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 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
SCREAMING_SNAKE_CASE__ : Tuple = {
"... | 0 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 0 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
__snake... | 1 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 0 |
from __future__ import annotations
from functools import lru_cache
from math import ceil
UpperCAmelCase_ = 1_0_0
UpperCAmelCase_ = set(range(3, NUM_PRIMES, 2))
primes.add(2)
UpperCAmelCase_ = 42
for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
if prime not in primes:
... | 2 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 0 |
'''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 import BatchFeature
fr... | 3 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 0 |
"""simple docstring"""
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _SCREAMING_SNAKE_CASE ():
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
... | 4 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 0 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
_lowercase = """examples/"""
_lowercase = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.comp... | 5 |
"""simple docstring"""
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.mo... | 682 | 0 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 6 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 0 |
"""simple docstring"""
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_co... | 7 |
"""simple docstring"""
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_... | 682 | 0 |
'''simple docstring'''
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class SCREAMING_SNAKE_CASE (un... | 8 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def A ( __UpperCamelCase ) -> List[str]:
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/... | 9 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 0 |
_lowerCAmelCase = {
"a": "AAAAA",
"b": "AAAAB",
"c": "AAABA",
"d": "AAABB",
"e": "AABAA",
"f": "AABAB",
"g": "AABBA",
"h": "AABBB",
"i": "ABAAA",
"j": "BBBAA",
"k": "ABAAB",
"l": "ABABA",
"m": "ABABB",
"n": "ABBAA",
"o": "ABBAB",
"p": "ABBBA",
"... | 10 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
class __A ( A ):
'''simple docstring'''
__lowerCamelCase : Optional[int] = 'timm_backbone'
def __init__(self ... | 11 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a__ : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization_... | 682 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase__ : Optional[Any] = {
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json""... | 12 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''xlm-... | 682 | 0 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_gra... | 13 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
... | 682 | 0 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDataset... | 14 |
"""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_schedule_with_warmup, set_s... | 682 | 0 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
A : Tuple = logging.getLogger(__name__)
class A ( UpperCAmelCase__ ):
'''simple do... | 15 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 682 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A : List[Any] = {
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitProcessor'],
}
try:
if ... | 16 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
... | 682 | 0 |
import math
class lowerCamelCase_ :
def __init__( self : Union[str, Any] , __A : List[str]=0 ): # a graph with Node 0,1,...,N-1
__A : List[str] = n
__A : List[str] = [
[math.inf for j in range(0 , __A )] for i in ran... | 17 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = r'''
... | 682 | 0 |
'''simple docstring'''
import functools
def __a(SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : str ):
'''simple docstring'''
_lowerCAmelCase = len(SCREAMING_SNAKE_CASE_ )
_lowerCAmelCase = len(SCREAMING_SNAKE_CASE_ )
... | 18 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.te... | 682 | 0 |
"""simple docstring"""
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_a = HfApi()
_a = {}
# fmt: off
_a = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
1.2342... | 19 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivi... | 682 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase: Union[str, Any] = {
'configuration_roformer': ['ROFORMER_PRETRAINED_... | 20 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = np.max(lowerCAmelCase_ , axis=-1 , keepdims=lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = ... | 682 | 0 |
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Conf... | 21 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_C... | 682 | 0 |
'''simple docstring'''
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def snake_case_ (UpperCamelCase : List[str] , UpperCamelCase : str , UpperCamelCase : int , UpperCamelCase : Optional[int]=5 ):
'''sim... | 22 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 0 |
def _snake_case (__lowercase):
UpperCamelCase_ = int(__lowercase)
if n_element < 1:
UpperCamelCase_ = ValueError('a should be a positive number')
raise my_error
UpperCamelCase_ = [1]
UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ =... | 23 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 0 |
'''simple docstring'''
def _UpperCamelCase (_lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : float )-> float:
'''simple docstring'''
return round(float(moles / volume ) * nfactor )
def _UpperCamelCase (_lowerCamelC... | 24 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 0 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class _UpperCamelCase ( unittest.TestCase ):
'''simple docstring'''
def __UpperCamelCase ( self : Dict ) -> Tuple... | 25 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 0 |
'''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def _a ( _lowerCamelCase ) -> str:
"""simple docstring"""
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("""Unde... | 26 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 0 |
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be c... | 27 |
"""simple docstring"""
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.mo... | 682 | 0 |
'''simple docstring'''
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
... | 28 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 0 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
A_ = """\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: improved evaluation ... | 29 |
"""simple docstring"""
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_... | 682 | 0 |
def lowerCamelCase__ ( _lowercase , _lowercase , _lowercase ):
'''simple docstring'''
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(_lowercase ) )
def lowerCamelCase__ ( _lowercase , _lowercase , _lo... | 30 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 0 |
import math
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> str:
