code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import Tokenize... | 684 |
import requests
__lowerCAmelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
# fetching a list of articles in json format
_UpperCAmelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()... | 684 | 1 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
__lowerCAmelCase = TypeVar("T")
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
return (position - 1) // 2
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
return (2 * posi... | 684 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Any ):
_UpperCAmelCase ... | 684 | 1 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 1 |
from __future__ import annotations
def __lowerCamelCase ( _lowerCAmelCase = 4 ) -> list[list[int]]:
_UpperCAmelCase = abs(_lowerCAmelCase ) or 4
return [[1 + x + y * row_size for x in range(_lowerCAmelCase )] for y in range(_lowerCAmelCase )]
def __lowerCamelCase ( _lowerCAmel... | 684 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class __SCREAMING_SNAKE_CASE ( lowerc... | 684 |
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
__lowerCAmelCase = {
... | 684 | 1 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
__lowerCAmelCase = Path(__file__).resolve().parents[3] / "src"
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io... | 684 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER... | 684 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diffusers.uti... | 684 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 1 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
__lowerCAmelCase = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"convert": ["exp... | 684 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 1 |
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__lowerCAmelCase = 3
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
print("Generating primitive root of p" )
while True:
_UpperCAmelCase = random.... | 684 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {"v... | 684 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 1 |
from __future__ import annotations
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase = None , _lowerCAmelCase = None ) -> None:
if start is None:
_UpperCAmelCase = 0
if end is None:
_UpperCAmelCase = len(_lowerCAmelCase ) - 1
if sta... | 684 |
# 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... | 684 | 1 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
T... | 684 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 1 |
import re
import string
import numpy as np
import datasets
__lowerCAmelCase = "\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n"
__lowerCAmelCase = "\nArgs:\n pred... | 684 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot... | 684 | 1 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__lowerCAmelCase = logging.getL... | 684 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__lowerCAmelCase = logging.g... | 684 | 1 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase ... | 684 |
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
_UpperCAmelCase = []
_UpperCAmelCase = set({"(", "[", "{"} )
_UpperCAmelCase = set({")", "]", "}"} )
_UpperCAmelCase = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_lowerCAme... | 684 | 1 |
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.modeling_tf_au... | 684 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> tuple[float, float]:
# Check if the input is valid
if not len(_lowerCAmelCase ) == len(_lowerCAmelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if equationa[0] == equationa[1] == equationa[0] == equatio... | 684 | 1 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCREAMING_SNAKE_CASE : Union[str, Any] = """M-CLIP"""
def __init__( self : Optional[int] , __UpperCamelCase : Union[st... | 684 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Optional[Any]:
# In... | 684 | 1 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {name: getattr(transformers, name + "F... | 684 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
... | 684 | 1 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
__lowerCAmelCase = {
# 1536-bit
5: {
"prime": int(
... | 684 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvaila... | 684 | 1 |
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
__lowerCAmelCase = datasets.load_iris()
__lowerCAmelCase = np.array(data["data"])
__lowerCAmelCase = np.array(data["target"])
__l... | 684 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCRE... | 684 | 1 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_ut... | 684 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , __UpperCamelCase : List[Any]=0 ): # a graph with Node 0,1,...,N-1
_UpperCAmelCase = n
_UpperCAmelCase = [
[math.inf for j in range... | 684 | 1 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
_UpperCAmelCase = 0
if start < end:
_UpperCAmelCase = randint(_lowerCAmelCa... | 684 |
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 __SCREAMING... | 684 | 1 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
