code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import Gradient... | 84 |
"""simple docstring"""
def _snake_case ( lowercase__ : list[int] ) -> list[list[int]]:
'''simple docstring'''
lowerCAmelCase_ :Optional[Any] = []
if len(lowercase__ ) == 1:
return [nums.copy()]
for _ in range(len(lowercase__ ) ):
... | 84 | 1 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_uti... | 365 |
"""simple docstring"""
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextMode... | 1 | 0 |
import math
import sys
def __snake_case ( __UpperCamelCase : Optional[Any] ):
"""simple docstring"""
A_ = ""
try:
with open(_A ,"rb" ) as binary_file:
A_ = binary_file.read()
for dat in data:
... | 312 |
import numpy
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : Union[str, Any] , __lowercase : numpy.ndarray , __lowercase : numpy.ndarray ):
"""simple docstring"""
... | 187 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
_lowerCAmelCase : Any = logging.get_logger(__name__)
class A_ ( _a ):
def __init__( self: List[Any] ,*__lowerCAmelCase: Dict ,**__lowe... | 340 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def lowerCamelCase_( _lowerCamelCase ) -> Any:
'''simple docstring'''
for param in module.parameters():
_lowerCamelCase : Optional[int] = False
def ... | 340 | 1 |
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self : Optional[int]) ->Tuple:
'''simple docstring'''
A__ = {} # Mapping from char to TrieNode
A__ = False
def SCREAMING_SNAKE_CASE ( self ... | 14 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_g... | 72 | 0 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( snake_case_ )... | 353 |
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, re... | 250 | 0 |
"""simple docstring"""
import os
import sys
import transformers
UpperCAmelCase = """3"""
print("""Python version:""", sys.version)
print("""transformers version:""", transformers.__version__)
try:
import torch
print("""Torch version:""", torch.__version__)
print("""Cuda available:""", torch.cuda.is_... | 256 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, float... | 55 | 0 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
if ... | 33 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A : Optional[Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDepend... | 33 | 1 |
"""simple docstring"""
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 imp... | 54 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _snake_case ( lowercase__ , lowercase__ ):
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(lowercase__ , ... | 96 | 0 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 356 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warning... | 25 | 0 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __UpperCamelCase ( lowerCAmelCase__ : Union[str, Any] , lowerCAmelCase__ : Tuple=False ):
__a : List[Any] = OmegaConf.load(lowerCAmelCase_ )
if display:
... | 216 |
import re
from filelock import FileLock
try:
import nltk
_snake_case : Any = True
except (ImportError, ModuleNotFoundError):
_snake_case : Union[str, Any] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', quiet=True)
d... | 284 | 0 |
"""simple docstring"""
from PIL import Image
def _SCREAMING_SNAKE_CASE ( _lowercase : Image , _lowercase : int ) ->Image:
'''simple docstring'''
a : Dict = (259 * (level + 255)) / (255 * (259 - level))
def contrast(_... | 360 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a : List[str] = {
'''configuration_perceiver'''... | 79 | 0 |
'''simple docstring'''
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
_UpperCamelCase : Dict = collections.na... | 304 | from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_te... | 143 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def __lowerCamelCase ( __a :int ) -> Any:
"""simple docstring"""
A__ = SwinConf... | 276 |
import unittest
import numpy as np
def __lowerCamelCase ( __a :np.ndarray , __a :np.ndarray , __a :np.ndarray , __a :np.ndarray | None = None , ) -> np.ndarray:
"""simple docstring"""
A__ = np.s... | 276 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : str = logging.get_logger(__name__)
lowerCAmelCase : Optiona... | 291 | '''simple docstring'''
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 s... | 1 | 0 |
def _lowercase ( _UpperCAmelCase , _UpperCAmelCase = False ) -> str:
if not isinstance(_UpperCAmelCase , _UpperCAmelCase ):
lowerCamelCase =F"""Expected string as input, found {type(_UpperCAmelCase )}"""
raise ValueError(_UpperCAmelCase )
if not isinstance... | 262 |
import qiskit
def _lowercase ( _UpperCAmelCase , _UpperCAmelCase ) -> qiskit.result.counts.Counts:
lowerCamelCase =qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
lowerCamelCase =qiskit.QuantumCircuit(_UpperCAmelCase ... | 262 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase :Tuple = {
'''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig'''],
}
try:
