code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class UpperCamelCase__( un... | 705 |
'''simple docstring'''
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def lowerCamelCase__ ( A : Optional[Any] , A : Tuple=1 ):
'''simple docstring'''
if n_shave_prefix_segments >= 0:
r... | 50 | 0 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
_lowercase : List[Any] = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and ... | 706 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : Dict = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encod... | 50 | 0 |
'''simple docstring'''
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCamelCase__ ( A : str , A : str = "cpu" , A : Union[str, None] = None ):
'''simple docstring'''
UpperCAmelCase = torch.load(A , ma... | 707 |
'''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,
DistilBertConfig,
DistilBe... | 50 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
_lowercase : str = logging.get_log... | 708 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : Tuple = ["image_processor", "tokenizer"]
__magic_name__ : Any = "ViT... | 50 | 0 |
'''simple docstring'''
import math
_lowercase : Optional[int] = 10
_lowercase : Optional[int] = 7
_lowercase : str = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCamelCase__ ( A : int = 20 ):
'''simple docstring'''
UpperCAmelCase =... | 709 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Any = {
"""configuration_maskformer""": ["""MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MaskFormerConfig"""],
... | 50 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_visio... | 710 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acceler... | 50 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Union[str, Any] = logging.get_logger(__name__)
_lowercase : Tuple = {
"""facebook/s2t-small-librispeech-asr""": (
"""https://huggingface.co/facebook/s2t-s... | 711 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 50 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase )
class UpperCamelCase__( lowerCAmelCase ):
# `task` is not a ClassVar since we want it... | 712 |
'''simple docstring'''
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Union[str, Any] = logging.get_logger(__name__)
_lowercase : List[str] = {
"""facebook/encodec_24khz""... | 50 | 0 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
_lowercase : Dict = [
"""kernels/rwkv/wkv_cuda.cu""",
"""kernels/rwkv/wkv_op.cpp""",
"""kernels/deformable_detr/ms_deform_attn.h""",
"""kernels/deformable_d... | 713 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team and The OpenBMB 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... | 50 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : ... | 714 |
'''simple docstring'''
import heapq
def lowerCamelCase__ ( A : dict ):
'''simple docstring'''
UpperCAmelCase = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Prior... | 50 | 0 |
'''simple docstring'''
import re
import string
import numpy as np
import datasets
_lowercase : List[str] = """
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
"""
_lowercase ... | 715 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
_lowercase : Optional[int] = """examples/"""
_lowercase : str = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
... | 50 | 0 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tens... | 716 |
'''simple docstring'''
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCriteria,... | 50 | 0 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
_lowercase : Optional[int] = [
# tf -> hf
("""/""", """."""),
("""layer_""",... | 717 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase__( metaclass=lowerCAmelCase ):
__magic_name__ : List[str] = ["note_seq"]
def __init__( self : Any , *lowerCAmelCase : List[str] , **lowerCAmelCase : int... | 50 | 0 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerat... | 718 |
'''simple docstring'''
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase__ ( A : List[Any] , A : int , A ... | 50 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
_lowercase : str = {
"""susnato/ernie-m-base_pytorch""": """https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json""",
"""susnato/ernie... | 719 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class UpperCamelCase__( unittest.TestCase ):
... | 50 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : List[Any] = {
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.json""",
... | 720 |
'''simple docstring'''
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCamelCase__ ( A : List[Any] ):
'''simple docstring'''
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
... | 50 | 0 |
'''simple docstring'''
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
fr... | 721 |
'''simple docstring'''
def lowerCamelCase__ ( A : str ):
'''simple docstring'''
assert column_title.isupper()
UpperCAmelCase = 0
UpperCAmelCase = len(A ) - 1
UpperCAmelCase = 0
while index >= 0:
UpperCAmelCase ... | 50 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
_lowercase : Union[str, Any] = {
"""Salesforce/blip-vqa-base""": """https... | 700 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 50 | 0 |
'''simple docstring'''
import functools
def lowerCamelCase__ ( A : list[int] , A : list[int] ):
'''simple docstring'''
if not isinstance(A , A ) or not all(isinstance(A , A ) for day in days ):
raise ValueError('''The parameter days shou... | 701 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_lowercase : str = logging.get_logger(__name_... | 50 | 0 |
from __future__ import annotations
_lowercase : List[Any] = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def lowerCamelCase__ ( A : list[list[int]] , A : list[int] , A : list[int] , A : int , A : ... | 702 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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
