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 |
|---|---|---|---|---|
'''simple docstring'''
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 _UpperCAmel... | 620 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _UpperCAmelCase ( unittest.TestCase ):
__lowerCame... | 620 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import pi, sqrt
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <=... | 620 |
'''simple docstring'''
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
UpperCamelCase__ = ['small', 'medium', 'large']
UpperCamelCase__ = 'lm_head.decoder.weight'
UpperCamelCase__ = 'lm_head.weight'
def __SCREAMING_SNAKE_CASE ( _UpperCamelC... | 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Any = len(_UpperCamelCase )
print("The following activities are selected:" )
# The first activity is always selected
lowerca... | 620 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 620 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class ... | 620 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
... | 620 | 1 |
'''simple docstring'''
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class _Upper... | 620 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 620 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_u... | 620 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 620 | 1 |
'''simple docstring'''
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class _Uppe... | 620 |
'''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... | 620 | 1 |
'''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
UpperCamelCase__ = 'src/diffusers'
# Matches is_xxx_available()
UpperCamelCase__ = re.compile(r'is\... | 620 |
'''simple docstring'''
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
UpperCamelCase__ = loggin... | 620 | 1 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoM... | 620 |
'''simple docstring'''
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, requi... | 620 | 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... | 620 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
)
| 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
return number | (1 << position)
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
return number & ~(1 <<... | 620 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase = 100 ):
"""simple docstring"""
lowercase_ : Dict = n * (n + 1) * (2 * n + 1) / 6
lowercase_ : int = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
i... | 620 | 1 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Optional[int] = 2
lowercase_ : Tuple = []
while i * i <= n:
if n % i:
i += 1
... | 620 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
i... | 620 | 1 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_R... | 620 |
'''simple docstring'''
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
f... | 620 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
... | 620 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ =... | 620 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCamelCase__ = logging.get_logger(__name__)
class _UpperCAmelCase ( snake_case ):
def __init__( self : Union[str, Any] , *a : Union[s... | 620 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
UpperCamelCase__ = False
try:
UpperCamelC... | 620 | 1 |
'''simple docstring'''
UpperCamelCase__ = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 1000000,
"gigajoule": 1000000000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 3600000,
"newtonmeter": 1.0,
"calorie_nutr": 4186.8,
"kilocalorie_nutr": 4186800.00,
... | 620 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ = {
'configuration_funnel': ['FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Funn... | 620 | 1 |
'''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, CLIPTextModel, CLIPTokenizer
... | 620 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ = {
'configuration_layoutlmv3': [
'LAYOUT... | 620 | 1 |
'''simple docstring'''
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCamelCase__ = 4
UpperCamelCase__ = 3
class _UpperCAmelCase (... | 620 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffus... | 620 | 1 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
UpperCamelCase__ = 3
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
print("Generating primitive root of p" )
while T... | 620 |
'''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, CLIPTextModel, CLIPTokenizer
... | 620 | 1 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _UpperCAmelCase ( unittest.TestCase , snake_case ):
def lowerCAmelCase__ ( self : Optional[int] ):
'''simple d... | 620 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Optional[int] = 2
lowercase_ : Tuple = []
while i * i <= n:
if n % i:
i += 1
... | 620 | 1 |
'''simple docstring'''
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__ = {
'facebook/xmod-base': 'h... | 620 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class _UpperCAmelCase ( nn.Module ):
__lowerCamelCase: int
__lowerCamelCase: jnp.dtype = jnp.floataa
def lowerCAmelCase__ ( self : Optional[Any] ):
... | 620 | 1 |
'''simple docstring'''
import unittest
from knapsack import knapsack as k
class _UpperCAmelCase ( unittest.TestCase ):
def lowerCAmelCase__ ( self : Union[str, Any] ):
'''simple docstring'''
lowercase_ : Optional[int] ... | 620 |
'''simple docstring'''
UpperCamelCase__ = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 1000000,
"gigajoule": 1000000000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 3600000,
"newtonmeter": 1.0,
"calorie_nutr": 4186.8,
"kilocalorie_nutr": 4186800.00,
... | 620 | 1 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common impor... | 620 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _UpperCAmelCase ( unittest.TestCase ):
__lowerCame... | 620 | 1 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
UpperCamelCase__ = datasets.u... | 620 |
'''simple docstring'''
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
UpperCamelCase__ = ['small', 'medium', 'large']
UpperCamelCase__ = 'lm_head.decoder.weight'
UpperCamelCase__ = 'lm_head.weight'
def __SCREAMING_SNAKE_CASE ( _UpperCamelC... | 620 | 1 |
'''simple docstring'''
import math
import os
import sys
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : List[Any] = ""