if no... | 331 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase :Tuple = {'''processing_layoutxlm''': ['''L... | 331 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase :Optional[int] = logging.get_logger(__name__)
_lowerCAmelCase :List[str] = {
'BAAI/AltCLIP': 'https://huggingface.co/BAAI/AltCLIP... | 68 |
"""simple docstring"""
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from torch.... | 68 | 1 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import B... | 266 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase ( __UpperCamelCase = 1_0_0_0_0_0_0 , __UpperCamelCase = 1_0 ):
"""simple docstring"""
__A = defaultdict(__UpperCamelCase )
for outer_width in range(3 , ... | 266 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}
try:
if not is_torch_available(... | 352 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
UpperCAmelCase__ = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONFIG_ARCHIVE_M... | 30 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : Tuple = {
'''configuration_convbert''': ['''CONVBERT_... | 33 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_v... | 33 | 1 |
"""simple docstring"""
from collections.abc import Generator
from math import sin
def a__ ( __lowercase ) -> bytes:
if len(__lowercase ) != 32:
raise ValueError("Input must be of length 32" )
_A = B""
for i in [3, 2, 1, 0]:
littl... | 163 |
"""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,
LMSD... | 163 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart i... | 72 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..... | 25 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowerCAm... | 242 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
lowercase ='\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitle={EMNLP},\n... | 242 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : str = logging.get_logger(__name__)
snake_case__ : int = {
'''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/config.json''',
# See al... | 60 |
'''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 import VQDi... | 79 | 0 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetP... | 240 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def _a ( ):
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = ArgumentParser('''Diffusers CLI tool''' , usage='''diffuse... | 240 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
A__: Optional[int] = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWit... | 276 |
'''simple docstring'''
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_sq... | 276 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase_ = {
'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
'tokenization_mvp'... | 111 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase_ = {
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE... | 111 | 1 |
"""simple docstring"""
def _a ( _SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
snake_case_ = len(_SCREAMING_SNAKE_CASE )
snake_case_ = sum(_SCREAMING_SNAKE_CASE )
snake_case_ = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1... | 347 |
"""simple docstring"""
def _a ( _SCREAMING_SNAKE_CASE ) -> bool:
if num < 0:
return False
snake_case_ = num
snake_case_ = 0
while num > 0:
snake_case_ = rev_num * 10 + (num % 10)
num //= 10
return ... | 347 | 1 |
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def _SCREAMING_SNAKE_CASE ( ):
'''simple docstring'''
lowerCamelCase_ , lowerCamelCase_ = 9, 14 # noqa: F841
lowerCamelCase_ = ... | 208 |
import math
def _SCREAMING_SNAKE_CASE ( lowercase : int ):
'''simple docstring'''
lowerCamelCase_ = 0
lowerCamelCase_ = 0
while num > 0:
lowerCamelCase_ = num % 8
lowerCamelCase_ = octal... | 208 | 1 |
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
lowerCAmelCase__ = datasets.logging.get_logger(__name__)
lowerCAmelCase__ = """\
@inproceedings{bleurt,
title={BLEURT: Learning Robust Metrics for Text Generation},
author=... | 68 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
cached_file,
get_file... | 68 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def UpperCAmelCase__ ( UpperCAmelCase__ ) -> int:
if not postfix_notation:
return 0
A_ = {"""+""", """-""", """*""", """/"""}
A_ = []
for token in postfix_notati... | 101 |
'''simple docstring'''
from functools import lru_cache
@lru_cache
def UpperCAmelCase__ ( UpperCAmelCase__ ) -> int:
if num < 0:
raise ValueError("""Number should not be negative.""" )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__m... | 101 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def lowerCAmelCase_ ( snake_case_ : str ) -> str:
'''simple do... | 1 |
from __future__ import annotations
def a ( snake_case__: list[int] , snake_case__: int , snake_case__: int , snake_case__: int ):
'''simple docstring'''
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and... | 30 | 0 |
"""simple docstring"""
from ....utils import logging
__A = logging.get_logger(__name__)
class UpperCAmelCase (_UpperCAmelCase ):