__lowerCAmelCase = importlib.util.find_spec("s3fs") is not None
if _has_safs:
from .safile... | 684 |
import requests
__lowerCAmelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
# fetching a list of articles in json format
_UpperCAmelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()... | 684 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMS... | 684 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Any ):
_UpperCAmelCase ... | 684 | 1 |
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding
from ... | 684 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 1 |
from __future__ import annotations
class __SCREAMING_SNAKE_CASE :
def __init__( self : str , __UpperCamelCase : int ):
_UpperCAmelCase = order
# a_{0} ... a_{k}
_UpperCAmelCase = [1.0] + [0.0] * order
# b_{0... | 684 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
"caidas/swin2sr-classicalsr-x2-64": (
"https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.... | 684 |
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
__lowerCAmelCase = {
... | 684 | 1 |
import math
from datetime import datetime, timedelta
def __lowerCamelCase ( _lowerCAmelCase ) -> datetime:
_UpperCAmelCase = year % 19
_UpperCAmelCase = year % 4
_UpperCAmelCase = year % 7
_UpperCAmelCase = math.floor(year / 100 )
... | 684 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER... | 684 | 1 |
import logging
from transformers.configuration_utils import PretrainedConfig
__lowerCAmelCase = logging.getLogger(__name__)
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCREAMING_SNAKE_CASE : List[str] = """masked_bert"""
def __init__( self : Tu... | 684 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 1 |
from __future__ import annotations
from typing import Any
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
if not postfix_notation:
return 0
_UpperCAmelCase = {"+", "-", "*", "/"}
_UpperCAmelCase = []
for token in postfix_notation:
if token in o... | 684 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
Rand... | 684 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 1 |
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
__lowerCAmelCase = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
"text-classif... | 684 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
"abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json",
}
clas... | 684 |
# 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... | 684 | 1 |
import re
from filelock import FileLock
try:
import nltk
__lowerCAmelCase = True
except (ImportError, ModuleNotFoundError):
__lowerCAmelCase = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("punkt", quiet=True)
def __... | 684 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 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
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer, TFAutoModelFo... | 684 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot... | 684 | 1 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
return "".join(sorted(_lowerCAmelCase ) )
def __lowerCamelCase ( _lowerCAmelCase ) -> list[str]:
return word_by_signature[signature(_lowerCAm... | 684 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__lowerCAmelCase = logging.g... | 684 | 1 |
from __future__ import annotations
import time
__lowerCAmelCase = list[tuple[int, int]]
__lowerCAmelCase = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1... | 684 |
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
_UpperCAmelCase = []
_UpperCAmelCase = set({"(", "[", "{"} )
_UpperCAmelCase = set({")", "]", "}"} )
_UpperCAmelCase = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_lowerCAme... | 684 | 1 |
import math
from typing import Dict, Iterable, List, Optional, Tuple, 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
from ...image_utils import (
IM... | 684 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> tuple[float, float]:
# Check if the input is valid
if not len(_lowerCAmelCase ) == len(_lowerCAmelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if equationa[0] == equationa[1] == equationa[0] == equatio... | 684 | 1 |
def __lowerCamelCase ( ) -> int:
return 1
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
return 0 if x < 0 else five_pence(x - 5 ) + two_pence(_lowerCAmelCase )
def _... | 684 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Optional[Any]:
# In... | 684 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJK_Unified_Ideograph... | 684 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
... | 684 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = "▁"... | 684 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvaila... | 684 | 1 |
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
__lowerCAmelCase = {
... | 684 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCRE... | 684 | 1 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.m... | 684 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , __UpperCamelCase : List[Any]=0 ): # a graph with Node 0,1,...,N-1
_UpperCAmelCase = n
_UpperCAmelCase = [
