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 |
|---|---|---|---|---|
class __snake_case :
'''simple docstring'''
def __init__( self , A_ , A_ , A_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = name
SCREAMING_SNAKE_CASE__ = value
SCREAMING_SNAKE_CASE__ = wei... | 100 |
"""simple docstring"""
import torch
from transformers import AutoModel
class _a ( torch.nn.Module):
"""simple docstring"""
def __init__( self : Any , __UpperCamelCase : Optional[int]="sayef/fsner-bert-base-uncased" )->List[str]:
super(__UpperCamelCase ... | 602 | 0 |
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,
MobileViTVaForImageClassification,
... | 101 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : List[str] = {
"configuration_roberta": ... | 602 | 0 |
"""simple docstring"""
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class lowercase__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
__lowerCAmelCase : Tuple = CustomTokenizer
pass
| 102 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__A : Tuple = logging.get_logger(__name__)
__A : Lis... | 602 | 0 |
"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parque... | 103 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _a :
"""simple docstring"""
def __init__( self : int , __UpperCamelCase : list[str] )->Dict:
_UpperCAmelCase = []
self.adlist.append(
... | 602 | 0 |
"""simple docstring"""
from math import isqrt
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> bool:
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2, isqrt(UpperCAmelCase_ ) + 1 ) )
def _lowe... | 104 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
_UpperCAmelCase = int(_SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
return str(_SCREAMING_SNAKE_CASE )
... | 602 | 0 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_vision_availabl... | 105 |
"""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, HTTPExce... | 602 | 0 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configur... | 106 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_com... | 602 | 0 |
'''simple docstring'''
class lowercase_ :
"""simple docstring"""
def __init__( self : Tuple, UpperCamelCase__ : int ) -> None:
_A = size
_A = [0] * size
_A = [0] * size
@staticmethod
def __UpperCAmelCase ( UpperC... | 107 |
"""simple docstring"""
from itertools import permutations
def lowercase ( _SCREAMING_SNAKE_CASE : tuple ):
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
... | 602 | 0 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class SCREAMING_SNAKE_C... | 108 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : Tuple = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pretrained... | 602 | 0 |
'''simple docstring'''
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,... | 109 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers im... | 602 | 0 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_commo... | 469 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelera... | 602 | 0 |
def a_ (__A = 1_000_000 ) -> Dict:
"""simple docstring"""
__a : List[str] = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , ... | 351 |
"""simple docstring"""
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : List[Any] = {
"facebook/encodec_24khz": "https://huggi... | 602 | 0 |
def UpperCamelCase__ ( _A: Any ):
'''simple docstring'''
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6... | 479 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import ... | 602 | 0 |
'''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 DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import... | 526 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowercase ( _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : Tuple ):
'''simple docs... | 602 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_visio... | 482 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A : List[str] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for... | 602 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
SCREAMING_SNAKE_... | 523 |
"""simple docstring"""
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils impor... | 602 | 0 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _lowercase ( lowercase__ , lowercase__ , lowercase__ ):
if gpta_config_file... | 492 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : List[Any] = logging.get_logger(__name__)
__A : Optional[Any] = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kineti... | 602 | 0 |
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
class UpperCam... | 491 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__A : Optional[int] = {
"configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"... | 602 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ : List[Any] , snake_case_ : str , snake_case_ : Any , snake_case_ : Any ) ->Tuple: # noqa: E741
while r - l > 1:
l... | 174 |
"""simple docstring"""
__A : int = frozenset(
[
"prompt",
"height",
"width",
"guidance_scale",
"negative_prompt",
"prompt_embeds",
"negative_prompt_embeds",
"cross_attention_kwargs",
]
)
__A : Any = ... | 602 | 0 |
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
from ... | 10 |
"""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 impor... | 602 | 0 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __a (UpperCamelCase_):
'''simple docstring'''
_SCREAMING_SNAKE_CASE :Optional[int] = """Speech2TextFeatureExtractor"""
_SCREAMING_SNAKE_CASE :Tu... | 680 |
"""simple docstring"""
__A : Optional[int] = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
fro... | 602 | 0 |
import re
def lowerCamelCase_ ( UpperCamelCase__ : str ) -> Optional[int]:
"""simple docstring"""
__lowerCamelCase = re.compile(R'^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$' )
if match := re.search(_SCREAMING_SNAKE_CASE , _SCREAMING_SN... | 469 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 602 | 0 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ (__A , __A , __A ) -> str:
"""simple docstring"""
__a : Li... | 351 |
"""simple docstring"""
import torch
from transformers import AutoModel
class _a ( torch.nn.Module):
"""simple docstring"""
def __init__( self : Any , __UpperCamelCase : Optional[int]="sayef/fsner-bert-base-uncased" )->List[str]:
super(__UpperCamelCase ... | 602 | 0 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class UpperCamelCase_ (... | 479 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : List[str] = {
"configuration_roberta": ... | 602 | 0 |
'''simple docstring'''
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
f... | 526 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__A : Tuple = logging.get_logger(__name__)
__A : Lis... | 602 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
lowerCAmelCase__ =TypeVar("T")
class A__( Generic[T] ):
def __init__( self : int , __SCREAMING_SNAKE_CASE : T ) -... | 482 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _a :
"""simple docstring"""
def __init__( self : int , __UpperCamelCase : list[str] )->Dict:
_UpperCAmelCase = []
self.adlist.append(
... | 602 | 0 |
'''simple docstring'''
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
SCREAMING_SNAKE_CASE_ = {
"n_samples": 64,
"horizon": 32,
"num_inference_steps": 20,
"n_guide_steps": 2, # can set to 0 for faster sampling, does not use value n... | 523 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
_UpperCAmelCase = int(_SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
return str(_SCREAMING_SNAKE_CASE )
... | 602 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
"roberta-base": "https://huggingface.co/... | 492 |
"""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, HTTPExce... | 602 | 0 |
import os
def UpperCamelCase ( _A : str = "input.txt" )-> List[Any]:
"""simple docstring"""
with open(os.path.join(os.path.dirname(_SCREAMING_SNAKE_CASE ) , _SCREAMING_SNAKE_CASE ) ) as input_file:
A__ = [
[int(_SCREAMIN... | 491 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_com... | 602 | 0 |
"""simple docstring"""
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePl... | 174 |
"""simple docstring"""
from itertools import permutations
def lowercase ( _SCREAMING_SNAKE_CASE : tuple ):
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
... | 602 | 0 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowerCAmelCase_ ( enum.Enum ):
Up... | 10 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : Tuple = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pretrained... | 602 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a :List[Any] = logging.get_logger(__name__)
a :Optional[Any] = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/co... | 680 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers im... | 602 | 0 |
class __lowerCAmelCase : # Public class to implement a graph
"""simple docstring"""
def __init__( self , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ) -> None:
'''simple docstring'''
__lowerCamelCase = r... | 469 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelera... | 602 | 0 |
import math
from collections.abc import Iterator
from itertools import takewhile
def a_ (__A ) -> Optional[Any]:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 351 |
"""simple docstring"""
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : List[Any] = {
"facebook/encodec_24khz": "https://huggi... | 602 | 0 |
from __future__ import annotations
from typing import TypedDict
class UpperCamelCase_ ( __UpperCamelCase ):
"""simple docstring"""
A = 42
A = 42
def UpperCamelCase__ ( _A: str ):
'''simple docstring'''
if not isinstance(_... | 479 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import ... | 602 | 0 |
'''simple docstring'''
import torch
from transformers import AutoModel
class a__( torch.nn.Module ):
def __init__( self : Any , __snake_case : Optional[int]="sayef/fsner-bert-base-uncased" ):
super(__UpperCamelCase , self ).__init__()
a :... | 526 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowercase ( _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : Tuple ):
'''simple docs... | 602 | 0 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _a ( UpperCAmelCase__ ) -> Optional[Any]:
return getitem, k
def _a ( UpperCAmelCase__ , UpperCAmelCase__ ) -> Li... | 482 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A : List[str] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for... | 602 | 0 |
'''simple docstring'''
import argparse
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_dummies.py
SCREAMING_SNAKE_CASE_ = "src/diffusers"
# Matches is_xxx_available()
SCREAMING_SNAKE_CASE_ = ... | 523 |
"""simple docstring"""
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils impor... | 602 | 0 |
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def _lowercase ( lowercas... | 492 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : List[Any] = logging.get_logger(__name__)
__A : Optional[Any] = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kineti... | 602 | 0 |
UpperCAmelCase_ : Optional[Any] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(100_000)]
def UpperCamelCase ( _A : int )-> Optional[int]:
"""simple docstring"""
A__ = 0
while number:
# Increased Speed Slightly by checki... | 491 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__A : Optional[int] = {
"configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"... | 602 | 0 |