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase=None , _UpperCAmelCase=2048 ):
... | 2 | """simple docstring"""
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__A = get_tests_dir("fixtu... | 2 | 1 |
'''simple docstring'''
import warnings
from ..trainer import Trainer
from ..utils import logging
__A =logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self , _lowerCamelCase=None , **_lowerCamelCase):
warning... | 163 |
'''simple docstring'''
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import ... | 163 | 1 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from... | 352 |
"""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
#
#... | 57 | 0 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
__snake_case =datasets.utils.logging.get_logger(__name__)
@datacla... | 4 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 242 | 0 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def __UpperCamelCase ( UpperCAmelCase ):
lowercase__ , lowercase__ , lowercase__ : str = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_9_8_9 * r + 0.5_8_7_0 * g + 0.1_1_4_0 * b
de... | 214 | '''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pip... | 214 | 1 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, logging
from .benchma... | 240 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
snake_case : List[Any] = datasets.logging.get_logger(__name__)
snake_case : List[str] = '''\
@InPro... | 240 | 1 |
from math import factorial, radians
def lowercase( UpperCamelCase_ , UpperCamelCase_ = 18 , UpperCamelCase_ = 10 ) -> float:
'''simple docstring'''
UpperCamelCase = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from degrees to radians
UpperCa... | 361 | import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionXLImgaImgPipeline,
UNetaDCondi... | 165 | 0 |
def A__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__) -> int:
return int((input_a, input_a).count(0) != 0)
def A__ ( ) -> None:
assert nand_gate(0 , 0) == 1
assert nand_gate(0 , 1) == 1
assert nand_gate(1 , 0) == 1
assert nand... | 111 |
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
__UpperCAmelCase : Any = "src/diffusers"
# Matches is_xxx_available()
__UpperCAmelCase : List[str] ... | 111 | 1 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytes... | 207 |
from math import factorial
class _UpperCAmelCase :
"""simple docstring"""
def __init__( self : Dict , lowerCAmelCase_ : Optional[int] , lowerCAmelCase_ : str ) -> Union[str, Any]:
__lowerCAmelCase = real
if isinstance(lowerCAmelCase_ , lowerCA... | 207 | 1 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def a_ ( _lowerCAmelCase ,_lowerCAmelCase ,_lowerCAmelCase ,_lowerCAm... | 208 |
'''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_sentence... | 208 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE :Optional[Any] = {
'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP',... | 124 |
import numpy
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : List[str] ,A : numpy.ndarray ,A : numpy.ndarray ):
__A = input_array
# Random initial weights are assigned where first argument is the
# number of nodes in previou... | 124 | 1 |
lowercase__ :Optional[int] = [
"DownloadConfig",
"DownloadManager",
"DownloadMode",
"StreamingDownloadManager",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager
| 101 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransformer,... | 101 | 1 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_tf... | 357 |
"""simple docstring"""
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class lowerCamelCase ( _UpperCAmelCase ):
lowercase : Union[str, Any] = 'EncodecFeatureExtractor'
lowercase : Lis... | 27 | 0 |
'''simple docstring'''
from ....utils import logging
lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
class __lowerCAmelCase (lowercase_ ):
'''simple docstring'''
def __init__(self : Optional[int] , UpperCamelCase : Union[str, Any] ... | 2 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : Tuple = logging.get_logger(__name__)
lowerCamelCase : Dict = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# S... | 2 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Union[str, Any] = {
"configuration_xlm_roberta_xl": [
"XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP",
"XLMRobertaXLConfig",
"XLMRobertaXLOn... | 367 |
from math import isqrt
def SCREAMING_SNAKE_CASE ( __UpperCamelCase) -> bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(__UpperCamelCase) + 1))
def SCREAMING_SNAKE_CASE ( __UpperCamelCase = 10**6) -> int:
a = 0
a = 1
... | 180 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resiz... | 343 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = False
while is_sorted is False: # Until all the indices are traversed keep looping
__lowerCAmelCase = True
for i in range(0 , len(_UpperCamelCase ) - ... | 57 | 0 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def UpperCAmelCase ( a_ ) -> str:
"""simple docstring"""
... | 124 |
import argparse
from collections import defaultdict
import yaml
SCREAMING_SNAKE_CASE :str = 'docs/source/en/_toctree.yml'
def UpperCAmelCase ( a_ ) -> int:
"""simple docstring"""
__A = defaultdict(a_ )
for doc in model_doc:
... | 124 | 1 |
def snake_case__ ( SCREAMING_SNAKE_CASE_ : str = "The quick brown fox jumps over the lazy dog" , ):
'''simple docstring'''
lowercase__ : str = set()
# Replace all the whitespace in our sentence
lowercase__ : Tuple = input_str.replace(' ' , ... | 214 |
from __future__ import annotations
def snake_case__ ( SCREAMING_SNAKE_CASE_ : dict , SCREAMING_SNAKE_CASE_ : str ):
'''simple docstring'''
lowercase__ , lowercase__ : List[str] = set(SCREAMING_SNAKE_CASE_ ), [start]
while stack:
lowercase__... | 214 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : List[Any] = {
'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'],
'feature_extraction_mctct... | 360 |
"""simple docstring"""
# 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 ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noq... | 233 | 0 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformers.ut... | 8 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
A_ : str = logging.get_logger(__name__)
# TODO: upload to AWS
A_ : Optional[int] = {
"yjernite/retribert-base-uncased": (
"https://huggingface.... | 165 | 0 |
def UpperCAmelCase_( a__ , a__ ):
"""simple docstring"""
return int((input_a, input_a).count(0 ) == 0 )
def UpperCAmelCase_( ):
"""simple docstring"""
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
as... | 19 |
from math import pi, sqrt, tan
def UpperCAmelCase_( a__ ):
"""simple docstring"""
if side_length < 0:
raise ValueError('''surface_area_cube() only accepts non-negative values''' )
return 6 * side_length**2
def UpperCAmelCase_( a__ , a__ , a__ ):
""... | 19 | 1 |
from __future__ import annotations
from collections.abc import Callable
A__ : Optional[Any] = list[list[float | int]]
def a ( lowerCamelCase_ , lowerCamelCase_ ):
'''simple docstring'''
lowercase__ = len(lowerCamelCase_ )
lowercase__ = [[0 for _ in ran... | 207 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_commo... | 207 | 1 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def _A ( snake_case = 1_50_00_00 ) -> int:
_lowercase : defaultdict = defaultdict(snake_case )
_lowercase : Optional[Any] = 2
while 2 * euclid_m * (euc... | 199 |
'''simple docstring'''
import os
import sys
import unittest
_snake_case = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object,... | 199 | 1 |
# Lint as: python3
import itertools
import os
import re
lowerCamelCase : Optional[int] = re.compile(r'([A-Z]+)([A-Z][a-z])')
lowerCamelCase : Dict = re.compile(r'([a-z\d])([A-Z])')
lowerCamelCase : Union[str, Any] = re.compile(r'(?<!_)_(?!_)')
lo... | 124 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def SCREAMING_SNAKE_CASE__ ( lowercase ,lowercase = "cpu" ,lowercase = None ) -> None:
snake_case : int = torch.load(lowercase ,map_location=lowercase )
for k, v in tqdm(state_... | 124 | 1 |
class UpperCamelCase :
def __init__( self ,__UpperCamelCase ) -> Optional[int]:
'''simple docstring'''
lowercase_ : Optional[Any] = n
lowercase_ : Tuple = [None] * self.n
lowercase_ : Any = ... | 362 | """simple docstring"""
class UpperCamelCase :
def __init__( self ,__UpperCamelCase ,__UpperCamelCase ) -> int:
'''simple docstring'''
lowercase_ : List[Any] = name
lowercase_ : int = val
def __str__( s... | 321 | 0 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
... | 320 |
'''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, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils... | 27 | 0 |
'''simple docstring'''
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMi... | 369 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
... | 270 | 0 |
import math
def lowerCAmelCase_ (lowerCAmelCase__: int ):
"""simple docstring"""
UpperCAmelCase_: List[str] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(snake_case__ )
def l... | 147 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
'BridgeTower/bridgetower-base': 'https://huggingface.co/BridgeTowe... | 180 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_lowerCamelCase )
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
UpperCAmelCase ... | 355 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pi... | 349 | 0 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
lowerCamelCase : Optional[int] = datasets.utils.logging.get_logger(__name__)
@dataclass
class ... | 124 |
import math
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> int:
if not isinstance(lowercase ,lowercase ):
snake_case : List[Any] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(lowercase )
if number < 1:
snake... | 124 | 1 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def SCREAMING_SNAKE_CASE__ ( lowercase ,lowercase ) -> Union[str, Any]:
snake_case : List[Any] = k_siz... | 350 |