#
# ... | 50 | 0 |
'''simple docstring'''
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
class UpperCamelCase__:
__magic_name__ : str = None
@exp... | 703 |
'''simple docstring'''
import functools
def lowerCamelCase__ ( A : list[int] , A : list[int] ):
'''simple docstring'''
if not isinstance(A , A ) or not all(isinstance(A , A ) for day in days ):
raise ValueError('''The parameter days shou... | 50 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Tuple = logging.get_logger(__name__)
_lowercase : Optional[Any] = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Any = {
"""configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}
try... | 50 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase__( metaclass=lowerCAmelCase ):
__magic_name__ : List[str] = ["note_seq"]
def __init__( self : Any , *lowerCAmelCase : List[str] , **lowerC... | 705 |
'''simple docstring'''
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def lowerCamelCase__ ( A : Optional[Any] , A : Tuple=1 ):
'''simple docstring'''
if n_shave_prefix_segments >= 0:
r... | 50 | 0 |
'''simple docstring'''
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase__ ( A : List[Any] , A : int , A ... | 706 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : Dict = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encod... | 50 | 0 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common i... | 707 |
'''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,
DistilBertConfig,
DistilBe... | 50 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
... | 708 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : Tuple = ["image_processor", "tokenizer"]
__magic_name__ : Any = "ViT... | 50 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( A : int ):
'''simple docstring'''
UpperCAmelCase = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 709 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Any = {
"""configuration_maskformer""": ["""MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MaskFormerConfig"""],
... | 50 | 0 |
'''simple docstring'''
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
_lowercase : List[str] = namedtuple(
"""_TestCom... | 710 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acceler... | 50 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
def lowerCamelCase__ ( ):
'''simple docstring'''
UpperCAmelCase = {}
UpperCAmelCase = 2
while True:
UpperCAmelCase = factor_map.pop(A ... | 711 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 50 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class UpperCamelCase__( lowerCAmelCase ):
__m... | 712 |
'''simple docstring'''
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Union[str, Any] = logging.get_logger(__name__)
_lowercase : List[str] = {
"""facebook/encodec_24khz""... | 50 | 0 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..uti... | 713 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team and The OpenBMB 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... | 50 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Any = {
"""configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}
t... | 714 |
'''simple docstring'''
import heapq
def lowerCamelCase__ ( A : dict ):
'''simple docstring'''
UpperCAmelCase = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Prior... | 50 | 0 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_see... | 715 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
_lowercase : Optional[int] = """examples/"""
_lowercase : str = {
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
... | 50 | 0 |
'''simple docstring'''
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import comp... | 716 |
'''simple docstring'''
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCriteria,... | 50 | 0 |
'''simple docstring'''
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : Optional[Any] = "philschmid/bart-large-cnn-samsum"
__magic_name__ : Any = (
"This i... | 717 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase__( metaclass=lowerCAmelCase ):
__magic_name__ : List[str] = ["note_seq"]
def __init__( self : Any , *lowerCAmelCase : List[str] , **lowerCAmelCase : int... | 50 | 0 |
'''simple docstring'''
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCriteria,... | 718 |
'''simple docstring'''
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase__ ( A : List[Any] , A : int , A ... | 50 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( ):
for n in range(1 , 1_00_00_00 ):
yield n * (n + 1) // 2
def lowerCamelCase__ ( A : List[str] ):
UpperCAmelCase = 1
UpperCAmelCase = 2
while i * i <= n:
UpperCAmelCa... | 719 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class UpperCamelCase__( unittest.TestCase ):
... | 50 | 0 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql... | 720 |
'''simple docstring'''
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCamelCase__ ( A : List[Any] ):
'''simple docstring'''
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
... | 50 | 0 |
'''simple docstring'''
_lowercase : Tuple = {"""a""": ["""c""", """b"""], """b""": ["""d""", """e"""], """c""": [], """d""": [], """e""": []}
_lowercase : Any = ["""a""", """b""", """c""", """d""", """e"""]
def lowerCamelCase__ ( A : Any , A : List[Any] , ... | 721 |
'''simple docstring'''
def lowerCamelCase__ ( A : str ):
'''simple docstring'''
assert column_title.isupper()
UpperCAmelCase = 0
UpperCAmelCase = len(A ) - 1
UpperCAmelCase = 0
while index >= 0:
UpperCAmelCase ... | 50 | 0 |
"""simple docstring"""
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIV... | 51 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCamelCase__ = input("Enter image url: ").strip()
print(f"""Downloading image from {url} ...""")