SCREAMING_SNAKE_CASE_ = 0
SCREAMING_SNAKE_CASE_ = 0
while num > 0:
SCREAMING_SNAKE_CASE_ = num % 8
SCREAMING_SNAKE_CASE_ = octal + (remainde... | 31 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 0 |
import unittest
from transformers import BertGenerationConfig, 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 ModelTes... | 32 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __magic_name__ (unittest.TestCase ):
'... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a__ : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization_... | 682 | 0 |
"""simple docstring"""
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class snake_case_ :
"""simple docstring"""
A_ = None
def UpperCAmelCase__ ( self) -> Optional[Any]:
UpperC... | 34 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''xlm-... | 682 | 0 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 35 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
... | 682 | 0 |
def lowercase ( __A : int = 200_0000 ) -> int:
'''simple docstring'''
snake_case : List[str] = [0 for i in range(n + 1 )]
snake_case : Optional[Any] = 1
snake_case : Tuple = 1
for i in range(2 , int(n**0.5 ) + 1 ):
... | 36 |
"""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_schedule_with_warmup, set_s... | 682 | 0 |
from math import asin, atan, cos, radians, sin, sqrt, tan
UpperCamelCase : List[Any] = 637_8137.0
UpperCamelCase : Tuple = 635_6752.31_4245
UpperCamelCase : Optional[Any] = 637_8137
def UpperCamelCase_ ( __a , __a , __a , __a )... | 37 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 682 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
A_ : Dict = logging.get_logger(__name__)
class __snake_case ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self , *_... | 38 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
... | 682 | 0 |
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = False ):
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n % 10 not in (1, 3, 7, 9): # can quickly check last digit
return False
i... | 39 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = r'''
... | 682 | 0 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is... | 40 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.te... | 682 | 0 |
'''simple docstring'''
def _A ( A__ , A__ ):
"""simple docstring"""
__lowercase = [1]
for i in range(2 , A__ ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k out of bounds"
__lowercase = []
__lowercase = l... | 41 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivi... | 682 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclas... | 42 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = np.max(lowerCAmelCase_ , axis=-1 , keepdims=lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = ... | 682 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 43 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_C... | 682 | 0 |
'''simple docstring'''
import math
from datetime import datetime, timedelta
def A_ ( _lowerCAmelCase : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = year % 19
_lowerCamelCase : Dict = year % 4
_lowerCamelCase : str ... | 44 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 0 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def A ( lowercase__ : np.ndarray ) -> np.ndarray:
return input_array.reshape((input_array.size, 1) )
def A ( lowercase__ : np.ndarray , ... | 45 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 0 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase : List[str] = loggin... | 46 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 0 |
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql im... | 47 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 0 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTokeniz... | 48 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 0 |
"""simple docstring"""
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transfo... | 49 |
"""simple docstring"""
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.mo... | 682 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCamelCase__ ... | 50 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 0 |
'''simple docstring'''
import argparse
import collections
import json
from pathlib import Path
import requests
import torch
import yaml
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTImageProcessor,
MobileViTVaConfig,
MobileViTVaForImageClassi... | 51 |
"""simple docstring"""
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_... | 682 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_t... | 52 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 0 |
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_softmax
if i... | 53 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 0 |
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,
... | 54 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 | 0 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
requir... | 55 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a__ : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization_... | 682 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImage... | 56 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''xlm-... | 682 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : Optional[Any] = logging.get_logger(__name__)
A_ : Optional[Any] = ... | 57 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
... | 682 | 0 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def __lowerCAmelCase ( __UpperCamelCase : int = 1_0_0_0_0_0_0 , __UpperCamelCase : int = 1_0 ):
'''simple docstring'''
snake_case_ : defaultdict... | 58 |
"""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_schedule_with_warmup, set_s... | 682 | 0 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow_... | 59 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 682 | 0 |
lowerCAmelCase_ = '''0.21.0'''
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batche... | 60 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
... | 682 | 0 |
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_attention_mask
if is_flax_available... | 61 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = r'''
... | 682 | 0 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import _... | 62 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.te... | 682 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET... | 63 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivi... | 682 | 0 |
def A__ ( snake_case_ : int ):
if not isinstance(snake_case_ , snake_case_ ):
raise TypeError('''Input value must be an \'int\' type''' )
SCREAMING_SNAKE_CASE__: Tuple= 0
while number:
position += 1
number >>= 1
return position
if __name__ == "__main__":
import doct... | 64 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = np.max(lowerCAmelCase_ , axis=-1 , keepdims=lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = ... | 682 | 0 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