try:
with open(_UpperCamelCase , "rb" ) as binary_file:
lowercase_ : Optiona... | 620 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 620 | 1 |
'''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__ = collections.namedtuple('_Datase... | 620 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
... | 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
if n == 1 or not isinstance(_UpperCamelCase , _UpperCamelCase ):
return 0
elif n == 2:
return 1
else:
lowercase_ : Union[str, Any] = [0, 1]
... | 620 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 620 | 1 |
'''simple docstring'''
class _UpperCAmelCase :
def __init__( self : Union[str, Any] , a : Optional[Any] ):
'''simple docstring'''
lowercase_ : Union[str, Any] = arr.split("," )
def lowerCAmelCase__ ( ... | 620 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 620 | 1 |
'''simple docstring'''
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
UpperCamelCase__ = (
'This metric will be removed from the library s... | 620 |
'''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... | 620 | 1 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.dat... | 620 |
'''simple docstring'''
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
UpperCamelCase__ = loggin... | 620 | 1 |
'''simple docstring'''
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from tr... | 620 |
'''simple docstring'''
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, requi... | 620 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase__ = {
'configuration_gpt_neo': ['GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoConfig', 'GPTNeoOnnxConfig'],
}
try:
if no... | 620 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
)
| 620 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
# See all BioGPT models at ... | 620 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase = 100 ):
"""simple docstring"""
lowercase_ : Dict = n * (n + 1) * (2 * n + 1) / 6
lowercase_ : int = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
i... | 620 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 620 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
i... | 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 620 |
'''simple docstring'''
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
f... | 620 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase__ = {
'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
'tokenization_mvp'... | 620 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ =... | 620 | 1 |
'''simple docstring'''
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForCon... | 620 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
UpperCamelCase__ = False
try:
UpperCamelC... | 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Any = int(_UpperCamelCase )
if n_element < 1:
lowercase_ : List[str] = ValueError("a should be a positive number" )
rais... | 620 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ = {
'configuration_funnel': ['FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Funn... | 620 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_... | 620 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ = {
'configuration_layoutlmv3': [
'LAYOUT... | 620 | 1 |
'''simple docstring'''
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
UpperCamelCa... | 620 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffus... | 620 | 1 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _UpperCAmelCase ( unittest.TestCase ):
def lowerCAmelCase__ ( self : List[Any] ):
'''simple docstring'''
lowercase_ ... | 620 |
'''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, CLIPTextModel, CLIPTokenizer
... | 620 | 1 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_t... | 620 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Optional[int] = 2
lowercase_ : Tuple = []
while i * i <= n:
if n % i:
i += 1
... | 620 | 1 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase=None , _U... | 620 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class _UpperCAmelCase ( nn.Module ):
__lowerCamelCase: int
__lowerCamelCase: jnp.dtype = jnp.floataa
def lowerCAmelCase__ ( self : Optional[Any] ):
... | 620 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _UpperCAmelCase ( snake_ca... | 620 |
'''simple docstring'''
UpperCamelCase__ = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 1000000,
"gigajoule": 1000000000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 3600000,
"newtonmeter": 1.0,
"calorie_nutr": 4186.8,
"kilocalorie_nutr": 4186800.00,
... | 620 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _UpperCAmelCase ( snake_case ):
__lowerCamelCase: Optional[int] = ['image_processor', 'tokenizer']
__lowerCamelCase: Dict ... | 620 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _UpperCAmelCase ( unittest.TestCase ):
__lowerCame... | 620 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
i... | 620 |
'''simple docstring'''
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
UpperCamelCase__ = ['small', 'medium', 'large']
UpperCamelCase__ = 'lm_head.decoder.weight'
UpperCamelCase__ = 'lm_head.weight'
def __SCREAMING_SNAKE_CASE ( _UpperCamelC... | 620 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class _UpperCAmelCase ( snake_case ):
... | 620 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 620 | 1 |
'''simple docstring'''
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_avai... | 620 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
... | 620 | 1 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def ... | 620 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 620 | 1 |
'''simple docstring'''
UpperCamelCase__ = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadM... | 620 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 620 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IM... | 620 |
'''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... | 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
if number > 0:
raise ValueError("input must be a negative integer" )
lowercase_ : int = len(bin(_UpperCamelCase )[3:] )
lowercase_ : Any ... | 620 |
'''simple docstring'''
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
UpperCamelCase__ = loggin... | 620 | 1 |