"""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 .test_pipeline... | 174 |
"""simple docstring"""
__A : int = frozenset(
[
"prompt",
"height",
"width",
"guidance_scale",
"negative_prompt",
"prompt_embeds",
"negative_prompt_embeds",
"cross_attention_kwargs",
]
)
__A : Any = ... | 602 | 0 |
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_... | 10 |
"""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 impor... | 602 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a :List[str] = {
"configuration_roberta": ["ROBERTA_PRETRAINED_CON... | 680 |
"""simple docstring"""
__A : Optional[int] = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
fro... | 602 | 0 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __lowerCAmelCase ( __magic_name__ , _... | 469 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 602 | 0 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def a_ (__A , __A=False ) -> Any:
"""simple docstring"""
__a : int = OmegaConf.load(_SCREAMING_SNAKE_CASE )
if display:
... | 351 |
"""simple docstring"""
import torch
from transformers import AutoModel
class _a ( torch.nn.Module):
"""simple docstring"""
def __init__( self : Any , __UpperCamelCase : Optional[int]="sayef/fsner-bert-base-uncased" )->List[str]:
super(__UpperCamelCase ... | 602 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_determinism,
load_numpy... | 479 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : List[str] = {
"configuration_roberta": ... | 602 | 0 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCamelCase__ ( ):
print('Making key files...' )
make_key_files('rsa' , 1024 )
print('Key files ge... | 526 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__A : Tuple = logging.get_logger(__name__)
__A : Lis... | 602 | 0 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
lowerCAmelCase__ =get_logger(__name__)
lowerCAmelCase__ =r"\n Args:\n input_ids (`jnp.ndarray` of shap... | 482 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _a :
"""simple docstring"""
def __init__( self : int , __UpperCamelCase : list[str] )->Dict:
_UpperCAmelCase = []
self.adlist.append(
... | 602 | 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 PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_... | 523 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
_UpperCAmelCase = int(_SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
return str(_SCREAMING_SNAKE_CASE )
... | 602 | 0 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Train... | 492 |
"""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, HTTPExce... | 602 | 0 |
from string import ascii_uppercase
UpperCAmelCase_ : str = {str(ord(c) - 55): c for c in ascii_uppercase}
def UpperCamelCase ( _A : int , _A : int )-> List[str]:
"""simple docstring"""
if isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SN... | 491 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_com... | 602 | 0 |
"""simple docstring"""
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Con... | 174 |
"""simple docstring"""
from itertools import permutations
def lowercase ( _SCREAMING_SNAKE_CASE : tuple ):
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
... | 602 | 0 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def _snake_case ( ):
_UpperCamelCase , _UpperCamelCase = 9, 14 # noqa: F841
_UpperCamelCase = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[... | 10 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : Tuple = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pretrained... | 602 | 0 |
"""simple docstring"""
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
a :List[Any] = abspath(join(dirname(dirname(dirna... | 680 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers im... | 602 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : int ) -> Optional[Any]:
"""simple docstring"""
assert (
isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) and number_of_steps > 0
), F"""number_of_steps needs to be positive integer, your input {num... | 469 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelera... | 602 | 0 |
import functools
from typing import Any
def a_ (__A , __A ) -> Tuple:
"""simple docstring"""
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) or len(_SCREAMING_SNAKE_CASE ) == 0:
raise ValueError("the string should b... | 351 |
"""simple docstring"""
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : List[Any] = {
"facebook/encodec_24khz": "https://huggi... | 602 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : Any = logging.get_logger(__name__)
_a : str = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class UpperCamelCase_ ( __UpperCamelCase ):
... | 479 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import ... | 602 | 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 SPIECE_UNDERLINE, logging
lowerCAmelCase: List[Any] =... | 526 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowercase ( _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : Tuple ):
'''simple docs... | 602 | 0 |
"""simple docstring"""
def _a ( UpperCAmelCase__ = 2_00_00_00 ) -> str:
__SCREAMING_SNAKE_CASE = [0 for i in range(n + 1 )]
__SCREAMING_SNAKE_CASE = 1
__SCREAMING_SNAKE_CASE = 1
for i in range(2 , int(n**0.5 ) + 1 ):
... | 482 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A : List[str] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for... | 602 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNOR... | 523 |
"""simple docstring"""
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils impor... | 602 | 0 |