__UpperCAmelCase = 'us-east-1' # defaults region
@dataclass
class __lowercase :
snake_case_ = 42
snake_case_ = """arn:aws:iam::558105141721:role/sagemaker... | 65 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_C... | 682 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
"https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-med... | 66 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 0 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass... | 67 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import TensorT... | 68 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 0 |
'''simple docstring'''
import math
def __UpperCAmelCase ( _UpperCAmelCase : int ) -> list:
__snake_case = [True] * n
__snake_case = False
__snake_case = False
__snake_case = True
for i in range(3 , int(n**0.5 + 1 ) , 2 ):
_... | 69 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 0 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprec... | 70 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowerCamelCase = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""tokenization_c... | 71 |
"""simple docstring"""
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.mo... | 682 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
... | 72 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 0 |
from __future__ import annotations
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
SCREAMING_SNAKE_CASE = []
SCREAMING_SNAKE_CASE = []
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = sum(_UpperCAmelCase)
create_state_space_tree(_Upp... | 73 |
"""simple docstring"""
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_... | 682 | 0 |
import math
def a__ ( snake_case ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Any = []
__SCREAMING_SNAKE_CASE : List[str] = 2
__SCREAMING_SNAKE_CASE : Dict = int(math.sqrt(snake_case ) ) # Size of every segment
__SCREAMING_SNAKE_C... | 74 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelC... | 75 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 76 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 | 0 |
"""simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,... | 77 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a__ : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization_... | 682 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int ) -> None:
'''simple docstring'''
UpperCAmelCase_ = generate_pascal_triangle(snake_case_ )
for row_idx in range(snake_case_ ):
# Print left spaces
for _ in range(n... | 78 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''xlm-... | 682 | 0 |
from math import factorial
def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase ) -> int:
'''simple docstring'''
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not ... | 79 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
... | 682 | 0 |
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
__UpperCamelCase : List[Any] = False
try:
__UpperCamel... | 80 |
"""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_schedule_with_warmup, set_s... | 682 | 0 |
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase ):
__snake_case : Union[str, Any] = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
__snake_case : Union[str, Any] = n - k
# Calc... | 81 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 682 | 0 |
"""simple docstring"""
import os
import sys
import unittest
lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: ... | 82 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
... | 682 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
lowerCAmelCase__ = {
'''sample_size''': 32,
'''in_channels''': 3,
'''out_channels''': 3,
'''layers_p... | 83 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = r'''
... | 682 | 0 |
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
if not head:
return True
# split the list to two parts
lowercase , lowercase = head.next, head
while fast and fast.next:
lowercase = fast.next.next
lowercase = slow.next
lowercase = slow.next
lowerca... | 84 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.te... | 682 | 0 |
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuratio... | 85 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivi... | 682 | 0 |
from copy import deepcopy
class _a :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase : list[int] | None = None , UpperCAmelCase : int | None = None ):
if arr is None and size is not None:
... | 86 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = np.max(lowerCAmelCase_ , axis=-1 , keepdims=lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = ... | 682 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCamelCase : Any = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
... | 87 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_C... | 682 | 0 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 88 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 0 |
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
SCREAMING_SNAKE_CASE : Optional[Any] = "src/transformers"
# This is to make sure the transformers mod... | 89 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegment... | 90 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 0 |
"""simple docstring"""
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _snake_case ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
with p... | 91 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {"""configurat... | 92 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__name__)
__A = ... | 93 |
"""simple docstring"""
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.mo... | 682 | 0 |
'''simple docstring'''
SCREAMING_SNAKE_CASE = {
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'da... | 94 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 0 |
"""simple docstring"""
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils imp... | 95 |
"""simple docstring"""
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_... | 682 | 0 |
"""simple docstring"""
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(REP... | 96 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 0 |
from typing import Dict, Optional
import numpy as np
import datasets
__a = '\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two classes) or multi-class segmentat... | 97 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 0 |
'''simple docstring'''
import functools
def a__ ( lowercase : list[int], lowercase : list[int] ) -> int:
"""simple docstring"""
if not isinstance(lowercase, lowercase ) or not all(isinstance(lowercase, lowercase ) for day in days ):
raise ValueE... | 98 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 | 0 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
... | 99 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a__ : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization_... | 682 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.