code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> Optional[Any]:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def _lowercase ( __snake_case ,__snake_case=0 ) -> Optional[int]:
return sorte... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> list:
__lowerCAmelCase : List[str] = len(__snake_case )
__lowerCAmelCase : Dict = []
for i in range(len(__snake_case ) - pat_len + 1 ):
__lowerCAmelCase ... | 615 | 1 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
... | 615 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
__snake_case : Any = True
except (ImportError, ModuleNotFoundError):
__snake_case : Optional[int] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.... | 615 | 1 |
"""simple docstring"""
import sys
__snake_case : List[Any] = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'1254069874715852386305071569329096329... | 615 |
"""simple docstring"""
import string
from math import logaa
def _lowercase ( __snake_case ,__snake_case ) -> int:
__lowerCAmelCase : int = document.translate(
str.maketrans("" ,"" ,string.punctuation ) ).replace("\n" ,"" )
... | 615 | 1 |
"""simple docstring"""
import string
from math import logaa
def _lowercase ( __snake_case ,__snake_case ) -> int:
__lowerCAmelCase : int = document.translate(
str.maketrans("" ,"" ,string.punctuation ) ).replace("\n" ,"" )
... | 615 |
"""simple docstring"""
import math
def _lowercase ( __snake_case ,__snake_case ) -> float:
return math.pow(__snake_case ,2 ) - a
def _lowercase ( __snake_case ) -> float:
return 2 * x
def _lowercase ( __sn... | 615 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers impo... | 615 |
"""simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _lowercase ( __snake_case ,__snake_case ,__snake_case ) -> T... | 615 | 1 |
"""simple docstring"""
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__snake_case : str = '%20'.join(argv[1:]) if len(argv) > 1... | 615 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMSch... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case ) -> str:
if isinstance(__snake_case ,__snake_case ):
raise TypeError("'float' object cannot be interpreted as an integer" )
if isinstance(__snake_case ,__snake_case ):
raise TypeError... | 615 |
"""simple docstring"""
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class A__ :
'''simple docstrin... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case ) -> float:
__lowerCAmelCase : List[str] = 0
while len(__snake_case ) > 1:
__lowerCAmelCase : Optional[Any] = 0
# Consider two files with minimum cost to be merged
for _ in ... | 615 |
"""simple docstring"""
import torch
from torch import nn
class A__ ( nn.Module ):
'''simple docstring'''
def __init__( self: Optional[Any] , _SCREAMING_SNAKE_CASE: List[Any] , _SCREAMING_SNAKE_CASE: str , _SCREAMING_SNAKE_CASE: List[str] , ... | 615 | 1 |
"""simple docstring"""
from __future__ import annotations
__snake_case : List[str] = list[tuple[int, int]]
__snake_case : List[str] = [
[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, ... | 615 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtraction... | 615 | 1 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 615 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def _lowercase ( __snake_case ) -> Tuple:
__lowerCAmelCase : Dict = [
"decoder.versio... | 615 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attent... | 615 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__snake_case : str = pytest.mark.integrat... | 615 | 1 |
"""simple docstring"""
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__snake_case : Any = {
'facebook/mask2former-swin-small-coco-instance': (
... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case = 3 ,__snake_case = 7 ,__snake_case = 1_000_000 ) -> int:
__lowerCAmelCase : Optional[Any] = 0
__lowerCAmelCase : List[str] = 1
for current_denominator in range(1 ,limit + 1 ... | 615 | 1 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__snake_case : Tuple = '\\n\n'
__snake_case : Optional[int]... | 615 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['torch', 'scipy']
def __init__( self: Tuple , *_SCREAMING_SNAKE_C... | 615 | 1 |
"""simple docstring"""
from ....utils import logging
__snake_case : List[Any] = logging.get_logger(__name__)
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self: Optional[int] , _SCREAMING_SNAKE_CAS... | 615 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__snake_case : ... | 615 | 1 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowercase ( ) -> str:
__lowerCAmelCase : Dict = ArgumentParser(
... | 615 |
"""simple docstring"""
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoMod... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case = 100 ) -> int:
__lowerCAmelCase : Union[str, Any] = 0
__lowerCAmelCase : Dict = 0
for i in range(1 ,n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_int... | 615 |
"""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,
... | 615 | 1 |
"""simple docstring"""
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
fro... | 615 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case : Tuple = logging.getLogger(__name__)
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE... | 615 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__snake_case : List[str] = {
'configuration_layoutlm... | 615 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__snake_case : Tuple = logging.get_logger(__name__)
def _lowerc... | 615 | 1 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def _lowercase ( __snake_case ) -> int:
# This defines a "chinese character" as anything in the ... | 615 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@staticmethod
@abstractmethod