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processor import AttnAddedK... | 176 | 0 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor... | 107 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 233 | 0 |
'''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main... | 362 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _co... | 31 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A =logging.get_logger(__name__)
__A ={
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/config.json''',
}
class _SCREAMING_SNAKE_CASE ( snake_case_ ):
lowerCAmelCase__ ... | 19 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunDiscreteScheduler
from ...... | 19 | 1 |
"""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,
PILImageRes... | 126 | """simple docstring"""
import math
def SCREAMING_SNAKE_CASE ( ) -> None:
_lowerCAmelCase : Any = input("""Enter message: """ )
_lowerCAmelCase : List[Any] = int(input(f"Enter key [2-{len(_lowerCamelCase ) - 1}]: " ) )
_lowerCAmelCase ... | 126 | 1 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ : str , S... | 199 |
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_common import TokenizerTeste... | 199 | 1 |
import os
SCREAMING_SNAKE_CASE__ = {"""I""": 1, """V""": 5, """X""": 1_0, """L""": 5_0, """C""": 1_0_0, """D""": 5_0_0, """M""": 1_0_0_0}
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: str ):
'''simple docstring'''
lowercase_ = 0
lowercase_ = 0
while i... | 297 |
# 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 required by applic... | 297 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForSemanticSegmentation,
Se... | 12 |
'''simple docstring'''
from __future__ import annotations
import math
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE ) -> None:
"""simple docstring"""
UpperCamelCase = size
# approximate the ov... | 321 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
lowerCAmelCase__ = ['small', 'medium', 'large']
lowerCAmelCase__ = 'lm_head.decoder.weight'
lowerCAmelCase__ = 'lm_head.weight'
def snake_case_ ( A_ : str, A_ :... | 353 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import M... | 175 | 0 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class SCREAMING_SNAKE_CASE__ ( UpperCAmelCase__ ):
def SCREAMING_SNAKE_CASE ( self ) -> Union[str, Any]:
'''simple docstring'''
r... | 109 |
"""simple docstring"""
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers... | 268 | 0 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class lowercase_ ( __SCREAMING_SNAKE_CASE ... | 261 |
from math import pow, sqrt
def lowerCamelCase__ ( *a__ : float ) -> bool:
UpperCamelCase_ = len(a__ ) > 0 and all(value > 0.0 for value in values )
return result
def lowerCamelCase__ ( a__ : float , a__ : float ) ... | 261 | 1 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, p... | 116 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
fr... | 349 | 0 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase = ["""image_processor""", """to... | 83 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _UpperCamelCase... | 83 | 1 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test... | 85 |
import os
from math import logaa
def _lowercase ( UpperCamelCase_ = "base_exp.txt" ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 0
SCREAMING_SNAKE_CASE__ = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(UpperCamelCase_ )... | 176 | 0 |
from __future__ import annotations
def snake_case_ (__A : list[float] , __A : list[float] ) -> float:
__lowerCAmelCase = sorted(numsa + numsa )
__lowerCAmelCase = divmod(len(__A ) , 2 )
if mod == 1:
return a... | 359 |
from __future__ import annotations
def snake_case_ (__A : list[float] , __A : list[float] ) -> float:
__lowerCAmelCase : Union[str, Any] = sorted(numsa + numsa )
__lowerCAmelCase ,__lowerCAmelCase : Optional[int] = div... | 139 | 0 |
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def _UpperCAmelCase (UpperCamelCase__ : ... | 11 | '''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import 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_avai... | 31 | 0 |
"""simple docstring"""
import math
def _lowerCamelCase(__UpperCamelCase , __UpperCamelCase = 0 , __UpperCamelCase = 0 ) -> list:
_lowerCAmelCase =end or len(__UpperCamelCase )
for i in range(__UpperCamelCase , __UpperCamelCase ):
_lowerCAmelCase =i
_lowerCAmelCa... | 341 |
"""simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
__A = argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=str, required=Tr... | 341 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import Pegas... | 126 |
"""simple docstring"""
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from... | 126 | 1 |
from __future__ import annotations
from typing import Any
def SCREAMING_SNAKE_CASE__ ( __a ):
create_state_space_tree(__a , [] , 0 )
def SCREAMING_SNAKE_CASE__ ( __a , __a , __a ):
if index == len(__a ):
print(__a )
return