from __future__ import annotations
def _lowercase ( lowercase__ ):
if not nums:
raise ValueError('''List is empty''' )
return sum(_SCREAMING_SNAKE_CASE ) / len(_SCREAMING_SNAKE_CASE )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 492 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : List[Any] = logging.get_logger(__name__)
__A : Optional[Any] = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kineti... | 602 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCAmelCase_ : Tuple = {"tokenization_bertweet": ["BertweetTokenizer"]}
if TYPE_CHECKING:
from .tokenization_bertweet import BertweetTokenizer
else:
import sys
UpperCAmelCase_ : int ... | 491 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__A : Optional[int] = {
"configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"... | 602 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simpli... | 174 |
"""simple docstring"""
__A : int = frozenset(
[
"prompt",
"height",
"width",
"guidance_scale",
"negative_prompt",
"prompt_embeds",
"negative_prompt_embeds",
"cross_attention_kwargs",
]
)
__A : Any = ... | 602 | 0 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_modeling_common imp... | 10 |
"""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 impor... | 602 | 0 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) ->... | 680 |
"""simple docstring"""
__A : Optional[int] = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
fro... | 602 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : int = 100 ) -> Optional[Any]:
"""simple docstring"""
__lowerCamelCase = 0
__lowerCamelCase = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
... | 469 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 602 | 0 |
import random
def a_ (__A , __A , __A = False ) -> List[str]:
"""simple docstring"""
__a : List[Any] = {i: [] for i in range(_SCREAMING_SNAKE_CASE )}
# if probability is greater or equal than 1, then generate a complete graph
... | 351 |
"""simple docstring"""
import torch
from transformers import AutoModel
class _a ( torch.nn.Module):
"""simple docstring"""
def __init__( self : Any , __UpperCamelCase : Optional[int]="sayef/fsner-bert-base-uncased" )->List[str]:
super(__UpperCamelCase ... | 602 | 0 |
def UpperCamelCase__ ( _A: str ):
'''simple docstring'''
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def UpperCamelCase__ ( _A: str ):
'''simple docstring'''
__lowerCamelCase = ... | 479 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : List[str] = {
"configuration_roberta": ... | 602 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase: List[str] = {"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTC... | 526 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__A : Tuple = logging.get_logger(__name__)
__A : Lis... | 602 | 0 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transfor... | 482 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _a :
"""simple docstring"""
def __init__( self : int , __UpperCamelCase : list[str] )->Dict:
_UpperCAmelCase = []
self.adlist.append(
... | 602 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_ = {"configuration_beit": ["BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BeitCon... | 523 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
_UpperCAmelCase = int(_SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
return str(_SCREAMING_SNAKE_CASE )
... | 602 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase )
class __lowercase (_UpperCAmelCase ):
_UpperCamelCase = field(default="""audio-cl... | 492 |
"""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, HTTPExce... | 602 | 0 |
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
UpperCAmelCase_ : List[Any] = logging.getLogger(__name_... | 491 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_com... | 602 | 0 |
"""simple docstring"""
from collections import deque
from .hash_table import HashTable
class A_ ( A__ ):
"""simple docstring"""
def __init__( self :Any , *lowerCamelCase_ :Optional[Any] , **lowerCamelCase_ :Tuple ):
"""... | 174 |
"""simple docstring"""
from itertools import permutations
def lowercase ( _SCREAMING_SNAKE_CASE : tuple ):
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
... | 602 | 0 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion import StableDiffu... | 10 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : Tuple = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pretrained... | 602 | 0 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRCon... | 680 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers im... | 602 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json",
# See al... | 469 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelera... | 602 | 0 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class snake_case_ ... | 351 |
"""simple docstring"""
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : List[Any] = {
"facebook/encodec_24khz": "https://huggi... | 602 | 0 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
_a : Optional[Any] = False
class UpperCamelCase_ ( ... | 479 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import ... | 602 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowerCAmelCase: Union[str, Any] = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
... | 526 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def lowercase ( _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : Tuple ):
'''simple docs... | 602 | 0 |
"""simple docstring"""
def _a ( UpperCAmelCase__ ) -> Tuple:
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print("Program to check whether a number is a Perfect number or not...")
