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 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 (
... | 63 |
"""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 | 1 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:... | 63 |
"""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 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_u... | 63 |
"""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 | 1 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/blob/main/co... | 63 |
"""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 | 1 |
"""simple docstring"""
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
... | 63 |
"""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 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
"configuration_blenderbot": [
... | 63 |
"""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 | 1 |
"""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 |
"""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 | 1 |
"""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 |
"""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 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=__snake_case )
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
# `task` is no... | 63 |
"""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 | 1 |
"""simple docstring"""
from math import asin, atan, cos, radians, sin, sqrt, tan
lowercase__ = 637_8137.0
lowercase__ = 635_6752.31_4245
lowercase__ = 6378137
def __magic_name__ ( _lowerCamelCase : float , _lowerCamelCase : float , _lowerCamelC... | 63 |
"""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 | 1 |
"""simple docstring"""
class SCREAMING_SNAKE_CASE__ :
def __init__(self ):
'''simple docstring'''
__a : Tuple = {}
def lowerCAmelCase__(self ):
'''simple docstring'''
... | 63 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def __init__(self , _lowercase , _lowercase ):
'''simple docstring'''
super().__init__(... | 63 | 1 |
"""simple docstring"""
from __future__ import annotations
lowercase__ = list[list[int]]
# assigning initial values to the grid
lowercase__ = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0,... | 63 |
"""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 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {"configuration_reformer": ["REFORMER_PRETRAINED_CONFIG_... | 63 |
"""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 | 1 |
"""simple docstring"""
from __future__ import annotations
lowercase__ = "Muhammad Umer Farooq"
lowercase__ = "MIT"
lowercase__ = "1.0.0"
lowercase__ = "Muhammad Umer Farooq"
lowercase__ = "contact@muhammadumerfarooq.me"
lowercase__ = "Alpha"
import re
from html... | 63 |
"""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 | 1 |
"""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 ... | 63 |
"""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 | 1 |
"""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
from trans... | 63 |
"""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 | 1 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJob... | 63 |
"""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 | 1 |
"""simple docstring"""
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 ... | 63 |
"""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 | 1 |
"""simple docstring"""
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_t... | 63 |
"""simple docstring"""
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : float ):
return round(float(moles / volume ) * nfactor )
def __magic_name__ ( _lowerCamelCase : float , _lowerC... | 63 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_fl... | 63 |
"""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 | 1 |
"""simple docstring"""
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( __snake_case ... | 63 |
"""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 | 1 |
"""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 ... | 63 |
"""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 | 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 transformer... | 63 |
"""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 | 1 |
"""simple docstring"""
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# ... | 63 |
"""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 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class SCREAMING_SNAKE_CASE__ :
_lowerCAmelCase = 42 # [batch_size x 3]
_lowerCAmelCase = 42 # [batch_size x 3]
_lowerCAmel... | 63 |
"""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 | 1 |
"""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... | 63 |
"""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 | 1 |
"""simple docstring"""
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tok... | 63 |
"""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 | 1 |
"""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... | 63 |
"""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 | 1 |
"""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... | 63 |
"""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 | 1 |
"""simple docstring"""
from __future__ import annotations
lowercase__ = list[tuple[int, int]]
lowercase__ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0, 0, 0, ... | 63 |
"""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 | 1 |
"""simple docstring"""
class SCREAMING_SNAKE_CASE__ :
def __init__(self ):
'''simple docstring'''
__a : dict[str, TrieNode] = {} # Mapping from char to TrieNode
__a : List[Any] = False
d... | 63 |
"""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 | 1 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class SCREAMING_SNAKE_CASE__ ... | 63 |
"""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 | 1 |
"""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"],
... | 63 |
"""simple docstring"""
import torch
from diffusers import DiffusionPipeline
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
def __init__(self , _lowercase , _lowercase ):
'''simple docstring'''
super().__init__(... | 63 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
lowercase__ = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control... | 63 |
"""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 | 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_retribert import RetriBertTokenizer
lowercase__ = logging.get_log... | 63 |
"""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 | 1 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowercase__ = input("Enter image url: ").strip()
print(f'Downloading image from {url} ...')
