code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowercase__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( UpperCamelCase_ ):
def __init__(self , *_lowercase , ... | 717 |
"""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 ... | 63 | 0 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class SCREAMING_SNAKE_CASE__ ( nn.Module ):
_lowerCAmelCase = 4_2
_lowerCAmelCase = jnp.floataa
def lowerCAmelCase__(self ):
... | 718 |
"""simple docstring"""
import os
def __magic_name__ ( _lowerCamelCase : Dict ):
__a : List[str] = len(grid[0] )
__a : int = len(_lowerCamelCase )
__a : Tuple = 0
__a : List[Any] = ... | 63 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowercase__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailabl... | 719 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class SCREAMING_SNAKE_CASE_... | 63 | 0 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddin... | 720 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, req... | 63 | 0 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def __magic_name__ ( _lowerCamelCase : Optional[int] ):
__a : Tuple = args.pruning_method
... | 721 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : str = 0
__... | 63 | 0 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def __magic_name__ ( _lowerCamelCase : Dict ):
__a : Any =... | 700 |
"""simple docstring"""
from manim import *
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : List[str] = Rectangle(height=0.5 , width=0.5 )
... | 63 | 0 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(">=", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from t... | 701 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def __magic_name__ ( _lowerCamelCase : float , _lowerC... | 63 | 0 |
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowercase__ = TypeVar("KT")
lowercase__ = TypeVar("VT")
class SCREAMING_SNAKE_CASE__ ( Generic[KT, VT] ):
def __init__(self , _lowercase = "root" , ... | 702 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : list[int] ):
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__a : Any = sum(_lowerCamelCase ) / len(_lowerCamelCase ) # C... | 63 | 0 |
"""simple docstring"""
import copy
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
from ..auto import CONFIG_MAPPING
lowercase__ = ... | 703 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def __magic_name__ ( _lowerCamelCase : np.ndarray , _lowerCamelCase : float ):
# For applying gaussian function for each element in matrix.
__a : int = math.... | 63 | 0 |
"""simple docstring"""
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin... | 704 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __magic_name__ ( ):
__a : Dict = {
"""repo_name""": ["""test_repo1""", """test_rep... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : Tuple = 1_0_0 ):
__a : Optional[Any] = 0
__a : int = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
r... | 705 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowercase__ = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}
... | 63 | 0 |
"""simple docstring"""
from __future__ import annotations
def __magic_name__ ( _lowerCamelCase : Dict , _lowerCamelCase : int , _lowerCamelCase : str , _lowerCamelCase : str ):
if (direction == 1 and array[indexa] > array[indexa]) or (
... | 706 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowercase__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( __... | 63 | 0 |
"""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_comm... | 707 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : Optional[Any]=False ):
__a : Dict = Omeg... | 63 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class SCREAMING_SNAKE_CASE__ ( lowerCAmelCase__ ... | 708 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_... | 63 | 0 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -... | 709 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"microsoft/unispeech-large-1500h-cv": (
"https://huggingface.co/microsoft/... | 63 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def lowerCAmelCase__(self ):
... | 710 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availabl... | 63 | 0 |
"""simple docstring"""
from math import asin, atan, cos, radians, sin, sqrt, tan
lowercase__ = 6378137.0
lowercase__ = 6356752.314245
lowercase__ = 6378137
def __magic_name__ ( _lowerCamelCase : List[Any] , _lowerCamelCase : Optional[Any] , _lowerCamelCase ... | 711 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class SCRE... | 63 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm i... | 712 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers impo... | 63 | 0 |
"""simple docstring"""
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
... | 713 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils i... | 63 | 0 |
"""simple docstring"""