'''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_gpu,... | 620 |
'''simple docstring'''
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, requi... | 620 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
... | 620 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
)
| 620 | 1 |
'''simple docstring'''
from typing import Any
class _UpperCAmelCase :
def __init__( self : str , a : Any ):
'''simple docstring'''
lowercase_ : str = data
lowercase_ : Optional[Any] = None
clas... | 620 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase = 100 ):
"""simple docstring"""
lowercase_ : Dict = n * (n + 1) * (2 * n + 1) / 6
lowercase_ : int = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
i... | 620 | 1 |
'''simple docstring'''
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
UpperCamelCase__ = Lock()
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , ... | 620 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
i... | 620 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class _UpperCAmelCase :
def __init__( self : List[Any] , a : Collection[float] | None = None ):
'''simple... | 620 |
'''simple docstring'''
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
f... | 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Any = []
lowercase_ : Optional[int] = set({"(", "[", "{"} )
lowercase_ : List[Any] = set({")", "]", "}"} )
... | 620 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ =... | 620 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from datasets import load_dataset
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, pr... | 620 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
UpperCamelCase__ = False
try:
UpperCamelC... | 620 | 1 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
UpperCamelCase__ = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
UpperCamelCase__ = requests.ge... | 620 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ = {
'configuration_funnel': ['FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Funn... | 620 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
Roberta... | 620 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ = {
'configuration_layoutlmv3': [
'LAYOUT... | 620 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ = {
'configuration_electra': ['ELECTRA_PRETRAINED_C... | 620 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffus... | 620 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {'vocab_file':... | 620 |
'''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, CLIPTextModel, CLIPTokenizer
... | 620 | 1 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
Channel... | 620 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Optional[int] = 2
lowercase_ : Tuple = []
while i * i <= n:
if n % i:
i += 1
... | 620 | 1 |
'''simple docstring'''
from __future__ import annotations
import time
UpperCamelCase__ = list[tuple[int, int]]
UpperCamelCase__ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, ... | 620 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class _UpperCAmelCase ( nn.Module ):
__lowerCamelCase: int
__lowerCamelCase: jnp.dtype = jnp.floataa
def lowerCAmelCase__ ( self : Optional[Any] ):
... | 620 | 1 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _UpperCAmelCase ( snake_case ):
__lowerCamelCase: List[Any] = ['image_processor', 'tokenizer']
__lowerCamelCase: Optional[Any] = 'Auto... | 620 |
'''simple docstring'''
UpperCamelCase__ = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 1000000,
"gigajoule": 1000000000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 3600000,
"newtonmeter": 1.0,
"calorie_nutr": 4186.8,
"kilocalorie_nutr": 4186800.00,
... | 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Union[str, Any] = set()
# edges = list of graph's edges
lowercase_ : Optional[Any] = get_edges(_UpperCamelCase )
# While there a... | 620 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _UpperCAmelCase ( unittest.TestCase ):
__lowerCame... | 620 | 1 |
'''simple docstring'''
import argparse
import json
import subprocess
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Tuple = []
lowercase_ : int = (
F"""curl -H \"Accept: appl... | 620 |
'''simple docstring'''
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
UpperCamelCase__ = ['small', 'medium', 'large']
UpperCamelCase__ = 'lm_head.decoder.weight'
UpperCamelCase__ = 'lm_head.weight'
def __SCREAMING_SNAKE_CASE ( _UpperCamelC... | 620 | 1 |
'''simple docstring'''
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, requi... | 620 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 620 | 1 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Dict = {
"... | 620 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
... | 620 | 1 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
lowercase_ : list[list[int]] = []
lowercase_ : list[int] = []
lowercase_ : str... | 620 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 620 | 1 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _UpperCAmelCase :
def __init__( self : Tuple , a : Any , a : int , a : List[str] , a : List[str] , a : int , a : Union[str, Any]=0.2 , a : ... | 620 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 620 | 1 |
'''simple docstring'''
class _UpperCAmelCase : # Public class to implement a graph
def __init__( self : Tuple , a : int , a : int , a : list[list[bool]] ):
'''simple docstring'''
lowercase_ : Tuple = row
... | 620 |
'''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... | 620 | 1 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
if len(_UpperCamelCase ) == 0:
return False
lowercase_ : Optional[int] = len(_UpperCamelCase ) // 2... | 620 |
'''simple docstring'''
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
UpperCamelCase__ = loggin... | 620 | 1 |
'''simple docstring'''
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
UpperCamelCase__ = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
UpperCamelCase__ = typing.Union[np.floataa, int, float] # noqa: UP007
de... | 620 |
'''simple docstring'''
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, requi... | 620 | 1 |
'''simple docstring'''
import qiskit
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase = 2 ):
"""simple docstring"""
lowercase_ : Any = qubits
