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 |
|---|---|---|---|---|
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
__UpperCamelCase : Optional[int] = 1.0_5457_1817E-34 # unit of ℏ : J * s
__UpperCamelCase : str = 3E8 # unit ... | 641 |
import math
import qiskit
def snake_case_ ( __lowercase = 1 , __lowercase = 1 , __lowercase = 1 ):
if (
isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , _... | 641 | 1 |
__UpperCamelCase : Any = 'Input must be a string of 8 numbers plus letter'
__UpperCamelCase : int = 'TRWAGMYFPDXBNJZSQVHLCKE'
def snake_case_ ( __lowercase ):
if not isinstance(__lowercase , __lowercase ):
UpperCAmelCase_ :... | 641 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Any = logging.get_logger(__name__)
__UpperCamelCase : Dict = {
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/... | 641 | 1 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCAmelCase__( snake_case__ ):
'''simple docstring'''
A_ : Any = 'EncodecFeatureExtractor'
A_ : Dic... | 641 |
import fire
from utils import calculate_rouge, save_json
def snake_case_ ( __lowercase , __lowercase , __lowercase=None , **__lowercase ):
UpperCAmelCase_ : Tuple = [x.strip() for x in open(__lowercase ).readlines()]
UpperCAmelCase_ ... | 641 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 641 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterM... | 641 | 1 |
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import... | 641 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__UpperCamelCase : Dict = R'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control t... | 641 | 1 |
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
__UpperCamelCase : str = [
'kernels/rwkv/wkv_cuda.cu',
'kernels/rwkv/wkv_op.cpp',
'kernels/deformable_detr/ms_deform_attn.h',
'kernels/deformable_detr/cuda/ms_defo... | 641 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def snake_case_ ( ):
UpperCAmelCase_ : str = HfArgumentParser(__lowercase )
UpperCAmelCase_ : Optional[Any] = parser.parse_args_into_dataclasses()[0]
UpperC... | 641 | 1 |
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
__UpperCamelCase : int = logging.get_logger(__name__)
class lowerCAmelCase__( snake_case__ ):
'''simple docstring'''
def __i... | 641 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : str = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
... | 641 | 1 |
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import Fl... | 641 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case_ ( __lowercase , __lowercase ):
# Lo... | 641 | 1 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_di... | 641 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaToke... | 641 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
__UpperCamelCase : List[str] = logging.get_l... | 641 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : str = {
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'... | 641 | 1 |
def snake_case_ ( __lowercase , __lowercase , __lowercase ):
def update_area_of_max_square(__lowercase , __lowercase ) -> int:
# BASE CASE
if row >= rows or col >= cols:
return 0
UpperCAmelCase_ : int = update_a... | 641 |
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__( snake_case__ ... | 641 | 1 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import F... | 641 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowerCAmelCase__:
'''simple docstring'''
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Ten... | 641 | 1 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class lowerCAmelCase__( ... | 641 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, reca... | 641 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 641 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Tuple = logging.get_logger(__name__)
class lowerCAmelCase__( snake_case__ ):
'''simple docstring'''
A_ : Union[str, ... | 641 | 1 |
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope='''session''' )
def snake_case_ ( ):
Up... | 641 |
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 Image
from transformers import (
... | 641 | 1 |
from __future__ import annotations
def snake_case_ ( __lowercase , __lowercase ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(__lowercase ):
print(F'''{i}\t\t{d}''' )
def snake_case_ ( __lowercase , _... | 641 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def snake_case_ ( __lowercase , __low... | 641 | 1 |
import string
def snake_case_ ( __lowercase ):
UpperCAmelCase_ : Optional[int] = ''''''
for i in sequence:
UpperCAmelCase_ : Optional[Any] = ord(__lowercase )
if 6_5 <= extract <= 9_0:
output += chr(1_5_5 - extract )
... | 641 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : str = logging.get_logger(__name__)
__UpperCamelCase : Any = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'ti... | 641 | 1 |
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__UpperCamelCase : Tuple = '.'