lowercase__ = {"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
lowercase__ = ["a", "b", "c", "d", "e"]
def __magic_name__ ( _lowerCamelCase : Optional[Any] , _lowerCamelCase : int , _lowerCamelCase : Dict ):
... | 714 |
"""simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
lowercase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str, requi... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : Optional[Any] ):
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def __magic_name__ ( _lowerCamelCase : List[Any] ):
__a : Union[str, Any] = 0
... | 715 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def __init__(self , _lowercase , _lowercase ):
'''simple docstring'''
super().__init__(... | 63 | 0 |
"""simple docstring"""
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension... | 716 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json",
# See all ViT M... | 63 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
en... | 717 |
"""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 ... | 63 | 0 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
lowercase__ = """us-east-1""" # defaults region
@dataclass
class SCREAMING_SNAKE_CASE__ :
_lowerCAmelCase = 4_2
_lowerCAmelCase = "arn:aws:iam::558105141721:role/sagemaker... | 718 |
"""simple docstring"""
import os
def __magic_name__ ( _lowerCamelCase : Dict ):
__a : List[str] = len(grid[0] )
__a : int = len(_lowerCamelCase )
__a : Tuple = 0
__a : List[Any] = ... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : Optional[Any] ):
__a : int = [0] * len(__a )
__a : Optional[int] = []
__a : List[str] = [1] * len(__a )
for values in graph.values():
... | 719 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class SCREAMING_SNAKE_CASE_... | 63 | 0 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def __magic_name__ ( _lowerCamelCase : float , _lowerCamelCase : float , _lowerCamelCase : int ):
__a : Any = x
__a : int = y
... | 720 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, req... | 63 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vis... | 721 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : str = 0
__... | 63 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
res... | 700 |
"""simple docstring"""
from manim import *
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : List[str] = Rectangle(height=0.5 , width=0.5 )
... | 63 | 0 |
"""simple docstring"""
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
lowercase__ = collections.namedtuple(... | 701 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def __magic_name__ ( _lowerCamelCase : float , _lowerC... | 63 | 0 |
from importlib import import_module
from .logging import get_logger
lowercase__ = get_logger(__name__)
class SCREAMING_SNAKE_CASE__ :
def __init__(self , _lowercase , _lowercase=None ):
'''simple docstring'''
... | 702 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : list[int] ):
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__a : Any = sum(_lowerCamelCase ) / len(_lowerCamelCase ) # C... | 63 | 0 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
lowercase__ = logging.getLogger()
@unittest.skip("Temp... | 703 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def __magic_name__ ( _lowerCamelCase : np.ndarray , _lowerCamelCase : float ):
# For applying gaussian function for each element in matrix.
__a : int = math.... | 63 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowerca... | 704 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __magic_name__ ( ):
__a : Dict = {
"""repo_name""": ["""test_repo1""", """test_rep... | 63 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_c... | 705 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowercase__ = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}
... | 63 | 0 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add_argu... | 706 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowercase__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( __... | 63 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
lowercase__ = tuple[int, int]
class SCREAMING_SNAKE_CASE__ :
def __init__(self , _lowercase , _lowercase ):
'''simple ... | 707 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : Optional[Any]=False ):
__a : Dict = Omeg... | 63 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class SCREAMING_SNAKE_CASE__ ( __A ... | 708 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_... | 63 | 0 |
"""simple docstring"""
import argparse
from .config import config_command_parser
from .config_args import default_config_file, load_config_from_file # noqa: F401
from .default import default_command_parser
from .update import update_command_parser
def __magic_name__ ( _lowerCamel... | 709 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"microsoft/unispeech-large-1500h-cv": (
"https://huggingface.co/microsoft/... | 63 | 0 |