lowerCAmelCase__ ... | 482 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A : List[str] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for... | 602 | 0 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class a ( unittest.TestCase ):
"""simple docstring"""
def lowercase_ ( self ):
'''simple docstring'''
... | 523 |
"""simple docstring"""
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils impor... | 602 | 0 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __lowercase (_UpperCAmelCase ):
@require_torch
def UpperCamelCase__ ( self ) ->int:
'''simple docstr... | 492 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : List[Any] = logging.get_logger(__name__)
__A : Optional[Any] = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kineti... | 602 | 0 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
... | 491 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__A : Optional[int] = {
"configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"... | 602 | 0 |
"""simple docstring"""
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcesso... | 174 |
"""simple docstring"""
__A : int = frozenset(
[
"prompt",
"height",
"width",
"guidance_scale",
"negative_prompt",
"prompt_embeds",
"negative_prompt_embeds",
"cross_attention_kwargs",
]
)
__A : Any = ... | 602 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"sail/poolformer_s12": "h... | 10 |
"""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 impor... | 602 | 0 |
"""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 docstring'''
@property
def ... | 680 |
"""simple docstring"""
__A : Optional[int] = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
fro... | 602 | 0 |
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils... | 469 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 602 | 0 |
UpperCAmelCase__ = [
"Audio",
"Array2D",
"Array3D",
"Array4D",
"Array5D",
"ClassLabel",
"Features",
"Sequence",
"Value",
"Image",
"Translation",
"TranslationVariableLanguages",
]
from .audio import Audio
from .features import ArrayaD, ArrayaD, ArrayaD,... | 351 |
"""simple docstring"""
import torch
from transformers import AutoModel
class _a ( torch.nn.Module):
"""simple docstring"""
def __init__( self : Any , __UpperCamelCase : Optional[int]="sayef/fsner-bert-base-uncased" )->List[str]:
super(__UpperCamelCase ... | 602 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add_start_docstrin... | 479 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : List[str] = {
"configuration_roberta": ... | 602 | 0 |
'''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... | 526 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__A : Tuple = logging.get_logger(__name__)
__A : Lis... | 602 | 0 |
"""simple docstring"""
from __future__ import annotations
lowerCAmelCase__ =[
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def _a ( UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , ) ... | 482 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _a :
"""simple docstring"""
def __init__( self : int , __UpperCamelCase : list[str] )->Dict:
_UpperCAmelCase = []
self.adlist.append(
... | 602 | 0 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_C... | 523 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
_UpperCAmelCase = int(_SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
return str(_SCREAMING_SNAKE_CASE )
... | 602 | 0 |
import os
from pathlib import Path
def _lowercase ( lowercase__ , lowercase__ , lowercase__ ):
__lowerCAmelCase : List[Any] = {
'''en''': '''Machine learning is great, isn\'t it?''',
'''ru''': '''Машинное обучение - это здорово, не так ли?''',
'... | 492 |
"""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, HTTPExce... | 602 | 0 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
UpperCAmelCase_ : int = 50_000
UpperCAmelCase_ : int = 5_000
UpperCAmelCase_ : List[Any] = os.path.split(__file__)
UpperCAmelCase_ ... | 491 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_com... | 602 | 0 |
"""simple docstring"""
import torch
from accelerate import PartialState
from accelerate.utils.operations import broadcast, gather, gather_object, pad_across_processes, reduce
def lowerCAmelCase_ ( snake_case_ : Optional[Any] ) ->Any:
return (torch.arange(state.num_proce... | 174 |
"""simple docstring"""
from itertools import permutations
def lowercase ( _SCREAMING_SNAKE_CASE : tuple ):
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
... | 602 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 10 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : Tuple = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pretrained... | 602 | 0 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 680 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers im... | 602 | 0 |
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowerCamelCase_ ... | 469 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelera... | 602 | 0 |
from __future__ import annotations
from collections import Counter
from random import random
class snake_case_ :
"""simple docstring"""
def __init__(self: Tuple ) -> int:
'''simple docstring'''
__a : Any = {}
d... | 351 |
"""simple docstring"""
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : List[Any] = {
"facebook/encodec_24khz": "https://huggi... | 602 | 0 |
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