if __name__ == "__main__":
__UpperCamelCase : List[Any] = os.path.join... | 641 |
def snake_case_ ( __lowercase ):
return " ".join(
''''''.join(word[::-1] ) if len(__lowercase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words('Hey wollef... | 641 | 1 |
from __future__ import annotations
def snake_case_ ( __lowercase ):
if len(__lowercase ) == 0:
return array
UpperCAmelCase_ , UpperCAmelCase_ : Union[str, Any] = min(__lowercase ), max(__lowercase )
# Compute the variables
Upper... | 641 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
fr... | 641 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin,... | 641 |
# 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
#
# Unless require... | 641 | 1 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FIL... | 641 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self : List[str] , __snake_case : Union[str, Any] ):
'''simple docstring'''
... | 641 | 1 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__UpperCamelCase : Tuple = get_logger(__name__)
class lowerCAmelCase__( enum.Enum ):
'''simple docstring'''
... | 641 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : int = logging.get_logger(__name__)
__UpperCamelCase : Union[str, Any] = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/conf... | 641 | 1 |
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
... | 641 |
import math
import qiskit
def snake_case_ ( __lowercase = 1 , __lowercase = 1 , __lowercase = 1 ):
if (
isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , _... | 641 | 1 |
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 Image
from transformers import (
... | 641 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Any = logging.get_logger(__name__)
__UpperCamelCase : Dict = {
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/... | 641 | 1 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, reca... | 641 |
import fire
from utils import calculate_rouge, save_json
def snake_case_ ( __lowercase , __lowercase , __lowercase=None , **__lowercase ):
UpperCAmelCase_ : Tuple = [x.strip() for x in open(__lowercase ).readlines()]
UpperCAmelCase_ ... | 641 | 1 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from tr... | 641 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterM... | 641 | 1 |
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import ConfigTester
... | 641 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__UpperCamelCase : Dict = R'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control t... | 641 | 1 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
... | 641 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def snake_case_ ( ):
UpperCAmelCase_ : str = HfArgumentParser(__lowercase )
UpperCAmelCase_ : Optional[Any] = parser.parse_args_into_dataclasses()[0]
UpperC... | 641 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCamelCase : Any = logging.get_logger(__name__)
__UpperCamelCase : List[Any] = ... | 641 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : str = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
... | 641 | 1 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterM... | 641 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case_ ( __lowercase , __lowercase ):
# Lo... | 641 | 1 |
def snake_case_ ( __lowercase , __lowercase ):
return int((input_a, input_a).count(0 ) == 0 )
def snake_case_ ( ):
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
ass... | 641 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaToke... | 641 | 1 |
def snake_case_ ( __lowercase , __lowercase ):
return int((input_a, input_a).count(1 ) != 0 )
def snake_case_ ( ):
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
assert or_gate(1 , 0 ) == 1
assert... | 641 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : str = {
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'... | 641 | 1 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
i... | 641 |
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__( snake_case__ ... | 641 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__UpperCamelCase : int = {
'speechbrain/m-ctc-t-large': 'https://huggingface.co/speechbrain/m-ctc-t-large/resolve/mai... | 641 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowerCAmelCase__:
'''simple docstring'''
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Ten... | 641 | 1 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def snake_case_ ( __lowercase , __lowercase ):
assert isins... | 641 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, reca... | 641 | 1 |
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_available
from ...test_configuration_co... | 641 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Tuple = logging.get_logger(__name__)
class lowerCAmelCase__( snake_case__ ):
'''simple docstring'''
A_ : Union[str, ... | 641 | 1 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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, random_attenti... | 641 |
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 Image
from transformers import (
... | 641 | 1 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__UpperCamelCase : Optional[int] = {
't5-s... | 641 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def snake_case_ ( __lowercase , __low... | 641 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCamelCase : Any = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
... | 641 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : str = logging.get_logger(__name__)
__UpperCamelCase : Any = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'ti... | 641 | 1 |
from sklearn.metrics import fa_score
import datasets
__UpperCamelCase : Dict = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
__UpperCamelCase : int = ... | 641 |
def snake_case_ ( __lowercase ):
