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 |
|---|---|---|---|---|
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json'
),
}
... | 638 | from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipeline... | 638 | 1 |
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, ... | 638 | import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(__lowercase ) , 'Tatoeba direc... | 638 | 1 |
def __magic_name__( __UpperCAmelCase ) -> list:
'''simple docstring'''
_lowerCamelCase = [0] * len(__UpperCAmelCase )
for i in range(1 , len(__UpperCAmelCase ) ):
# use last results for better performance - dynamic programming
_lo... | 638 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_inf... | 638 | 1 |
import argparse
import json
import subprocess
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = []
_lowerCamelCase = (
F'curl -H "Accept: application/vnd.github+json" -H "Authoriz... | 638 | import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
logging,
)
... | 638 | 1 |
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,
rescale,
resize,
to_channel... | 638 | import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase ( __lowercase ):
'''simple docstring'''
def __init__( self , *A_ , **A_ ) -> None:
... | 638 | 1 |
import math
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = len(__UpperCAmelCase )
_lowerCamelCase = int(math.floor(math.sqrt(__UpperCAmelCase ) ) )
_lowerCamelCase = 0
... | 638 | import argparse
import json
import subprocess
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = []
_lowerCamelCase = (
F'curl -H "Accept: application/vnd.github+json" -H "Authoriz... | 638 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ = {
'configuration_electra': ['ELECTRA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Elec... | 638 | from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
requi... | 638 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
'shi-labs/nat-mini-in1k-224': 'https://huggingface.co/shi... | 638 | def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
_lowerCamelCase = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def __magic_name__... | 638 | 1 |
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 OptionalDependencyNotAvailable:
fr... | 638 | import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTokenizerFast,
... | 638 | 1 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from acc... | 638 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 638 | 1 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_m... | 638 | from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransformerConfig',
],
}
try:
... | 638 | 1 |
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_common import Onn... | 638 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils ... | 638 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
snake_case__ = {
'configuration_ernie': ['ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieConfig', 'ErnieOnnxConfig'],
}
try:
if not is_torch_availabl... | 638 | import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
snake_case__ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf(), gbe... | 638 | 1 |
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
return number | (1 << position)
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
return number & ~(1 << ... | 638 | import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcess... | 638 | 1 |
import os
def __magic_name__( __UpperCAmelCase = "matrix.txt" ) -> int:
'''simple docstring'''
with open(os.path.join(os.path.dirname(__UpperCAmelCase ) , __UpperCAmelCase ) ) as in_file:
_lowerCamelCase = in_file.read()
_lowerCamelCase ... | 638 | import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from transformers.model... | 638 | 1 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
snake_case__ = [
'Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'
' f... | 638 | def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> bool:
'''simple docstring'''
_lowerCamelCase = len(__UpperCAmelCase )
_lowerCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of z... | 638 | 1 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> Any:
'''simple docstring'''
... | 638 | from typing import List
import numpy as np
def __magic_name__( __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = {key: len(__UpperCAmelCase ) for key, value in gen_kwargs.items() if isinstance(__UpperCAmelCase , __UpperCAmelCase )}
if le... | 638 | 1 |
from __future__ import annotations
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> list[str]:
'''simple docstring'''
if partitions <= 0:
raise ValueError('''partitions must be a positive number!''' )
if partitions > number_of_bytes:
... | 638 | 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 ImageProcessingSavingTestMixin, prepare_image_inputs
... | 638 | 1 |
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class UpperCamelCase ( __lowercase ):
'''s... | 638 | import argparse
import json
from tqdm import tqdm
def __magic_name__( ) -> List[str]:
'''simple docstring'''
_lowerCamelCase = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'''--src_path''' , type=__UpperCAmelCase ... | 638 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
snake_case__ = logging.get_logger(__name__)
snake_case__ = {'vocab_f... | 638 | import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerF... | 638 | 1 |
class UpperCamelCase :
'''simple docstring'''
def __init__( self , A_ ) -> Optional[int]:
"""simple docstring"""
# we need a list not a string, so do something to change the type
_lowerCamelCase = arr.split(''',''' )
... | 638 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ = {
'configuration_whisper': ['WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Whis... | 638 | 1 |
import unittest