def _SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CAS... | 615 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( __SCREAMING_SNAKE_CASE , unittest.TestCase ... | 615 |
"""simple docstring"""
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
... | 615 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class A__ ( __SCREAMING... | 615 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class A__ ( unittest.TestCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self: Optional[int]) -> List[Any]:
"""simple docstring"""
... | 615 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowercase ( __snake_case ,__snake_case ,__snake_case ) -> int | float:
if len(__snake_case ) == 0:
raise ValueError("find_max() arg is an empty sequence" )
if (
left >= len... | 615 |
"""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_ba... | 615 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case : str = {
'configuration_groupvit': [
'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> list:
__lowerCAmelCase : List[str] = len(__snake_case )
__lowerCAmelCase : Dict = []
for i in range(len(__snake_case ) - pat_len + 1 ):
__lowerCAmelCase ... | 615 | 1 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/lic... | 615 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
__snake_case : Any = True
except (ImportError, ModuleNotFoundError):
__snake_case : Optional[int] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.... | 615 | 1 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: t... | 615 |
"""simple docstring"""
import string
from math import logaa
def _lowercase ( __snake_case ,__snake_case ) -> int:
__lowerCAmelCase : int = document.translate(
str.maketrans("" ,"" ,string.punctuation ) ).replace("\n" ,"" )
... | 615 | 1 |
"""simple docstring"""
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 DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, Vi... | 615 |
"""simple docstring"""
import math
def _lowercase ( __snake_case ,__snake_case ) -> float:
return math.pow(__snake_case ,2 ) - a
def _lowercase ( __snake_case ) -> float:
return 2 * x
def _lowercase ( __sn... | 615 | 1 |
"""simple docstring"""
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
__snake_case : U... | 615 |
"""simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _lowercase ( __snake_case ,__snake_case ,__snake_case ) -> T... | 615 | 1 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
__snake_case : Optional[Any] = datasets.utils.logging.ge... | 615 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMSch... | 615 | 1 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, i... | 615 |
"""simple docstring"""
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class A__ :
'''simple docstrin... | 615 | 1 |
"""simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class A__ :
'''simple docstring'''
def __init__( self: Optional[Any] , _SCREAMING_SNAKE_CASE: List[str] , _SCREAMING_SNAKE_CASE: Dict , _SCREAMING_SNAKE_CA... | 615 |
"""simple docstring"""
import torch
from torch import nn
class A__ ( nn.Module ):
'''simple docstring'''
def __init__( self: Optional[Any] , _SCREAMING_SNAKE_CASE: List[Any] , _SCREAMING_SNAKE_CASE: str , _SCREAMING_SNAKE_CASE: List[str] , ... | 615 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__snake_case : Dict = {
'configuration_vision_encoder_decoder'... | 615 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtraction... | 615 | 1 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.... | 615 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def _lowercase ( __snake_case ) -> Tuple:
__lowerCAmelCase : Dict = [
"decoder.versio... | 615 | 1 |
"""simple docstring"""
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
__snake_case : Optional[int] ... | 615 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__snake_case : str = pytest.mark.integrat... | 615 | 1 |
"""simple docstring"""
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoder... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case = 3 ,__snake_case = 7 ,__snake_case = 1_000_000 ) -> int:
__lowerCAmelCase : Optional[Any] = 0
__lowerCAmelCase : List[str] = 1
for current_denominator in range(1 ,limit + 1 ... | 615 | 1 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtraction... | 615 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['torch', 'scipy']
def __init__( self: Tuple , *_SCREAMING_SNAKE_C... | 615 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
__snake_case : Union[str, Any] = ... | 615 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__snake_case : ... | 615 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def _lowercase ( __snake_case ) -> None:
create_state_space_tree(__snake_case ,[] ,0 )
def _lowercase ( __snake_case ,__snake_case ,__snake_ca... | 615 |
"""simple docstring"""
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoMod... | 615 | 1 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def _lowercase ( __snake_case = "https://www.worldometers.info/coronavirus" ) -> dict:
__lowerCAmelCase : str = BeautifulSoup(requests.get(__snake_case ).text ,"html.parser" )
... | 615 |
"""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,
... | 615 | 1 |
"""simple docstring"""
from collections import deque
from .hash_table import HashTable
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self: Union[str, Any] , *_SCREAMING_SNAKE_CASE: str , **_SCREAMING_SNAKE_CASE: ... | 615 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case : Tuple = logging.getLogger(__name__)
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case = 3 ,__snake_case = 7 ,__snake_case = 1_000_000 ) -> int:
__lowerCAmelCase : Optional[Any] = 0
__lowerCAmelCase : List[str] = 1
for current_denominator in range(1 ,limit + 1 ... | 615 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__snake_case : Tuple = logging.get_logger(__name__)