"""simple docstring"""
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
... | 710 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availabl... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : Union[str, Any] , _lowerCamelCase : List[str] ):
while a != 0:
__a , __a : Any = b % a, a
return b
def __magic_name__ ( _lowerCamelCase : List[str] ... | 711 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class SCRE... | 63 | 0 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"kakaobrain/align... | 712 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers impo... | 63 | 0 |
"""simple docstring"""
import re
def __magic_name__ ( _lowerCamelCase : Optional[int] ):
__a : Tuple = 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.search(UpperCAm... | 713 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils i... | 63 | 0 |
"""simple docstring"""
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
Defau... | 714 |
"""simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
lowercase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str, requi... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : int ):
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input... | 715 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def __init__(self , _lowercase , _lowercase ):
'''simple docstring'''
super().__init__(... | 63 | 0 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingT... | 716 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json",
# See all ViT M... | 63 | 0 |
"""simple docstring"""
import math
def __magic_name__ ( _lowerCamelCase : int = 1_0_0 ):
__a : str = sum(i * i for i in range(1 , n + 1 ) )
__a : Tuple = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ... | 717 |
"""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 ... | 63 | 0 |
"""simple docstring"""
from __future__ import annotations
lowercase__ = []
def __magic_name__ ( _lowerCamelCase : list[list[int]] , _lowerCamelCase : int , _lowerCamelCase : int ):
for i in range(len(snake_case_ ) ):
if ... | 718 |
"""simple docstring"""
import os
def __magic_name__ ( _lowerCamelCase : Dict ):
__a : List[str] = len(grid[0] )
__a : int = len(_lowerCamelCase )
__a : Tuple = 0
__a : List[Any] = ... | 63 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 719 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class SCREAMING_SNAKE_CASE_... | 63 | 0 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
... | 720 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, req... | 63 | 0 |
"""simple docstring"""
from __future__ import annotations
def __magic_name__ ( _lowerCamelCase : list , _lowerCamelCase : int | None = None , _lowerCamelCase : int | None = None ):
if start is None:
__a : Union[str, Any] = ... | 721 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : str = 0
__... | 63 | 0 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
lowercase__ = logging.get_logger(__name__)
lowercase__ = O... | 700 |
"""simple docstring"""
from manim import *
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : List[str] = Rectangle(height=0.5 , width=0.5 )
... | 63 | 0 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transfo... | 701 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def __magic_name__ ( _lowerCamelCase : float , _lowerC... | 63 | 0 |
from __future__ import annotations
import math
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : int , _lowerCamelCase : bool , _lowerCamelCase : list[int] , _lowerCamelCase : float ):
if depth < 0:
rai... | 702 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : list[int] ):
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__a : Any = sum(_lowerCamelCase ) / len(_lowerCamelCase ) # C... | 63 | 0 |
"""simple docstring"""
lowercase__ = 9.8_0665
def __magic_name__ ( _lowerCamelCase : float , _lowerCamelCase : float , _lowerCamelCase : float = g ):
if fluid_density <= 0:
raise ValueError("""Impossible fluid density""" )
... | 703 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def __magic_name__ ( _lowerCamelCase : np.ndarray , _lowerCamelCase : float ):
# For applying gaussian function for each element in matrix.
__a : int = math.... | 63 | 0 |
"""simple docstring"""
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
lowercase__ = abspath(join(dirname(dirnam... | 704 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __magic_name__ ( ):
__a : Dict = {
"""repo_name""": ["""test_repo1""", """test_rep... | 63 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=__snake_case ):
_lowerCAmelCase = ["keras_nlp"]
def __init__(self , *_lowercase , **_lowercase ):
... | 705 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowercase__ = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}
... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : str , _lowerCamelCase : list[str] ):
