 1 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ... | 630 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Optional[Any] = year % 1_9
_lowerCAmelCase : Any = ... | 630 | 1 |
'''simple docstring'''
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 UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
def a ( self ):
'''simple docstring'''
_lowerCAmelCase : Union[str, ... | 630 | 1 |
'''simple docstring'''
import numpy as np
lowerCAmelCase : Optional[Any] = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"... | 630 |
'''simple docstring'''
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = (boundary[1] - boundary[0]) / steps
_lowerCAmelCase : Any = boundary[0]
_low... | 630 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...imag... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase : int = {
"""configuration_trocr""... | 630 | 1 |
'''simple docstring'''
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u bel... | 630 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def lowercase (_A = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values()... | 630 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Dict = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Nllb... | 630 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase :... | 630 | 1 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class Upper... | 630 |
'''simple docstring'''
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase : List[str] = ["""tests.fixtures.files""", """tests.fixtures.hub""", """tests.fixtures.fsspec"""]
def lowercase (_A , _A ):
... | 630 | 1 |
'''simple docstring'''
import operator as op
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Union[str, Any] = []
_lowerCAmelCase : List[str] = lambda _A , _A ... | 630 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseMod... | 630 | 1 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCAmelCase : Any = input("""Enter image url: """).strip()
print(F'''Downloading image from {url} ...''')
lowerCAmelCase ... | 630 |
'''simple docstring'''
from typing import Any
def lowercase (_A ):
"""simple docstring"""
if not input_list:
return []
_lowerCAmelCase : Optional[int] = [input_list.count(_A ) for value... | 630 | 1 |
'''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 UpperC... | 630 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from ... | 630 | 1 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
lowerCAmelCase : str = logging.getLogger(__name__)
class UpperCamelCase__ ... | 630 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, l... | 630 | 1 |
'''simple docstring'''
import numpy as np
def lowercase (_A ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 630 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__magic_name__ = (DDPMScheduler,)
... | 630 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowerCAmelCase : Optional[int] = {
"""config""": [
"""EXTERNAL_DATA_FORMAT_SIZE_LIMIT""",
"""OnnxConfig""",
"""OnnxConfigWithPast""",
"""OnnxSeq2S... | 630 |
'''simple docstring'''
import socket
def lowercase ():
"""simple docstring"""
_lowerCAmelCase : Tuple = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
_lowerCAmelCase : Optional[int] ... | 630 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : List[str] = logging.get_logger(__name__)
lowerCAmelCase : Optional[Any] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve... | 630 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCAmelCase : Tuple = False
lowerCAmelCase : str = True
lowerCAmelCase ... | 630 | 1 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable... | 630 |
'''simple docstring'''
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 UpperCamelCase__ ( tf.keras.layers.Layer ):... | 630 | 1 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
lowerCAmelCase : Any = """\
"""
lowerCAmelCase : Union[str, A... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
... | 630 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.ex... | 630 |
'''simple docstring'''
lowerCAmelCase : Optional[int] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : str = 0
... | 630 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : List[Any] = logging.get_logger(__name__)
lowerCAmelCase : int = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https... | 630 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 630 | 1 |
'''simple docstring'''
lowerCAmelCase : Any = """
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install ... | 630 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import F... | 630 | 1 |
'''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
... | 630 |
'''simple docstring'''
def lowercase (_A ):
"""simple docstring"""
_lowerCAmelCase : Dict = len(_A )
while cur > 1:
# Find the maximum number in arr
_lowerCAmelCase : int ... | 630 | 1 |
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