def _lowerc... | 615 | 1 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__snake_case : Tuple = logging.get_logger('transformers.models.speecht5')
def _lowercase... | 615 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@staticmethod
@abstractmethod
def _SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CAS... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case ) -> int:
__lowerCAmelCase : Optional[Any] = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def _lowercase ( __snake_case = 100 ) -> int:
... | 615 |
"""simple docstring"""
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
... | 615 | 1 |
"""simple docstring"""
import unittest
from transformers import 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,
)
from ... | 615 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class A__ ( unittest.TestCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self: Optional[int]) -> List[Any]:
"""simple docstring"""
... | 615 | 1 |
"""simple docstring"""
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 615 |
"""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_ba... | 615 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import req... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> list:
__lowerCAmelCase : List[str] = len(__snake_case )
__lowerCAmelCase : Dict = []
for i in range(len(__snake_case ) - pat_len + 1 ):
__lowerCAmelCase ... | 615 | 1 |
"""simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _lowercase ( __snake_case ,__snake_case ,__snake_case ) -> T... | 615 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
__snake_case : Any = True
except (ImportError, ModuleNotFoundError):
__snake_case : Optional[int] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.... | 615 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_con... | 615 |
"""simple docstring"""
import string
from math import logaa
def _lowercase ( __snake_case ,__snake_case ) -> int:
__lowerCAmelCase : int = document.translate(
str.maketrans("" ,"" ,string.punctuation ) ).replace("\n" ,"" )
... | 615 | 1 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__snake... | 615 |
"""simple docstring"""
import math
def _lowercase ( __snake_case ,__snake_case ) -> float:
return math.pow(__snake_case ,2 ) - a
def _lowercase ( __snake_case ) -> float:
return 2 * x
def _lowercase ( __sn... | 615 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Dict = logging.get_logger(__name__)
__snake_case : List[Any] = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
clas... | 615 |
"""simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _lowercase ( __snake_case ,__snake_case ,__snake_case ) -> T... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> Any:
__lowerCAmelCase : List[Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def _lowercase ( __snake_ca... | 615 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMSch... | 615 | 1 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
__snake_case : Tuple = TypeVar('KEY')
__snake_case : Dict = TypeVar('VAL')
@dataclass(frozen=__SCREAMING_SNA... | 615 |
"""simple docstring"""
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class A__ :
'''simple docstrin... | 615 | 1 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def _lowercase ( __snake_case ,__snake_case ,__snake_case = None ) -> str:
if version.parse(hfh.__version__ )... | 615 |
"""simple docstring"""
import torch
from torch import nn
class A__ ( nn.Module ):
'''simple docstring'''
def __init__( self: Optional[Any] , _SCREAMING_SNAKE_CASE: List[Any] , _SCREAMING_SNAKE_CASE: str , _SCREAMING_SNAKE_CASE: List[str] , ... | 615 | 1 |
"""simple docstring"""
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
__snake_case : int = Mapping[str, np.ndarray]
__snake_case : ... | 615 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtraction... | 615 | 1 |
"""simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__snake_case : Tuple = logging.get_logger(__name__) # pylint: disable... | 615 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def _lowercase ( __snake_case ) -> Tuple:
__lowerCAmelCase : Dict = [
"decoder.versio... | 615 | 1 |
"""simple docstring"""
import datasets
__snake_case : Dict = '\\n@InProceedings{conneau2018xnli,\n author = "Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.... | 615 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__snake_case : str = pytest.mark.integrat... | 615 | 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 Mask... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case = 3 ,__snake_case = 7 ,__snake_case = 1_000_000 ) -> int:
__lowerCAmelCase : Optional[Any] = 0
__lowerCAmelCase : List[str] = 1
for current_denominator in range(1 ,limit + 1 ... | 615 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowercase ( __snake_case ) -> float:
__lowerCAmelCase : Optional[int] = 0.00
__lowerCAmelCase : List[Any] = 0
for resistor in resistors:
if resistor <= 0:
__low... | 615 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['torch', 'scipy']
def __init__( self: Tuple , *_SCREAMING_SNAKE_C... | 615 | 1 |
"""simple docstring"""
from __future__ import annotations
__snake_case : str = list[list[int]]
# assigning initial values to the grid
__snake_case : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1]... | 615 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__snake_case : ... | 615 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _lowercase ( __snake_case ,__... | 615 |
"""simple docstring"""
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoMod... | 615 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : int = {
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MA... | 615 |
"""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,