__a : Tuple = """"""
for word_or_phrase in separated:
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
... | 706 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowercase__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( __... | 63 | 0 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
f... | 707 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : Optional[Any]=False ):
__a : Dict = Omeg... | 63 | 0 |
"""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 (
... | 708 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_... | 63 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig
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_configuration... | 709 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"microsoft/unispeech-large-1500h-cv": (
"https://huggingface.co/microsoft/... | 63 | 0 |
"""simple docstring"""
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_devi... | 710 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availabl... | 63 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/c... | 711 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class SCRE... | 63 | 0 |
"""simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowercase__ = 0b10_11_00_11_11_10_11_00_10_01_00_00... | 712 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers impo... | 63 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
f... | 713 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils i... | 63 | 0 |
"""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 transformer... | 714 |
"""simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
lowercase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str, requi... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : Any , _lowerCamelCase : List[str] ):
__a : List[str] = 0
__a : Tuple = len(_lowerCamelCase ) - 1
while left <= right:
# avoid divided by 0 dur... | 715 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def __init__(self , _lowercase , _lowercase ):
'''simple docstring'''
super().__init__(... | 63 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 716 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json",
# See all ViT M... | 63 | 0 |
"""simple docstring"""
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
lowercase__ = "\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems... | 717 |
"""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 ... | 63 | 0 |
"""simple docstring"""
lowercase__ = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def __magic_name__ ( ):
__a : Dict = input("""Enter message: """ )
__a : Union[str, Any] = input("""Enter key [alphanumeric]: """ )
__a : Optional[An... | 718 |
"""simple docstring"""
import os
def __magic_name__ ( _lowerCamelCase : Dict ):
__a : List[str] = len(grid[0] )
__a : int = len(_lowerCamelCase )
__a : Tuple = 0
__a : List[Any] = ... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : str , _lowerCamelCase : int ):
__a : list[list[str]] = [[] for _ in range(_lowerCamelCase )]
__a : Any = key - 1
if key <= 0:
raise ValueError... | 719 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class SCREAMING_SNAKE_CASE_... | 63 | 0 |
"""simple docstring"""
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
lowe... | 720 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, req... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( ):
__a : Union[str, Any] = [3_1, 2_8, 3_1, 3_0, 3_1, 3_0, 3_1, 3_1, 3_0, 3_1, 3_0, 3_1]
__a : List[Any] = 6
__a : List[Any] = 1
__a : Optional[Any] = 1_9_0_... | 721 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : str = 0
__... | 63 | 0 |
"""simple docstring"""
from __future__ import annotations
def __magic_name__ ( _lowerCamelCase : tuple[int, int] , _lowerCamelCase : int ):
__a : Tuple = position
__a : Any = [
(y + 1, x + 2),
(y - ... | 700 |
"""simple docstring"""
from manim import *
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : List[str] = Rectangle(height=0.5 , width=0.5 )
... | 63 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class SCREAMING_SNAKE_CASE__ :
_lowerCAmelCase = 4_2 # [batch_size x 3]
_lowerCAmelCase = 4_2 # [batch_size x 3]
_lowerCAm... | 701 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def __magic_name__ ( _lowerCamelCase : float , _lowerC... | 63 | 0 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
lowercase__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def __init__(self , *_lowercase , **_lowercase ... | 702 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : list[int] ):
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__a : Any = sum(_lowerCamelCase ) / len(_lowerCamelCase ) # C... | 63 | 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 tran... | 703 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def __magic_name__ ( _lowerCamelCase : np.ndarray , _lowerCamelCase : float ):
