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"""
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPMo... | 624 |
"""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,
... | 624 | 1 |
"""simple docstring"""
import gc
import threading
import time
import psutil
import torch
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Optional[int] ) -> List[str]:
_UpperCamelCase : Dict = psutil.Process()
_Upp... | 624 |
"""simple docstring"""
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 624 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class __SCREAMING_SNAKE_CASE ( unittest.TestC... | 624 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> str:
"""simple docstring"""
if number > 0:
raise ValueError("input must be a negative integer" )
_UpperCamelCase : int = len(bin(lowercase_ )[3:] )
_Upper... | 624 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 1 |
"""simple docstring"""
from itertools import product
def lowercase__ ( lowercase_ ,lowercase_ ) -> list[int]:
"""simple docstring"""
_UpperCamelCase : Optional[Any] = sides_number
_UpperCamelCase : Optional[Any] = max_face_... | 624 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging... | 624 |
"""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_... | 624 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,) -> tuple:
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("You cannot supply mo... | 624 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
... | 624 |
"""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
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 1 |
"""simple docstring"""
import math
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0,... | 624 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 1 |
"""simple docstring"""
from __future__ import annotations
lowerCamelCase__ = 1.6021E-19 # units = C
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,) -> tuple[str, float]:
"""simple docstring"""
if (conductivity, electron_conc, mobility).count(0 ... | 624 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 1 |
"""simple docstring"""
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Nest... | 624 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
... | 624 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ = None ,lowercase_ = None ,lower... | 624 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 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... | 624 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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... | 624 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 624 | 1 |
"""simple docstring"""
import math
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
assert isinstance(lowercase_ ,lowercase_ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
... | 624 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from tran... | 624 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 1 |
"""simple docstring"""
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("dataset_size" ,[None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize("input_in_memory_max_size" ,["default", 0, 100 * 2**20, 900 * 2**20] )
def ... | 624 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
Diffu... | 624 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 1 |
"""simple docstring"""
from math import pi, sqrt
def lowercase__ ( lowercase_ ) -> float:
"""simple docstring"""
if num <= 0:
raise ValueError("math domain error" )
if num > 171.5:
raise OverflowError("math range error" )
... | 624 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 1 |
"""simple docstring"""
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
lowerCamelCase__ = HfArgumentParser(InitializationArguments)
lowerCamelCase__ = parser.parse_args()
# Load codeparrot toke... | 624 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 | 1 |
"""simple docstring"""
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> List[str]:
"""simple docstring"""
_UpperCamelCase : Union[str, Any] = {
... | 624 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 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,
DDIMSchedul... | 624 |
"""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,
... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ = "The quick brown fox jumps over the lazy dog" ,) -> bool:
"""simple docstring"""
_UpperCamelCase : Optional[int] = set()
# Replace all the whitespace in our sentence
_UpperCamelCase : ... | 624 |
"""simple docstring"""
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 624 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __SCREAMING_SNAKE_CASE ( unittest.Tes... | 624 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 1 |
"""simple docstring"""
# 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-... | 624 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 1 |
"""simple docstring"""
import functools
def lowercase__ ( lowercase_ ,lowercase_ ) -> int:
"""simple docstring"""
_UpperCamelCase : List[str] = len(lowercase_ )
_UpperCamelCase : int = len(lowercase_ )
@fun... | 624 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( ) -> str:
"""simple docstring"""
for n in range(1 ,1_000_000 ):
yield n * (n + 1) // 2
def lowercase__ ( lowercase_ ) -> Dict:
"""simple docstring"""
_UpperCamelC... | 624 |
"""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_... | 624 | 1 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowerCamelCase__ = numpy.array([0, 0])
lowerCamelCase__ = numpy.array([0.5, 0.8_6_6_0_2_5_4])
lowerCamelCase__ = numpy.array([1, 0])
lowerC... | 624 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 1 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowerCamelCase__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# Th... | 624 |
"""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
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 1 |
"""simple docstring"""
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase__ = 50_0000
lowerCamelCase__ , lowerCamelCase__ = os.path.split(__file__)
lowerCamelCase__ = os.path.join(RESULTS_BASEP... | 624 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> str:
"""simple docstring"""
_UpperCamelCase : Tuple = int(lowercase_ )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowercase_ )
_UpperCame... | 624 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 1 |
"""simple docstring"""
# using dfs for finding eulerian path traversal
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=None ) -> str:
"""simple docstring"""
_UpperCamelCase : Union[str, Any] = (path or []) + [u]
for v in... | 624 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 1 |
"""simple docstring"""
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokeniz... | 624 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 1 |
"""simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple d... | 624 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
lowerCamelCase__ = logging.get_logger(__nam... | 624 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 1 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 624 | 1 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Union[str, Any] ) -> List[str]:
_UpperCamelCase : Optional[Any] = ... | 624 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 1 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowercase__ ( lowercase_ ) -> Any:
"""simple docstring"""
if (
(cp >= 0X4e00 and cp <= 0X9fff)
or (cp ... | 624 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 1 |
"""simple docstring"""
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
lower... | 624 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ = 200 ) -> int:
"""simple docstring"""
_UpperCamelCase : Tuple = [1, 2, 5, 10, 20, 50, 100, 200]
_UpperCamelCase : str = [0] * (pence + 1)
_UpperCamelCase : int ... | 624 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, tor... | 624 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.te... | 624 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 | 1 |
"""simple docstring"""
import math
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
if not isinstance(lowercase_ ,lowercase_ ):
_UpperCamelCase : Tuple = F'''Input value of [number={number}] must be an integer'''
... | 624 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 1 |
"""simple docstring"""
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase__ (... | 624 |
"""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,
... | 624 | 1 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 |
"""simple docstring"""
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 624 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 1 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
lowerCamelCase__ = tuple[int, int]
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Optional[Any] , __a : set[int] , __a : ... | 624 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 1 |
"""simple docstring"""
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
lowerCamelCase__ = [
"word_embeddin... | 624 |
"""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_... | 624 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.... | 624 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = "▁"
... | 624 |
"""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
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ = 1_000_000 ) -> int:
"""simple docstring"""
_UpperCamelCase : Optional[int] = set(range(3 ,lowercase_ ,2 ) )
primes.add(2 )
for p in range(3 ,lowercase_ ,2 ):
... | 624 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 1 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_availa... | 624 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 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.tra... | 624 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"vinvino02/glpn-kitti": "https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json",
# See all GLPN models ... | 624 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 1 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 1 |
"""simple docstring"""
import argparse
import os
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
from accel... | 624 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 624 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 624 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"microsoft/focalnet-ti... | 624 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 1 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
f... | 624 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_token... | 624 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 1 |
"""simple docstring"""
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_=1_024 ,lowercase_=1_024 ,lowercase_=False ,**lower... | 624 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCamelCase__ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm": ["XLMTo... | 624 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : List[Any] , __a : int , __a : int , __a : float = 0 ) -> None:
_UpperCam... | 624 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 | 1 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
lowerCamelCase__ = True
except (ImportError, ModuleNotFoundError):
lowerCamelCase__ = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("punkt", quiet=True)
def lowercase__ ... | 624 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 1 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def lowercase__ ( lowercase_ = 8 ) -> str:
"""simple docstring"""
_UpperCamelCase : Any = asc... | 624 |
"""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,
... | 624 | 1 |
"""simple docstring"""
lowerCamelCase__ = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCamelCase__ = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
lowerCamelCase__ = {
0: "Sunday",
1: "Monday",
2: "Tuesday",
3: "Wednesday",
4: "Thursday",
5: "Friday",
6: "Saturday",
}
def ... | 624 |
"""simple docstring"""
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 624 | 1 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DP... | 624 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 1 |
"""simple docstring"""
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 ...... | 624 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 1 |
"""simple docstring"""
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_con... | 624 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.j... | 624 |
"""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_... | 624 | 1 |
"""simple docstring"""
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :List[Any] = CustomTokenizer
pass
| 624 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():
rais... | 624 |
"""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
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> int:
"""simple docstring"""
_UpperCamelCase : Optional[int] = abs(lowercase_ )
_UpperCamelCase : Union[str, Any] = 0
while n > 0:
res += n % 10
... | 624 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 1 |
"""simple docstring"""
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_h... | 624 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 1 |
"""simple docstring"""
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( self : List[Any] , __a : str ... | 624 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 1 |
"""simple docstring"""
import argparse
from collections import defaultdict
import yaml
lowerCamelCase__ = "docs/source/en/_toctree.yml"
def lowercase__ ( lowercase_ ) -> Any:
"""simple docstring"""
_UpperCamelCase : Any = defaultdict(lowe... | 624 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 1 |
"""simple docstring"""
def lowercase__ ( lowercase_ ,lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : List[Any] = ""
for i in table:
res += inp[i - 1]
return res
def lowercase__ ( lowercase... | 624 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowerCamelCase__ = "src/transformers"
# Matches is_xxx_available()
lowerCamelCase__ = re.compile(R"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase__ = re.compile(R"^_i... | 624 | 1 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
lowerCamelCase__ = (720, 1280) # Height, Width
lowerCamelCase__ = (0.4, 0.6) # if height or width lower than this scale, drop it.