lowerCamelCase__ = BeautifulSoup(requests.get(url).content, "ht... | 51 | 1 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
lowerCamelCase__ = parse(importlib.metadata.version("torch"))
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ) ... | 51 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
_UpperCamelC... | 51 | 1 |
"""simple docstring"""
lowerCamelCase__ = "\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/... | 51 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mask2FormerConfig",
... | 51 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase ... | 51 |
"""simple docstring"""
lowerCamelCase__ = "\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/... | 51 | 1 |
"""simple docstring"""
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def lowercase__ ( ) -> Any:
"""simple docstring"""
raise RuntimeError("CU... | 51 |
"""simple docstring"""
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_... | 51 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import Counter
from random import random
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Any ) -> Union[str, Any]:
_UpperCamelCase : int = {}
def... | 51 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
fro... | 51 | 1 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowercase__ ( lowercase_ = 1_000_000 ,lowercase_ = 10 ) -> int:
"""simple docstring"""
_UpperCamelCase : defaultdict = defaultdict(lowercase_ )
for outer_w... | 51 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.test... | 51 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch,... | 51 |
"""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__ = logging.get_logger(__name__)
lowerCamelCase__ = ... | 51 | 1 |
"""simple docstring"""
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__":
lowerCamelCase__ = pd.read_csv("sample_data.csv", header=None)
lowerC... | 51 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
lowerCamelCase__ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
lowerCamelCase__ = [ord(letter) for letter in string.asci... | 51 | 1 |
"""simple docstring"""
import argparse
import json
from tqdm import tqdm
def lowercase__ ( ) -> Dict:
"""simple docstring"""
_UpperCamelCase : Any = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" ,t... | 51 |
"""simple docstring"""
def lowercase__ ( lowercase_ ,lowercase_ ) -> None:
"""simple docstring"""
_UpperCamelCase : List[Any] = len(lowercase_ )
print("The following activities are selected:" )
# The first activity is always selected
_U... | 51 | 1 |
"""simple docstring"""
import os
def lowercase__ ( ) -> List[str]:
"""simple docstring"""
with open(os.path.dirname(lowercase_ ) + "/p022_names.txt" ) as file:
_UpperCamelCase : Optional[Any] = str(file.readlines()[0] )
_UpperCa... | 51 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get... | 51 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ) -> Dict:
... | 51 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCamelCase )
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
S... | 51 | 1 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvis... | 51 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> set:
"""simple docstring"""
_UpperCamelCase : Union[str, Any] = set()
# edges = list of graph's edges
_UpperCamelCase : Union[str, Any] = get_edges(lowercase_ )
# Whi... | 51 | 1 |
"""simple docstring"""
def lowercase__ ( ) -> list[list[int]]:
"""simple docstring"""
return [list(range(1_000 - i ,-1_000 - i ,-1 ) ) for i in range(1_000 )]
lowerCamelCase__ = generate_large_matrix()
lowerCamelCase__ = (
[[4, 3, 2, -1], [3, 2, 1, -... | 51 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase__ = {
"configuration_owlvit... | 51 | 1 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Optional[Any] , __a : list[int] ) -> None:
_UpperCamelCase : Tuple = len(__a )
_UpperCamelCase : Dict = [0] * len_arra... | 51 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowercase__ ( lowercase_ = 1_000_000 ,lowercase_ = 10 ) -> int:
"""simple docstring"""
_UpperCamelCase : defaultdict = defaultdict(lowercase_ )
for outer_w... | 51 | 1 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[int] = (UnCLIPScheduler,)
def ... | 51 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("KEY")
lowerCamelCase__ = TypeVar("VAL")
@dataclass(frozen=_UpperCamelCase , slots=_UpperCamelCase )
class __SCR... | 51 | 1 |
"""simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 51 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Optional[Any] , __a : list[int] ) -> None:
_UpperCamelCase : Tuple = len(__a )
_UpperCamelCase : Dict = [0] * len_arra... | 51 | 1 |
"""simple docstring"""
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( self : ... | 51 |
"""simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowercase__ ( lowercase_ ,lowercase_=7 ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = Non... | 51 | 1 |
"""simple docstring"""
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from t... | 51 |
"""simple docstring"""
import math
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( self : Any , __a : list[list[float]] , __a : list[int] ) -> int:
_UpperCamelCase : List[Any] = 0.0
... | 51 | 1 |
"""simple docstring"""
from collections import deque
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : List[Any] , __a : str , __a : int , __a : int ) -> None:
_UpperCamelCase : List[str] = ... | 51 |
"""simple docstring"""
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
lowerCamelCase__ = "src/transf... | 51 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_token... | 51 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCamelCase__ = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that g... | 51 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mask2FormerConfig",
... | 51 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 51 | 1 |
"""simple docstring"""
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def ... | 51 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCamelCase__ = input("Enter image url: ").strip()
print(f"""Downloading image from {url} ...""")