[math.inf for j in range... | 684 | 1 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> Any:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase=0 ) -> Union[str, Any]:
return sorted(_lowerCAmelCase , key=lambda _lowerCAmelCa... | 684 |
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 __SCREAMING... | 684 | 1 |
from pathlib import Path
import fire
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> List[str]:
_UpperCAmelCase = Path(_lowerCAmelCase )
_UpperCAmelCase = Path(_lowerCAmelCase )
dest_dir.mkdir(exist_ok=_lowerCAmelCase ... | 684 |
import requests
__lowerCAmelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
# fetching a list of articles in json format
_UpperCAmelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()... | 684 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
"studio-ousia/luke-... | 684 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Any ):
_UpperCAmelCase ... | 684 | 1 |
from collections.abc import Sequence
def __lowerCamelCase ( _lowerCAmelCase = None ) -> int:
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
_UpperCAmelCase = nums[0]
for i in range(1 , len(_lowerCAmelCase ) ):
_UpperCAmelCas... | 684 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 1 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softm... | 684 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCAmelCase = {"configuration_mbart": ["... | 684 |
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
__lowerCAmelCase = {
... | 684 | 1 |
from __future__ import annotations
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
_UpperCAmelCase = len(_lowerCAmelCase ) // 2
# choose the middle 3 elements
_UpperCAmelCase = lst[m - 1 : m + 2]
# if middle element is peak
if three[1] > three[0] and thr... | 684 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER... | 684 | 1 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.... | 684 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 1 |
import numpy as np
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> np.ndarray:
return np.where(vector > 0 , _lowerCAmelCase , (alpha * (np.exp(_lowerCAmelCase ) - 1)) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 684 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 1 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common i... | 684 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 1 |
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
_UpperCAmelCase = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def __lowerCamelCase ( _lowerCAmelCase = 100 ) -> int:
_UpperCAmelCase = 1
_UpperCAmelCase = ... | 684 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 1 |
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
impo... | 684 |
# 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... | 684 | 1 |
from copy import deepcopy
class __SCREAMING_SNAKE_CASE :
def __init__( self : str , __UpperCamelCase : list[int] | None = None , __UpperCamelCase : int | None = None ):
if arr is None and size is not None:
_UpperCAmelCase = ... | 684 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
__lowerCAmelCase = {"configuration_beit": ["BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BeitConfig", "BeitOnnx... | 684 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot... | 684 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Ac... | 684 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__lowerCAmelCase = logging.g... | 684 | 1 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
_UpperCAmelCase , _UpperCAmelCase = analyze_text(_lowerCAmelCase )
_UpperCAmelCase = list(" "... | 684 |
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
_UpperCAmelCase = []
_UpperCAmelCase = set({"(", "[", "{"} )
_UpperCAmelCase = set({")", "]", "}"} )
_UpperCAmelCase = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_lowerCAme... | 684 | 1 |
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
_UpperCAmelCase = hex_num.strip()
if not hex_num:
raise ValueError("No value was passed to the function" )
_UpperCAmelCase = hex_num[0] == "-"
if is_negative:
_UpperCAmelCase = hex_num[1:... | 684 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> tuple[float, float]:
# Check if the input is valid
if not len(_lowerCAmelCase ) == len(_lowerCAmelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if equationa[0] == equationa[1] == equationa[0] == equatio... | 684 | 1 |
import heapq
def __lowerCamelCase ( _lowerCAmelCase ) -> set[int]:
_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 Priority Queue
# heapq works with a min priority que... | 684 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Optional[Any]:
# In... | 684 | 1 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPip... | 684 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
... | 684 | 1 |
from ..utils import DummyObject, requires_backends
class __SCREAMING_SNAKE_CASE ( metaclass=lowercase):
__SCREAMING_SNAKE_CASE : Any = ["""flax"""]
def __init__( self : Optional[Any] , *__UpperCamelCase : List[Any] , **__UpperCamelCase : in... | 684 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvaila... | 684 | 1 |