# For applying gaussian function for each element in matrix.
__a : int = math.... | 63 | 0 |
"""simple docstring"""
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
lowercase__ = "scheduler_config.json"
c... | 704 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __magic_name__ ( ):
__a : Dict = {
"""repo_name""": ["""test_repo1""", """test_rep... | 63 | 0 |
"""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... | 705 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowercase__ = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}
... | 63 | 0 |
"""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
... | 706 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowercase__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( __... | 63 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def __magic_name__ ( _lowerCamelCase : Sequence[float] , _lowerCamelCase : bool = False ):
if not arr:
return 0
__a : Optional[int] = 0 if allow_empty_subarrays ... | 707 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : Optional[Any]=False ):
__a : Dict = Omeg... | 63 | 0 |
"""simple docstring"""
from itertools import product
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : int ):
__a : Dict = sides_number
__a : Optional[Any] = max_face_number * dice_number
__a : str ... | 708 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_... | 63 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
f... | 709 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"microsoft/unispeech-large-1500h-cv": (
"https://huggingface.co/microsoft/... | 63 | 0 |
"""simple docstring"""
import argparse
import os
import platform
import numpy as np
import psutil
import torch
from accelerate import __version__ as version
from accelerate.commands.config import default_config_file, load_config_from_file
from ..utils import is_npu_available, is_xpu_available
... | 710 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availabl... | 63 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
f... | 711 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class SCRE... | 63 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch,... | 712 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers impo... | 63 | 0 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class SCRE... | 713 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils i... | 63 | 0 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddin... | 714 |
"""simple docstring"""
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
lowercase__ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str, requi... | 63 | 0 |
"""simple docstring"""
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class SCREAMING_SNAKE_CASE__ ( __snake_case... | 715 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def __init__(self , _lowercase , _lowercase ):
'''simple docstring'''
super().__init__(... | 63 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"microsoft/unispeech-large-1500h-cv": (
"https://huggingface.co/microsoft/... | 716 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"sayakpaul/vit-msn-base": "https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json",
# See all ViT M... | 63 | 0 |
"""simple docstring"""
class SCREAMING_SNAKE_CASE__ :
def __init__(self , _lowercase ):
'''simple docstring'''
__a : Optional[Any] = val
__a : Any = None
__a : Optional[Any] ... | 717 |
"""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 ... | 63 | 0 |
"""simple docstring"""
from __future__ import annotations
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : int ):
if partitions <= 0:
raise ValueError("""partitions must be a positive number!""" )
if partitions > number_o... | 718 |
"""simple docstring"""
import os
def __magic_name__ ( _lowerCamelCase : Dict ):
__a : List[str] = len(grid[0] )
__a : int = len(_lowerCamelCase )
__a : Tuple = 0
__a : List[Any] = ... | 63 | 0 |
"""simple docstring"""
from __future__ import annotations
import requests
lowercase__ = set(
"approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content... | 719 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class SCREAMING_SNAKE_CASE_... | 63 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
"configuration_xmod": [
"XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP",
"XmodConfig",
"XmodOnnxConfig",
],
}
... | 720 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, req... | 63 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
... | 721 |
"""simple docstring"""
import unittest
from knapsack import knapsack as k
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : str = 0
__... | 63 | 0 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def __magic_name__ ( _lowerCamelCase : np.ndarray , _lowerCamelCase : float ):
# For applying gaussian function for each element in matrix.
__a : int = math.... | 700 |
"""simple docstring"""
from manim import *
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def lowerCAmelCase__(self ):
'''simple docstring'''
__a : List[str] = Rectangle(height=0.5 , width=0.5 )
... | 63 | 0 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : float , _lowerCamelCase : list[float] ):
if discount_rate < 0:
raise ValueError("""Discount rate cannot be negative""" )
if not cash_flows:
raise ValueError("""Cash flow... | 701 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def __magic_name__ ( _lowerCamelCase : float , _lowerC... | 63 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
from .... | 702 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : list[int] ):
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
__a : Any = sum(_lowerCamelCase ) / len(_lowerCamelCase ) # C... | 63 | 0 |
"""simple docstring"""
import sys
from pathlib import Path
lowercase__ = Path(__file__).resolve().parents[3] / "src"
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io # noqa
import itertools # noqa
import json # noqa
import os # noqa
import unittest # noqa
... | 703 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def __magic_name__ ( _lowerCamelCase : np.ndarray , _lowerCamelCase : float ):
# For applying gaussian function for each element in matrix.
__a : int = math.... | 63 | 0 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
lowercase__ = True
except (ImportError, ModuleNotFoundError):
lowercase__ = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("punkt", quiet=True)
d... | 704 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __magic_name__ ( ):
__a : Dict = {
"""repo_name""": ["""test_repo1""", """test_rep... | 63 | 0 |
"""simple docstring"""
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
low... | 705 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowercase__ = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
}
... | 63 | 0 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
lowercase__ = {
"<": operator.lt,
"<=": operator.le,
"==": operator.eq,
"!=": operator.ne,
">=": operator.ge,
">": op... | 706 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowercase__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( __... | 63 | 0 |
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