lowerCamelCase__ = BeautifulSoup(requests.get(url).content, "ht... | 51 | 1 |
"""simple docstring"""
from __future__ import annotations
lowerCamelCase__ = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
class __SCREAMING_SNAKE_CASE :
'''simple docstring'... | 51 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
_UpperCamelC... | 51 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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... | 51 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mask2FormerConfig",
... | 51 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCamelCase__ = {"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}
try:
if not is_torch_avail... | 51 |
"""simple docstring"""
lowerCamelCase__ = "\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/... | 51 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffu... | 51 |
"""simple docstring"""
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_... | 51 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_blenderbot": [
"BLENDER... | 51 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
fro... | 51 | 1 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
fr... | 51 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.test... | 51 | 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__ = logging.get_logger(__name__)
lowerCamelCase__ = ... | 51 |
"""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__ = logging.get_logger(__name__)
lowerCamelCase__ = ... | 51 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from t... | 51 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
lowerCamelCase__ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
lowerCamelCase__ = [ord(letter) for letter in string.asci... | 51 | 1 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def lowercase__ ( lowercase_ ) -> List[str]:
"""simple docstring"""
_UpperCamelCase : List[Any] = ... | 51 |
"""simple docstring"""
def lowercase__ ( lowercase_ ,lowercase_ ) -> None:
"""simple docstring"""
_UpperCamelCase : List[Any] = len(lowercase_ )
print("The following activities are selected:" )
# The first activity is always selected
_U... | 51 | 1 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCamelCase__ = {"UserAgent": UserAgent().random}
def lowercase__ ( lowercase_ ) -> dict:
"""simple docstring"""
... | 51 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get... | 51 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowercase_ ) -> float:
"""simple docstring"""
_UpperCamelCase : str = 0.00
_UpperCamelCase : int = 0
for resistor in resistors:
if resistor ... | 51 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCamelCase )
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
S... | 51 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accel... | 51 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> set:
"""simple docstring"""
_UpperCamelCase : Union[str, Any] = set()
# edges = list of graph's edges
_UpperCamelCase : Union[str, Any] = get_edges(lowercase_ )
# Whi... | 51 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.u... | 51 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase__ = {
"configuration_owlvit... | 51 | 1 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask... | 51 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowercase__ ( lowercase_ = 1_000_000 ,lowercase_ = 10 ) -> int:
"""simple docstring"""
_UpperCamelCase : defaultdict = defaultdict(lowercase_ )
for outer_w... | 51 | 1 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_a... | 51 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("KEY")
lowerCamelCase__ = TypeVar("VAL")
@dataclass(frozen=_UpperCamelCase , slots=_UpperCamelCase )
class __SCR... | 51 | 1 |
"""simple docstring"""
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
... | 51 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Optional[Any] , __a : list[int] ) -> None:
_UpperCamelCase : Tuple = len(__a )
_UpperCamelCase : Dict = [0] * len_arra... | 51 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCamelCase )
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''s... | 51 |
"""simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowercase__ ( lowercase_ ,lowercase_=7 ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = Non... | 51 | 1 |
"""simple docstring"""
from pathlib import Path
import fire
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ) -> List[str]:
"""simple docstring"""
_UpperCamelCase : str = Path(lowercase_ )
_UpperCamelCase : int = Path(lowerc... | 51 |
"""simple docstring"""
import math
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( self : Any , __a : list[list[float]] , __a : list[int] ) -> int:
_UpperCamelCase : List[Any] = 0.0
... | 51 | 1 |
"""simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase... | 51 |
"""simple docstring"""
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
lowerCamelCase__ = "src/transf... | 51 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :int
SCRE... | 51 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCamelCase__ = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that g... | 51 | 1 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : List[str] , __a : str , __a : List[Any] ) -> Optional[int]:
_UpperCamelCase : Union[str, Any] = name
_UpperCamelCase ... | 51 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 51 | 1 |
"""simple docstring"""
from __future__ import annotations
lowerCamelCase__ = "Muhammad Umer Farooq"
lowerCamelCase__ = "MIT"
lowerCamelCase__ = "1.0.0"
lowerCamelCase__ = "Muhammad Umer Farooq"
lowerCamelCase__ = "contact@muhammadumerfarooq.me"
lowerCamelCase__ = "Alph... | 51 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCamelCase__ = input("Enter image url: ").strip()
print(f"""Downloading image from {url} ...""")