... | 615 | 1 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHE... | 615 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case : Tuple = logging.getLogger(__name__)
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE... | 615 | 1 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInp... | 615 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__snake_case : Tuple = logging.get_logger(__name__)
def _lowerc... | 615 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class A__ :
'''simple docstring'''
def __init__( self: Optional[int] , _SCREAMING_SNAKE_CASE: list[str]) -> Dict:
"""simple docstring"""
__lowerCAm... | 615 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@staticmethod
@abstractmethod
def _SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CAS... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case = 4_000_000 ) -> int:
__lowerCAmelCase : Any = []
__lowerCAmelCase , __lowerCAmelCase : Optional[Any] = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(__snake_case )
... | 615 |
"""simple docstring"""
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
... | 615 | 1 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def _lowercase ( __snake_case ,__snake_case ) -> str:
__lowerCAmelCase : Dict = BeautifulSoup(requests.get(__snake_case ,params=__snake_case ).content ,"html.parser" )
... | 615 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class A__ ( unittest.TestCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self: Optional[int]) -> List[Any]:
"""simple docstring"""
... | 615 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__snake_case : int = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except Optio... | 615 |
"""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_ba... | 615 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extract... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> list:
__lowerCAmelCase : List[str] = len(__snake_case )
__lowerCAmelCase : Dict = []
for i in range(len(__snake_case ) - pat_len + 1 ):
__lowerCAmelCase ... | 615 | 1 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenizat... | 615 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
__snake_case : Any = True
except (ImportError, ModuleNotFoundError):
__snake_case : Optional[int] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.... | 615 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : Union[str, Any] = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Bio... | 615 |
"""simple docstring"""
import string
from math import logaa
def _lowercase ( __snake_case ,__snake_case ) -> int:
__lowerCAmelCase : int = document.translate(
str.maketrans("" ,"" ,string.punctuation ) ).replace("\n" ,"" )
... | 615 | 1 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case : int = None
try:
import msvcrt
except ImportError:
__snake_case : Tuple = None
try:
import fcntl
except Impo... | 615 |
"""simple docstring"""
import math
def _lowercase ( __snake_case ,__snake_case ) -> float:
return math.pow(__snake_case ,2 ) - a
def _lowercase ( __snake_case ) -> float:
return 2 * x
def _lowercase ( __sn... | 615 | 1 |
"""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_ba... | 615 |
"""simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _lowercase ( __snake_case ,__snake_case ,__snake_case ) -> T... | 615 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
__snake_case : List[Any] = {
'configuration_speecht5': [
'SPEECHT5... | 615 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMSch... | 615 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['torch', 'scipy']
def __init__( self: Tuple , *_SCREAMING_SNAKE_C... | 615 |
"""simple docstring"""
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class A__ :
'''simple docstrin... | 615 | 1 |
"""simple docstring"""
import requests
__snake_case : List[str] = 'https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='
def _lowercase ( __snake_case ) -> None:
# fetching a list of articles in json format
__lowerCAmelCase : ... | 615 |
"""simple docstring"""
import torch
from torch import nn
class A__ ( nn.Module ):
'''simple docstring'''
def __init__( self: Optional[Any] , _SCREAMING_SNAKE_CASE: List[Any] , _SCREAMING_SNAKE_CASE: str , _SCREAMING_SNAKE_CASE: List[str] , ... | 615 | 1 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 615 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtraction... | 615 | 1 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowercase ( ) -> int:
__lowerCAmelCase : Union[str, Any] = ArgumentPar... | 615 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def _lowercase ( __snake_case ) -> Tuple:
__lowerCAmelCase : Dict = [
"decoder.versio... | 615 | 1 |
"""simple docstring"""
import argparse
import os
# New Code #
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_schedul... | 615 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__snake_case : str = pytest.mark.integrat... | 615 | 1 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
__snake_case : int = logging.get_logger(__name__)
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( sel... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case = 3 ,__snake_case = 7 ,__snake_case = 1_000_000 ) -> int:
__lowerCAmelCase : Optional[Any] = 0
__lowerCAmelCase : List[str] = 1
for current_denominator in range(1 ,limit + 1 ... | 615 | 1 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
__snake_case : Any = True
except (ImportError, ModuleNotFoundError):
__snake_case : Optional[int] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.... | 615 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = ['torch', 'scipy']
def __init__( self: Tuple , *_SCREAMING_SNAKE_C... | 615 | 1 |
"""simple docstring"""
from scipy.stats import pearsonr
import datasets