from ..utils import DummyObject, requires_backends
class __SCREAMING_SNAKE_CASE ( metaclass=lowercase):
__SCREAMING_SNAKE_CASE : Any = ["""torch"""]
def __init__( self : int , *__UpperCamelCase : int , **__UpperCamelCase : Union[str, Any] )... | 684 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCRE... | 684 | 1 |
import string
import numpy
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> int:
return b if a == 0 else greatest_common_divisor(b % a , _lowerCAmelCase )
class __SCREAMING_SNAKE_CASE :
__SCREAMING_SNAKE_CASE : Union[str, Any] = string.ascii_upperc... | 684 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , __UpperCamelCase : List[Any]=0 ): # a graph with Node 0,1,...,N-1
_UpperCAmelCase = n
_UpperCAmelCase = [
[math.inf for j in range... | 684 | 1 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(_lowerCAmelCase , int(b / 2 ) ) * actual_power(_lowerCAmelCase , int(b / 2 ) )
else:
return a * actual_power(_lowerCAmelCase , ... | 684 |
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 __SCREAMING... | 684 | 1 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def __lowerCamelCase ( _lowerCAmelCase ) -> Union[str, Any]: # picklable for multi... | 684 |
import requests
__lowerCAmelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
# fetching a list of articles in json format
_UpperCAmelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()... | 684 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvaila... | 684 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Any ):
_UpperCAmelCase ... | 684 | 1 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def __lowerCamelCase ( _lowerCAmelCase ) -> ... | 684 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 1 |
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCREAMING_SNAKE_C... | 684 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
"YituTech/conv-bert-base"... | 684 |
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
__lowerCAmelCase = {
... | 684 | 1 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER... | 684 | 1 |
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
__lowerCAmelCase = logging.get_logger(__name__) # pylint: disable=invalid-name
def __lowerCamelCa... | 684 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 1 |
import math
import unittest
from transformers import BioGptConfig, 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 imp... | 684 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 1 |
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ) or number < 0:
raise ValueError("Input must be a non-negative integer" )
_UpperCAmelCase = 0
while number:
# This way we arrive at next set bit (next 1) instead... | 684 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 1 |
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
__lowerCAmelCase ... | 684 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 1 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 684 |
# 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... | 684 | 1 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def __lowerCamelCase ( _lowerCAmelCase = "" ) -> dict[str, float]:
_UpperCAmelCase = url or "https://www.imdb.com/chart/top/?ref_=nv_mv_250"
_UpperCAmelCase = BeautifulS... | 684 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 1 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
__lowerCAmelCase = re.compile(r"\b(a|an|the)\b", re.UNICODE)
__lowerCAmelCase = None
def __lowerCamelCase ( ) -> int:
_UpperCAmelCase = ... | 684 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot... | 684 | 1 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsm... | 684 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__lowerCAmelCase = logging.g... | 684 | 1 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
__lowerCAmelCase = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowercase):
def __init__( self : Dict , *__UpperCamelCase : Union[... | 684 |
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
_UpperCAmelCase = []
_UpperCAmelCase = set({"(", "[", "{"} )
_UpperCAmelCase = set({")", "]", "}"} )
_UpperCAmelCase = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_lowerCAme... | 684 | 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
__lowerCAmelCase = "."
if __name__ == "__main__":
__lowerCAmelCase = os.path.join(REPO_PATH, "utils/documentation_test... | 684 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> tuple[float, float]:
# Check if the input is valid
if not len(_lowerCAmelCase ) == len(_lowerCAmelCase ) == 3:
raise ValueError("Please enter a valid equation." )
if equationa[0] == equationa[1] == equationa[0] == equatio... | 684 | 1 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigT... | 684 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Optional[Any]:
# In... | 684 | 1 |
def __lowerCamelCase ( _lowerCAmelCase ) -> str:
_UpperCAmelCase = []
_UpperCAmelCase = set({"(", "[", "{"} )
_UpperCAmelCase = set({")", "]", "}"} )