lowerCamelCase__ = BeautifulSoup(requests.get(url).content, "ht... | 51 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Any = ["image_processor", "to... | 51 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
_UpperCamelC... | 51 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
lowerCamelCase__ = logging.get_logger(__n... | 51 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Mask2FormerConfig",
... | 51 | 1 |
"""simple docstring"""
from collections import defaultdict
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : str , __a : List[str] , __a : Tuple ) -> Optional[Any]:
_UpperCamelCase : Optional[Any] = ... | 51 |
"""simple docstring"""
lowerCamelCase__ = "\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/... | 51 | 1 |
"""simple docstring"""
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
... | 51 |
"""simple docstring"""
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_... | 51 | 1 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCamelCase__ = input("Enter image url: ").strip()
print(f"""Downloading image from {url} ...""")
lowerCamelCase__ = BeautifulSoup(requests.get(url).content, "ht... | 51 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
fro... | 51 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ = 1_000_000 ) -> int:
"""simple docstring"""
_UpperCamelCase : int = set(range(3 ,lowercase_ ,2 ) )
primes.add(2 )
for p in range(3 ,lowercase_ ,2 ):
if p not in primes:
... | 51 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.test... | 51 | 1 |
"""simple docstring"""
from collections import deque
def lowercase__ ( lowercase_ ) -> str:
"""simple docstring"""
_UpperCamelCase : Dict = len(lowercase_ )
_UpperCamelCase : str = deque()
_UpperCamelCase : str = ... | 51 |
"""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__ = logging.get_logger(__name__)
lowerCamelCase__ = ... | 51 | 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
from ..auto import CONFIG_MAPPING
lowerCamelCase__ = logging.get_logger(_... | 51 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
lowerCamelCase__ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
lowerCamelCase__ = [ord(letter) for letter in string.asci... | 51 | 1 |
"""simple docstring"""
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase... | 51 |
"""simple docstring"""
def lowercase__ ( lowercase_ ,lowercase_ ) -> None:
"""simple docstring"""
_UpperCamelCase : List[Any] = len(lowercase_ )
print("The following activities are selected:" )
# The first activity is always selected
_U... | 51 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=_UpperCamelCase )
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''s... | 51 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get... | 51 | 1 |
"""simple docstring"""
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowercase__ ( lowercase_ ) -> List[Tuple[int, ...... | 51 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCamelCase )
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
S... | 51 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils... | 51 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> set:
"""simple docstring"""
_UpperCamelCase : Union[str, Any] = set()
# edges = list of graph's edges
_UpperCamelCase : Union[str, Any] = get_edges(lowercase_ )
# Whi... | 51 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
lowerCamelCase__ = logging.get_logger(__name__)
def lowercase__ ( lowercase_ ) -> str:
... | 51 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase__ = {
"configuration_owlvit... | 51 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InformerConf... | 51 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowercase__ ( lowercase_ = 1_000_000 ,lowercase_ = 10 ) -> int:
"""simple docstring"""
_UpperCamelCase : defaultdict = defaultdict(lowercase_ )
for outer_w... | 51 | 1 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Optional[int] , __a : Optional[Any] , __a : str , __a : Optional[int] ) -> Any:
_UpperCamelCase : Tuple = name
... | 51 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("KEY")
lowerCamelCase__ = TypeVar("VAL")
@dataclass(frozen=_UpperCamelCase , slots=_UpperCamelCase )
class __SCR... | 51 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
_UpperCamelCase : Union[str, Any] = [1]
_UpperCamelCase, _UpperCamelCase, _UpperCamelCase : List[str] = 0, 0, 0
_UpperCamelCase : str ... | 51 |
"""simple docstring"""
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Optional[Any] , __a : list[int] ) -> None:
_UpperCamelCase : Tuple = len(__a )
_UpperCamelCase : Dict = [0] * len_arra... | 51 | 1 |
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