return " ".join(
''''''.join(word[::-1] ) if len(__lowercase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words('Hey wollef... | 641 | 1 |
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compute_met... | 641 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
fr... | 641 | 1 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
D... | 641 |
# 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
#
# Unless require... | 641 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, Patchi... | 641 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self : List[str] , __snake_case : Union[str, Any] ):
'''simple docstring'''
... | 641 | 1 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
fr... | 641 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : int = logging.get_logger(__name__)
__UpperCamelCase : Union[str, Any] = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/conf... | 641 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__UpperCamelCase : List[str] = {'processing_wav2vec2_with_lm': ['Wav2Vec2ProcessorWithLM']}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
... | 641 |
import math
import qiskit
def snake_case_ ( __lowercase = 1 , __lowercase = 1 , __lowercase = 1 ):
if (
isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , _... | 641 | 1 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self : Union[str, Any] , __snake_case : Optional[Any] , __snake_case : int , __snake_case ... | 641 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Any = logging.get_logger(__name__)
__UpperCamelCase : Dict = {
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/... | 641 | 1 |
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class lower... | 641 |
import fire
from utils import calculate_rouge, save_json
def snake_case_ ( __lowercase , __lowercase , __lowercase=None , **__lowercase ):
UpperCAmelCase_ : Tuple = [x.strip() for x in open(__lowercase ).readlines()]
UpperCAmelCase_ ... | 641 | 1 |
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()
except OptionalDependencyNotAvaila... | 641 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterM... | 641 | 1 |
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import ConfigMixin, register_to_config
from diffusers.schedulers.scheduling_utils import SchedulerMixin
from diffusers.utils import BaseOutput... | 700 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__UpperCamelCase : Dict = R'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control t... | 641 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
__UpperCamelCase : Tuple = {
'configuration_ernie': ['ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieConfig', 'ErnieOnnxConfig'],
}
... | 701 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def snake_case_ ( ):
UpperCAmelCase_ : str = HfArgumentParser(__lowercase )
UpperCAmelCase_ : Optional[Any] = parser.parse_args_into_dataclasses()[0]
UpperC... | 641 | 0 |
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def snake_case_ ( __lowercase ):
UpperCAmelCase_ : str = [
'''encoder.version''',
'''decoder.version''',
'''model.encoder.vers... | 702 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : str = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
... | 641 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Any = logging.get_logger(__name__)
__UpperCamelCase : Optional[int] = {
"microsoft/swinv2-tiny-patch4-window8-256": (
"https://huggingface.co/microsoft/swinv2-tin... | 703 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case_ ( __lowercase , __lowercase ):
# Lo... | 641 | 0 |
def snake_case_ ( __lowercase , __lowercase ):
_enforce_args(_lowercase , _lowercase )
if n == 0:
return 0
UpperCAmelCase_ : List[Any] = float('''-inf''' )
for i in range(1 , n + 1 ):
UpperCAmelCase_ : ... | 704 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaToke... | 641 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def snake_case_ ( __lowercase ):
UpperCAmelCase_... | 705 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : str = {
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'... | 641 | 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,
Eul... | 706 |
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__( snake_case__ ... | 641 | 0 |
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_configuration_common impo... | 707 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowerCAmelCase__:
'''simple docstring'''
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Ten... | 641 | 0 |
def snake_case_ ( __lowercase , __lowercase , __lowercase = 0 , __lowercase = 0 ):
UpperCAmelCase_ : List[Any] = right or len(__A ) - 1
if left > right:
return -1
elif list_data[left] == key:
return left
elif list_data[right] ... | 708 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, reca... | 641 | 0 |
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.utils.testi... | 709 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Tuple = logging.get_logger(__name__)
class lowerCAmelCase__( snake_case__ ):
'''simple docstring'''
A_ : Union[str, ... | 641 | 0 |
import sys
from collections import defaultdict
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self : str ):
'''simple docstring'''
UpperCAmelCase_ : Optional[Any] = []
def _lowerCamelCas... | 710 |
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 Image
from transformers import (
... | 641 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
__UpperCamelCase : int = loggi... | 711 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def snake_case_ ( __lowercase , __low... | 641 | 0 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Any = logging.get_logger(__name__)
__UpperCamelCase : str = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base... | 712 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : str = logging.get_logger(__name__)
__UpperCamelCase : Any = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'ti... | 641 | 0 |
'''simple docstring'''