cre... | 88 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import It... | 88 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
fr... | 297 |
'''simple docstring'''
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data... | 297 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils imp... | 207 |
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 lowercase ( self : Any ) -> Optional[int]:
... | 207 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json",
"uclanlp/visualbert-vqa-pre": "https://hug... | 66 | from maths.prime_check import is_prime
def __lowercase ( lowerCamelCase : int ):
if not isinstance(lowerCamelCase , lowerCamelCase ):
UpperCamelCase_ : List[str] = F"Input value of [number={number}] must be an integer"
raise TypeError(lowerCamelCase )
if is_prime(lowerCamel... | 175 | 0 |
"""simple docstring"""
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transforme... | 241 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
... | 241 | 1 |
"""simple docstring"""
import torch
from diffusers import StableDiffusionPipeline
SCREAMING_SNAKE_CASE__:int = """path-to-your-trained-model"""
SCREAMING_SNAKE_CASE__:Union[str, Any] = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")
SCREAMIN... | 261 | """simple docstring"""
import copy
import re
class snake_case__ :
_snake_case : Dict = """hp"""
_snake_case : List[str] = {}
_snake_case : int = None
@classmethod
def a__ ( cls , lowerCamelCase , lowerCamelCase ):
__a = prefix
... | 261 | 1 |
"""simple docstring"""
from statistics import mean
import numpy as np
def __UpperCAmelCase ( UpperCAmelCase_ : int , UpperCAmelCase_ : Any , UpperCAmelCase_ : Optional[Any] , UpperCAmelCase_ : int ) -> list:
'''simple docstring'''
_... | 364 | """simple docstring"""
from __future__ import annotations
import os
from typing import Any
import requests
_a : int= "https://api.github.com"
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
_a : Dict= BASE_URL + "/user"
... | 95 | 0 |
'''simple docstring'''
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization impor... | 83 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : int = logging.get_logger(__name__)
snake_case_ : Optional[Any] = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}
c... | 83 | 1 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
f... | 358 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase ):
... | 220 | 0 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.modeling_flax... | 138 |
'''simple docstring'''
from __future__ import annotations
import math
from collections.abc import Callable
def A_ ( snake_case , snake_case , snake_case , snake_case = 100 , ):
SCREAMING_SNAKE_CASE:Any = x_start
SCREAMING_SNAKE_CASE:int ... | 139 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''funnel-transformer/small''': '''https://huggingface.co/funnel-transformer/small/resolve/main/config.json''',
'''... | 364 | """simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
... | 85 | 0 |
'''simple docstring'''
import math
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = 0 , _SCREAMING_SNAKE_CASE = 0 ):
_snake_case = end or len(_SCREAMING_SNAKE_CASE )
for i in range(_SCREAMING_SNAKE_CASE , _SCREAMING_S... | 341 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__lowerCAmelCase = {
'configuration_perceiver': ['PERCEIVER_PRETRAINED_CONFIG_ARCHI... | 341 | 1 |
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_availab... | 247 |
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_ = {
'configuration... | 247 | 1 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class UpperCAmelCase_ ( _A ... | 88 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging im... | 88 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch... | 220 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.i... | 220 | 1 |
from collections.abc import Sequence
def a ( lowerCamelCase_ , lowerCamelCase_ = False ):
'''simple docstring'''
if not arr:
return 0
lowercase__ = 0 if allow_empty_subarrays else float('''-inf''' )
lowercase__ = 0.0
for num in arr:
low... | 207 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def a ( lowerCamelCase_ ):
'''simple docstring'''
lowercase__ = []
lowercase__ = []
lowercase__ = []
for ... | 207 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_visi... | 253 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_a... | 253 | 1 |
from ..utils import DummyObject, requires_backends
class lowercase_ ( metaclass=lowercase ):
'''simple docstring'''
__snake_case = ['''torch''']
def __init__( self : Optional[int] , *__UpperCAmelCase ... | 0 |
"""simple docstring"""
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_avai... | 241 | 0 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError('To use the rich extension, install rich with `pip install rich`')
| 39 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_... | 39 | 1 |
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