_UpperCAmelCase = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_lowerCAme... | 684 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
... | 684 | 1 |
from itertools import product
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> list[int]:
_UpperCAmelCase = sides_number
_UpperCAmelCase = max_face_number * dice_number
_UpperCAmelCase = [0] * (max_total + 1)
_UpperCAmelCase ... | 684 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvaila... | 684 | 1 |
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.schedulers.sched... | 684 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCRE... | 684 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCAmelCase = {
"configuration_nllb_moe": [
"NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP",
"NllbMoeConfig",
]
}
try:
if not is_torch_avail... | 684 |
import math
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , __UpperCamelCase : List[Any]=0 ): # a graph with Node 0,1,...,N-1
_UpperCAmelCase = n
_UpperCAmelCase = [
[math.inf for j in range... | 684 | 1 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
for i in range(len(_lowerCAmelCase ) - 1 , 0 , -1 ):
_UpperCAmelCase = False
for j in range(_lowerCAmelCase , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
_UpperCAmelCase , _UpperC... | 684 |
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 __SCREAMING... | 684 | 1 |
import inspect
import unittest
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Optional[int] ):
try:
import diffusers # noqa: F401
except ImportError:
assert False
def UpperCAmelCas... | 684 |
import requests
__lowerCAmelCase = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __lowerCamelCase ( _lowerCAmelCase ) -> None:
# fetching a list of articles in json format
_UpperCAmelCase = requests.get(_NEWS_API + bbc_news_api_key ).json()... | 684 | 1 |
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
__lowerCAmelCas... | 684 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __SCREAMING_SNAKE_CASE ( unittest.TestCase):
def UpperCAmelCase__ ( self : Any ):
_UpperCAmelCase ... | 684 | 1 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
__lowerCAmelCase = (3, 9, -1_1, 0, 7, 5, 1, -1)
__lowerCAmelCase = (4, 6, 2, 0, 8, 1_0, 3, -2)
@dataclass
class __SCREAMING_SNAKE_CASE :
__SCREAM... | 684 |
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> tuple:
_UpperCAmelCase = namedtuple("result" , "name value" )
if (voltage, current, power).count(0 ) != 1:
... | 684 | 1 |
__lowerCAmelCase = 9.8_06_65
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase = g ) -> float:
if fluid_density <= 0:
raise ValueError("Impossible fluid density" )
if volume < 0:
raise ValueError("Impossible Object volume" )
if gravi... | 684 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = {}
_UpperCAmelCase = job["started_at"]
_UpperCAmelCase = job["completed_at"]... | 684 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__lowerCAmelCase = {"processing_layoutxlm": ["LayoutXLMProcessor"... | 684 |
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
__lowerCAmelCase = {
... | 684 | 1 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
__lowerCAmelCase = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( lowercase):
def __init__( self : Tuple , *__UpperCamelCase ... | 684 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER... | 684 | 1 |
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = []
for i in range(len(_lowerCAmelCase ) - pat_len + 1 ):
_UpperCAmelCase = True
for j in range(_lowerCAmelCas... | 684 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowerCAmelCase ) -> List[str]:
return getitem, k
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
return setitem, ... | 684 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
"Intel/dpt-large": "https://huggingface.co/Intel/dpt-large/resolve/main/config.j... | 684 |
def __lowerCamelCase ( _lowerCAmelCase ) -> list:
_UpperCAmelCase = len(_lowerCAmelCase )
for i in range(1 , _lowerCAmelCase ):
_UpperCAmelCase = collection[i]
_UpperCAmelCase = 0
_UpperCAmelCase = i - 1
while l... | 684 | 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... | 684 |
__lowerCAmelCase = 2_5_6
# Modulus to hash a string
__lowerCAmelCase = 1_0_0_0_0_0_3
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> bool:
_UpperCAmelCase = len(_lowerCAmelCase )
_UpperCAmelCase = len(_lowerCAmelCase )
... | 684 | 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... | 684 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.uti... | 684 | 1 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def __lowerCamelCase ( _lowerCAmelCase ) -> Any:
_UpperCAmelCase = [
"decoder.version",
"decoder.output_projection.weight",
... | 684 |
# 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... | 684 | 1 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
__lowerCAmelCase = version.parse(version.... | 684 |
from itertools import permutations
def __lowerCamelCase ( _lowerCAmelCase ) -> bool:
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
_UpperCAmelCase = [7, 11, 13, 17]
for i, test in ... | 684 | 1 |
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