import torch
def snake_case_ ( ):
if torch.cuda.is_available():
UpperCAmelCase_ : List[str] = torch.cuda.device_count()
else:
UpperCAmelCase_ : List[Any] = 0
print(F'''Successfully ran on {num_... | 713 |
def snake_case_ ( __lowercase ):
return " ".join(
''''''.join(word[::-1] ) if len(__lowercase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words('Hey wollef... | 641 | 0 |
'''simple docstring'''
import argparse
from collections import defaultdict
def snake_case_ ( __lowercase , __lowercase , __lowercase , __lowercase , __lowercase ):
UpperCAmelCase_ : Tuple = F'''{file}_{class_name}_{test_name}'''
... | 714 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
fr... | 641 | 0 |
from __future__ import annotations
__UpperCamelCase : Optional[int] = "Muhammad Umer Farooq"
__UpperCamelCase : Optional[Any] = "MIT"
__UpperCamelCase : Any = "1.0.0"
__UpperCamelCase : Tuple = "Muhammad Umer Farooq"
__UpperCam... | 715 |
# 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
#
# Unless require... | 641 | 0 |
from math import isqrt
def snake_case_ ( __lowercase ):
return all(number % divisor != 0 for divisor in range(2 , isqrt(_lowerCamelCase ) + 1 ) )
def snake_case_ ( __lowercase = 1_0**6 ):
UpperCAmelCase_ : Dict = 0
UpperCAme... | 716 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self : List[str] , __snake_case : Union[str, Any] ):
'''simple docstring'''
... | 641 | 0 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s',
datefmt='%m/%d/%Y %H:%M:%S',
level=logging.INFO,
)
__UpperCamelCase : Any ... | 717 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : int = logging.get_logger(__name__)
__UpperCamelCase : Union[str, Any] = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/conf... | 641 | 0 |
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
__UpperCamelCase : List[str] ... | 718 |
import math
import qiskit
def snake_case_ ( __lowercase = 1 , __lowercase = 1 , __lowercase = 1 ):
if (
isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , _... | 641 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Any = logging.get_logger(__name__)
__UpperCamelCase : Dict = {
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/... | 641 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from... | 720 |
import fire
from utils import calculate_rouge, save_json
def snake_case_ ( __lowercase , __lowercase , __lowercase=None , **__lowercase ):
UpperCAmelCase_ : Tuple = [x.strip() for x in open(__lowercase ).readlines()]
UpperCAmelCase_ ... | 641 | 0 |
from __future__ import annotations
def snake_case_ ( __lowercase , __lowercase ):
UpperCAmelCase_ : List[str] = sorted(numsa + numsa )
UpperCAmelCase_ : Dict = divmod(len(__UpperCamelCase ) , 2 )
if mod == 1:
... | 721 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterM... | 641 | 0 |
import copy
import re
class lowerCAmelCase__:
'''simple docstring'''
A_ : Tuple = '''hp'''
A_ : Optional[Any] = {}
A_ : Optional[Any] = None
@classmethod
def _lowerCamelCase ( cls : List[str] , __snak... | 700 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__UpperCamelCase : Dict = R'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control t... | 641 | 0 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaag... | 701 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def snake_case_ ( ):
UpperCAmelCase_ : str = HfArgumentParser(__lowercase )
UpperCAmelCase_ : Optional[Any] = parser.parse_args_into_dataclasses()[0]
UpperC... | 641 | 0 |
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def snake_case_ ( __lowercase , ... | 702 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : str = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
... | 641 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class lowerCAmelCase__( Upp... | 703 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case_ ( __lowercase , __lowercase ):
# Lo... | 641 | 0 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def snake_case_ ( __lowercase , __lowercase , __lowercase ):
UpperCAmelCase_ : Optional[Any] = 0
if start < end:
UpperCAmelCase_ : Union[str, Any] ... | 704 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaToke... | 641 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from... | 705 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : str = {
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'... | 641 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCamelCase : Optional[int] = {
'configuration_efficientnet': [
... | 706 |
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__( snake_case__ ... | 641 | 0 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have ... | 707 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowerCAmelCase__:
'''simple docstring'''
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Ten... | 641 | 0 |
import numpy as np
import torch
from ..models.clipseg import CLIPSegForImageSegmentation
from ..utils import is_vision_available, requires_backends
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class lowerCAmelCase__( _UpperCAmelCase ):
... | 708 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, reca... | 641 | 0 |
from __future__ import annotations
from collections import namedtuple
def snake_case_ ( __lowercase , __lowercase , __lowercase ):
UpperCAmelCase_ : Optional[Any] = namedtuple('''result''' , '''name value''' )
if (voltage, current, power)... | 709 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Tuple = logging.get_logger(__name__)
class lowerCAmelCase__( snake_case__ ):
'''simple docstring'''
A_ : Union[str, ... | 641 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 710 |