__snake_case : Dict = '\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculati... | 615 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__snake_case : ... | 615 | 1 |
"""simple docstring"""
import argparse
import json
from tqdm import tqdm
def _lowercase ( ) -> List[str]:
__lowerCAmelCase : Any = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" ,type=__snake_case ... | 615 |
"""simple docstring"""
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoMod... | 615 | 1 |
"""simple docstring"""
import math
def _lowercase ( __snake_case ,__snake_case ) -> float:
return math.pow(__snake_case ,2 ) - a
def _lowercase ( __snake_case ) -> float:
return 2 * x
def _lowercase ( __sn... | 615 |
"""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,
... | 615 | 1 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, r... | 615 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case : Tuple = logging.getLogger(__name__)
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
SCREAMING_SNAKE... | 615 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def _lowercase ( __snake_case ... | 615 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__snake_case : Tuple = logging.get_logger(__name__)
def _lowerc... | 615 | 1 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVis... | 615 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@staticmethod
@abstractmethod
def _SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CAS... | 615 | 1 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from ... | 615 |
"""simple docstring"""
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
... | 615 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMSch... | 615 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class A__ ( unittest.TestCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self: Optional[int]) -> List[Any]:
"""simple docstring"""
... | 615 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Dict = logging.get_logger(__name__)
__snake_case : Dict = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingfac... | 615 |
"""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_ba... | 615 | 1 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> list:
__lowerCAmelCase : List[str] = len(__snake_case )
__lowerCAmelCase : Dict = []
for i in range(len(__snake_case ) - pat_len + 1 ):
__lowerCAmelCase ... | 615 | 1 |
"""simple docstring"""
import torch
from torch import nn
class A__ ( nn.Module ):
'''simple docstring'''
def __init__( self: Optional[Any] , _SCREAMING_SNAKE_CASE: List[Any] , _SCREAMING_SNAKE_CASE: str , _SCREAMING_SNAKE_CASE: List[str] , ... | 615 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
__snake_case : Any = True
except (ImportError, ModuleNotFoundError):
__snake_case : Optional[int] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.... | 615 | 1 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import Seq... | 615 |
"""simple docstring"""
import string
from math import logaa
def _lowercase ( __snake_case ,__snake_case ) -> int:
__lowerCAmelCase : int = document.translate(
str.maketrans("" ,"" ,string.punctuation ) ).replace("\n" ,"" )
... | 615 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils impor... | 615 |
"""simple docstring"""
import math
def _lowercase ( __snake_case ,__snake_case ) -> float:
return math.pow(__snake_case ,2 ) - a
def _lowercase ( __snake_case ) -> float:
return 2 * x
def _lowercase ( __sn... | 615 | 1 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
__snake_case : Tuple = '\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhe... | 615 |
"""simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _lowercase ( __snake_case ,__snake_case ,__snake_case ) -> T... | 615 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@staticmethod
@abstractmethod
def _SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CAS... | 615 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMSch... | 615 | 1 |
"""simple docstring"""
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError('To use the rich extension, install rich with `pip install rich`') | 615 |
"""simple docstring"""
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class A__ :
'''simple docstrin... | 615 | 1 |
"""simple docstring"""
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
__snake_case : Optional[Any] = datasets.logging.get_logger(__name__)
__snake_cas... | 615 |
"""simple docstring"""
import torch
from torch import nn
class A__ ( nn.Module ):
'''simple docstring'''
def __init__( self: Optional[Any] , _SCREAMING_SNAKE_CASE: List[Any] , _SCREAMING_SNAKE_CASE: str , _SCREAMING_SNAKE_CASE: List[str] , ... | 615 | 1 |
"""simple docstring"""
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExamp... | 615 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtraction... | 615 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case ) -> list:
if len(__snake_case ) <= 1:
return lst
__lowerCAmelCase : Tuple = 1
while i < len(__snake_case ):
if lst[i - 1] <= lst[i]:
i += 1
else:
__lowe... | 615 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def _lowercase ( __snake_case ) -> Tuple:
__lowerCAmelCase : Dict = [
"decoder.versio... | 615 | 1 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__snake_case : Optional[Any] = 'examples/'
__snake_case : str = {
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERS... | 615 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__snake_case : str = pytest.mark.integrat... | 615 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transfor... | 615 |
"""simple docstring"""
def _lowercase ( __snake_case = 3 ,__snake_case = 7 ,__snake_case = 1_000_000 ) -> int:
__lowerCAmelCase : Optional[Any] = 0
__lowerCAmelCase : List[str] = 1
for current_denominator in range(1 ,limit + 1 ... | 615 | 1 |
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