lowerCamelCase__ ... | 624 |
"""simple docstring"""
import re
def lowercase__ ( lowercase_ ) -> bool:
"""simple docstring"""
_UpperCamelCase : List[Any] = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.se... | 624 | 1 |
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_tens... | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 624 | 0 |
def _A ( _lowercase ) -> Dict:
"""simple docstring"""
__UpperCamelCase = []
__UpperCamelCase = set({'(', '[', '{'} )
__UpperCamelCase = set({')', ']', '}'} )
__UpperCamelCase = {'{': '}', '[': ']', '(': ')'}
for i in range(len(_lowercase ) ):
... | 1 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( _UpperCamelCase ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ :Optional[Any] = ["image_processor", "tokenizer"]
... | 624 | 0 |
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import Tokeni... | 2 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "ResNetConfi... | 624 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
... | 3 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowerCamelCase__ = False
lowerCamelCase__ = True
lowerCamelCase__ = False
if __name__ == "__main__":
lowerCamelCas... | 624 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Any = {
'''configuration_blip_2''': [
'''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Blip2Config''',
... | 4 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowercase__ ( lowercase_ ) -> Tuple:
"""simple docstring"""
_UpperCamelCase : Optional[int] = [
... | 624 | 0 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class UpperCAmelCase_ ( _SCREAMING_SNAKE_CASE ):
... | 5 |
"""simple docstring"""
def lowercase__ ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
_UpperCamelCase : Optional[Any] = []
def generate(lowercase_ ,lowercase_ ... | 624 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'facebook/dpr-ctx_encoder-single-nq-base': (
'https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.js... | 6 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGenerat... | 624 | 0 |
"""simple docstring"""
import os
from distutils.util import strtobool
def _snake_case ( _snake_case : Tuple , _snake_case : str ) -> Any:
'''simple docstring'''
for e in env_keys:
_A = int(os.environ.get(_snake_case , -1 ) ... | 7 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_sched... | 624 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( __snake_case : int = 10_00 ) -> int:
__A : Tuple = -1
__A : Tuple = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
... | 8 |
"""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,
... | 624 | 0 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
SCREAMING_SNAKE_CASE__ = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the... | 9 |
"""simple docstring"""
import warnings
warnings.warn(
"memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: "
"`from accelerate import find_executable_batch_size` to avoid this warning.",
FutureWarning,
)
| 624 | 0 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
_lowerCAmelCase = (720, 1_280) # Height, Width
_lowerCAmelCase = (0.4, 0.6) # if height or width lower than this scale, drop it.
_lowerCAmelCase = 1 / 100
_lowerCAmelCase ... | 10 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_=5 ) -> List[Any]:
"""simple docstring"""
assert masked_input.count("<mask>" ) == 1
... | 624 | 0 |
'''simple docstring'''
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowerCAmelCase (... | 11 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
Stab... | 624 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class _snake_case ( unittest.TestCase ):
def lowe... | 12 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequ... | 624 | 0 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
A__ : Dict = logg... | 13 |
"""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_... | 624 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcesso... | 14 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ,lowercase_ ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase : List[str] = int(np.ceil((x_... | 624 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerBase, Tensor... | 15 |
"""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
lowerCamelCase__ = False
try:
lowerCamelC... | 624 | 0 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def __a ( A__ : str , A__ : List[Any]=None ):
SCREAMING_SNAKE_CASE = None
if token is not None:
SC... | 16 |
"""simple docstring"""
import numpy as np
def lowercase__ ( lowercase_ ,lowercase_ ,lowercase_ = 1e-12 ,lowercase_ = 100 ,) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.shape(lowercase_ )[0] == np.shape(lowercase_ )[1]
# Ensure pr... | 624 | 0 |
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase_ : str = logging.get_logger(__name__)
def ... | 17 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowerCamelCase__ = "examples/"
lowerCamelCase__ = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=... | 624 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import l... | 18 |
"""simple docstring"""
import random
from typing import Any
def lowercase__ ( lowercase_ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(lowercase_ ) ):
_UpperCamelCase : Dict = random.randint(0 ,len(lowercase_ ... | 624 | 0 |
"""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( ... | 19 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
... | 624 | 0 |
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