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 Image
from transformers import (
... | 641 | 0 |
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def snake_case_ ( __lowercase ):
if not is_accelerate_available():
return method
UpperCAmelCase_ : List[str] = version.p... | 711 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def snake_case_ ( __lowercase , __low... | 641 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
__UpperCamelCase : str = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
... | 712 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : str = logging.get_logger(__name__)
__UpperCamelCase : Any = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'ti... | 641 | 0 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffuse... | 713 |
def snake_case_ ( __lowercase ):
return " ".join(
''''''.join(word[::-1] ) if len(__lowercase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words('Hey wollef... | 641 | 0 |
'''simple docstring'''
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self : Optional[int] , __snake_case : list ):
'''simple docstring'''
UpperCAmelCase_ : Tuple = set_counts
UpperCAmel... | 714 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
fr... | 641 | 0 |
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
... | 715 |
# 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
#
# Unless require... | 641 | 0 |
__UpperCamelCase : dict[str, float] = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 1000000,
"gigajoule": 1000000000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 3600000,
"newtonmeter": 1.0,
"calorie_nutr": 4_186.8,
"kilocalorie_nutr... | 716 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self : List[str] , __snake_case : Union[str, Any] ):
'''simple docstring'''
... | 641 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_... | 717 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : int = logging.get_logger(__name__)
__UpperCamelCase : Union[str, Any] = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/conf... | 641 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase : Any = {
'configuration_deberta': ['DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MA... | 718 |
import math
import qiskit
def snake_case_ ( __lowercase = 1 , __lowercase = 1 , __lowercase = 1 ):
if (
isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , __lowercase )
or isinstance(__lowercase , _... | 641 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Optional[Any] = {
'configuration_mgp_str': ['MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MgpstrConfig'],
'processing_mgp_str': ['MgpstrProcess... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Any = logging.get_logger(__name__)
__UpperCamelCase : Dict = {
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/... | 641 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Optional[int] = logging.get_logger(__name__)
__UpperCamelCase : str = {}
class lowerCAmelCase__( __lowercase ):
'''simple docstr... | 720 |
import fire
from utils import calculate_rouge, save_json
def snake_case_ ( __lowercase , __lowercase , __lowercase=None , **__lowercase ):
UpperCAmelCase_ : Tuple = [x.strip() for x in open(__lowercase ).readlines()]
UpperCAmelCase_ ... | 641 | 0 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.mode... | 721 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterM... | 641 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
__UpperCamelCase : Dict = pd.read_csv('sample_data.csv', header=None)
... | 700 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__UpperCamelCase : Dict = R'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control t... | 641 | 0 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
__UpperCamelCase : Optional[int] = False
class lowerCAmelCase__( ... | 701 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def snake_case_ ( ):
UpperCAmelCase_ : str = HfArgumentParser(__lowercase )
UpperCAmelCase_ : Optional[Any] = parser.parse_args_into_dataclasses()[0]
UpperC... | 641 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCamelCase : Union[str, Any] = {
'configuration_groupvit': [
'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'GroupViTConfig',
... | 702 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__UpperCamelCase : str = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
... | 641 | 0 |
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMRobertaXLForSequenceClas... | 703 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case_ ( __lowercase , __lowercase ):
# Lo... | 641 | 0 |
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__( _UpperCAmelCase ):
'''simple docstring'''
... | 704 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaToke... | 641 | 0 |
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
requ... | 705 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : str = {
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'... | 641 | 0 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( __lowercase , __lowercase = None ):
UpperCAmelCase_ : Tuple = word_bank or []
# create a table
UpperCAmelCase_ : Optional[Any] = len(__lowercase ) +... | 706 |
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__( snake_case__ ... | 641 | 0 |
def snake_case_ ( __lowercase ):
if bit_count < 0:
raise ValueError('''The given input must be positive''' )
# get the generated string sequence
UpperCAmelCase_ : str = gray_code_sequence_string(lowercase_ )
#
# convert them to integers
... | 707 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class lowerCAmelCase__:
'''simple docstring'''
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Tensor # [batch_size x 3]
A_ : torch.Ten... | 641 | 0 |
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