# Using Aer's simulator
lowercase_ : List[str] = qiskit.Aer.get_backend("aer_simulator" )
# ... | 620 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
)
| 620 | 1 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/go... | 620 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase = 100 ):
"""simple docstring"""
lowercase_ : Dict = n * (n + 1) * (2 * n + 1) / 6
lowercase_ : int = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
i... | 620 | 1 |
'''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_a... | 620 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
i... | 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( ):
"""simple docstring"""
for n in range(1 , 100_0000 ):
yield n * (n + 1) // 2
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Dict = 1
lowe... | 620 |
'''simple docstring'''
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
f... | 620 | 1 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
UpperCamelCase__ = False
try:
UpperCamelC... | 620 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ =... | 620 | 1 |
'''simple docstring'''
import random
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
lowercase_ , lowercase_ , lowercase_ : List[Any] = [], [], []
for element in data:
if element < pivot:
less... | 620 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
UpperCamelCase__ = False
try:
UpperCamelC... | 620 | 1 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
UpperCamelCase__ = {'UserAgent': UserAgent().random}
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
... | 620 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ = {
'configuration_funnel': ['FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Funn... | 620 | 1 |
'''simple docstring'''
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobert... | 620 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ = {
'configuration_layoutlmv3': [
'LAYOUT... | 620 | 1 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Con... | 620 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffus... | 620 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase__ = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
}
... | 620 |
'''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, CLIPTextModel, CLIPTokenizer
... | 620 | 1 |
'''simple docstring'''
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class ... | 620 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Optional[int] = 2
lowercase_ : Tuple = []
while i * i <= n:
if n % i:
i += 1
... | 620 | 1 |
'''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
UpperCamelCase__ = logging.ge... | 620 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class _UpperCAmelCase ( nn.Module ):
__lowerCamelCase: int
__lowerCamelCase: jnp.dtype = jnp.floataa
def lowerCAmelCase__ ( self : Optional[Any] ):
... | 620 | 1 |
'''simple docstring'''
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
UpperCamelCase__ = Mapping[str, np.ndarray]
UpperCamelCase__ = Mapping[str, Any] # Is a nested d... | 620 |
'''simple docstring'''
UpperCamelCase__ = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 1000000,
"gigajoule": 1000000000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 3600000,
"newtonmeter": 1.0,
"calorie_nutr": 4186.8,
"kilocalorie_nutr": 4186800.00,
... | 620 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
... | 620 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _UpperCAmelCase ( unittest.TestCase ):
__lowerCame... | 620 | 1 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 620 |
'''simple docstring'''
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
UpperCamelCase__ = ['small', 'medium', 'large']
UpperCamelCase__ = 'lm_head.decoder.weight'
UpperCamelCase__ = 'lm_head.weight'
def __SCREAMING_SNAKE_CASE ( _UpperCamelC... | 620 | 1 |
'''simple docstring'''
import numpy as np
from PIL import Image
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Optional[int] = np.array(_UpperCamelCase )
if arr.shape[0] != arr.s... | 620 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 620 | 1 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTo... | 620 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/config.json',
}
... | 620 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training... | 620 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 620 | 1 |
'''simple docstring'''
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAmelCase ( snake_case , snake_case ):
@register_to_config
def __init__( self : Dict , *,
... | 620 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 620 | 1 |
'''simple docstring'''
from typing import List
import numpy as np
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
lowercase_ : Optional[int] = {key: len(_UpperCamelCase ) for key, value in gen_kwargs.items() if isinstance(_UpperCamelCase ... | 620 |
'''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... | 620 | 1 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, ... | 620 |
'''simple docstring'''
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
UpperCamelCase__ = loggin... | 620 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import DistilBertConfig, 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 Mo... | 620 |
'''simple docstring'''
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, requi... | 620 | 1 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase = 50 ):
"""simple docstring"""
lowercase_ : int = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_... | 620 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'The `inpainting.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionInpaintPipeline` instead.'
)
| 620 | 1 |
'''simple docstring'''
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
"""simple docstring"""
if not nums:
return 0
lowercase_ : List[Any] = nums[0]
lowercase_ : int = 0
for num in nums[1:]:
... | 620 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase = 100 ):
"""simple docstring"""
lowercase_ : Dict = n * (n + 1) * (2 * n + 1) / 6
lowercase_ : int = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
i... | 620 | 1 |
'''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 transformers... | 620 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
i... | 620 | 1 |
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