lowercase__ = BeautifulSoup(requests.get(url).content, "html.parse... | 63 |
"""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 | 1 |
"""simple docstring"""
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
... | 63 |
"""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 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.... | 63 |
"""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 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowercase__ = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
... | 63 |
"""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 | 1 |
"""simple docstring"""
from __future__ import annotations
def __magic_name__ ( _lowerCamelCase : Tuple ):
__a : List[str] = str(SCREAMING_SNAKE_CASE_ )
return n == n[::-1]
def __magic_name__ ( _lowerCamelCase : Optional... | 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 collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"bert-base-uncased": ... | 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 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,
MusicgenForConditionalGeneration,
M... | 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"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_comm... | 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 argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
lowercase__ = logging.get_logger(__name__)
def __magic_name__ ( _lower... | 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 typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
"configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"],
"processing_git": ["GitProcessor"],
... | 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 os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {"vocab_fi... | 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 dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
# TODO Update this
lowercase__ = {
"facebook/esm-1b": "https:... | 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 argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __magic_name__ ( _lowerCamelCase : List[str] , _lowerC... | 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 os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {'vocab_file': 'voc... | 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 json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercas... | 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 logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
lowercase__ = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ ( __snake_case ):
... | 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"""
from __future__ import annotations
def __magic_name__ ( _lowerCamelCase : Any ):
__a : Optional[int] = [True] * limit
__a : int = False
__a : Any = False
__a : int = ... | 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 darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
lowercase__ : List[str] = {
"n_samples": 64,
"horizon": 32,
"num_inference_steps": 20,
"n_guide_steps": 2, # can set to 0 for faster sampling, do... | 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 .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError("To use the rich extension, install rich with `pip install rich`") | 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 argparse
import struct
import unittest
class SCREAMING_SNAKE_CASE__ :
def __init__(self , _lowercase ):
'''simple docstring'''
__a : str = data
# Initialize hash va... | 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 ...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... | 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"""
def __magic_name__ ( _lowerCamelCase : Union[str, Any] , _lowerCamelCase : List[str] ):
print("""\nThe shortest path matrix using Floyd Warshall algorithm\n""" )
for i in range(_lowerCamelCase ):
for j in range(_lowerCa... | 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 torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ):
_lowerCAmelCase = (DDPMParallelScheduler,)
def lowerCAmelCase__(se... | 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"""
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def __magic_name__ ( _lowerCamelCase : Any ):
__a : Tuple = [
"""encoder.version""",
... | 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 collections.abc import Iterable
from typing import Any
class SCREAMING_SNAKE_CASE__ :
def __init__(self , _lowercase = None ):
'''simple docstring'''
__a : Optional[Any] = value
... | 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 unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_i... | 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 functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"asapp/sew-d-tiny-100k": "https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main... | 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 re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokeniz... | 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 argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
loggi... | 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 tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,... | 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"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ = {
"configuration_rag": ["RagConfig"],
"retrieval_rag": ["RagRetriever"],
"tokenization_rag": ["RagTokenizer"... | 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 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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
... | 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 itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizer... | 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 shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProc... | 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 diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class SCREAMING_SNAKE_CASE__ :
pass
| 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 random import randint
from tempfile import TemporaryFile
import numpy as np
def __magic_name__ ( _lowerCamelCase : Optional[int] , _lowerCamelCase : Optional[Any] , _lowerCamelCase : Union[str, Any] ):
__a : List[str] ... | 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"""
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__ ... | 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 datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transfor... | 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"""
# 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... | 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 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... | 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
import sys
lowercase__ = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoMode... | 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 os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import... | 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 os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer... | 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 __future__ import annotations
def __magic_name__ ( _lowerCamelCase : list ):
if not nums:
raise ValueError("""List is empty""" )
return sum(_lowerCamelCase ) / len(_lowerCamelCase )
if __name__ ==... | 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 copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils ... | 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"""
import argparse
import os
import re
lowercase__ = "src/diffusers"
# Pattern that looks at the indentation in a line.
lowercase__ = re.compile(R"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
lowercase__ = re.compile(R"^\s*\"([^\"]+)... | 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"""
def __magic_name__ ( _lowerCamelCase : int = 4_0_0_0_0_0_0 ):
__a : List[Any] = [0, 1]
__a : Optional[Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] >... | 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 importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
lowercase__ = importlib.util.find_spec("s3fs") is not None
if _has_safs:
... | 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 ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependency... | 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 collections.abc import Sequence
def __magic_name__ ( _lowerCamelCase : Dict = None ):
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__a : Tuple = nums[0]
... | 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 os
from distutils.util import strtobool
def __magic_name__ ( _lowerCamelCase : str , _lowerCamelCase : Optional[Any] ):
for e in env_keys:
__a : Optional[Any] = int(os.environ.get(lowercase__ , -1 ) )
... | 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"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
'configuration_bridgetower': [
'BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BridgeTowerConfig... | 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"""
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...tes... | 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"""
class SCREAMING_SNAKE_CASE__ :
def __init__(self , _lowercase , _lowercase=None , _lowercase=None ):
'''simple docstring'''
__a : Union[str, Any] = data
__a : str ... | 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 : int , _lowerCamelCase : int ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 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 logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from... | 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 argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_confi... | 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 math
class SCREAMING_SNAKE_CASE__ :
def lowerCAmelCase__(self , _lowercase , _lowercase ):
'''simple docstring'''
__a : List[Any] = 0.0
__a : Dict ... | 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"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"microsoft/swinv2-tiny-patch4-window8-256": (
"https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/... | 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 argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_... | 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 TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conve... | 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"""
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : int ):
return number | (1 << position)
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : int ):
return number & ~(1 << position... | 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 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__ = ... | 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 json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from .... | 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 collections
import inspect
import unittest
from transformers import FocalNetConfig
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 ...t... | 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 |
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