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_ima... | 638 | import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='%(message)s')
def __magic_name__( __UpperCAmelCase ) -> np.ndarray:
'''simple docstring'''
return input_array.reshape((input_array.size, 1) )
def... | 638 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
'google/bigbird-roberta-base': 'https://huggingface.co/goog... | 638 | from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipeline... | 638 | 1 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Generati... | 638 | import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(__lowercase ) , 'Tatoeba direc... | 638 | 1 |
from collections.abc import Sequence
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase = False ) -> float:
'''simple docstring'''
if not arr:
return 0
_lowerCamelCase = 0 if allow_empty_subarrays else float('''-inf''' )
_lowerCamel... | 638 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_inf... | 638 | 1 |
from __future__ import annotations
snake_case__ = []
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> bool:
'''simple docstring'''
for i in range(len(__UpperCAmelCase ) ):
if board[row][i] == 1:
retur... | 638 | import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
logging,
)
... | 638 | 1 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class UpperC... | 638 | import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase ( __lowercase ):
'''simple docstring'''
def __init__( self , *A_ , **A_ ) -> None:
... | 638 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtracto... | 638 | import argparse
import json
import subprocess
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = []
_lowerCamelCase = (
F'curl -H "Accept: application/vnd.github+json" -H "Authoriz... | 638 | 1 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {"vocab... | 700 | from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
requi... | 638 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
'junnyu/roformer_chinese_small': 'https://huggingface.co/ju... | 701 | def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
_lowerCamelCase = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def __magic_name__... | 638 | 0 |
snake_case__ = 0 # The first color of the flag.
snake_case__ = 1 # The second color of the flag.
snake_case__ = 2 # The third color of the flag.
snake_case__ = (red, white, blue)
def __magic_name__( __UpperCAmelCase ) -> list:
'''simple docstring'''
if not sequen... | 702 | import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTokenizerFast,
... | 638 | 0 |
from collections.abc import Generator
def __magic_name__( ) -> Generator[int, None, None]:
'''simple docstring'''
_lowerCamelCase , _lowerCamelCase = 0, 1
while True:
_lowerCamelCase , _lowerCamelCase = b, a + b
... | 703 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 638 | 0 |
from collections import deque
class UpperCamelCase :
'''simple docstring'''
def __init__( self , A_ , A_ , A_ ) -> None:
"""simple docstring"""
_lowerCamelCase = process_name # process name
_lowerCamel... | 704 | from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransformerConfig',
],
}
try:
... | 638 | 0 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTe... | 705 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils ... | 638 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fro... | 706 | import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
snake_case__ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf(), gbe... | 638 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase ( UpperCAmelCase_ ):
'''simple docstri... | 707 | import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcess... | 638 | 0 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class UpperCamelCase ( yaml.SafeLoader ):
'''simple docstring'''
def UpperCamelCase_ ( self , A_ ) -> Union[str, Any]:
"""simple docstr... | 708 | import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from transformers.model... | 638 | 0 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
snake_case__ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf(), gbe... | 709 | def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> bool:
'''simple docstring'''
_lowerCamelCase = len(__UpperCAmelCase )
_lowerCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of z... | 638 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
snake_case__ = {
"configuration_efficientformer": [
"EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 710 | from typing import List
import numpy as np
def __magic_name__( __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = {key: len(__UpperCAmelCase ) for key, value in gen_kwargs.items() if isinstance(__UpperCAmelCase , __UpperCAmelCase )}
if le... | 638 | 0 |
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def __magic_name__( ) -> Optional[... | 711 | 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 ImageProcessingSavingTestMixin, prepare_image_inputs
... | 638 | 0 |
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class UpperCamelCase ( UpperCamelCase_ , UpperCamelCase_ ):
'''simple docstring'''
@register_to_co... | 712 | import argparse
import json
from tqdm import tqdm
def __magic_name__( ) -> List[str]:
'''simple docstring'''
_lowerCamelCase = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'''--src_path''' , type=__UpperCAmelCase ... | 638 | 0 |
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
snake_case__ = get_logger... | 713 | import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerF... | 638 | 0 |
from math import pow
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , ) -> List[Any]:
'''simple docstring'''
if current_sum == needed_sum:
# If the sum of the powers is e... | 714 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ = {
'configuration_whisper': ['WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Whis... | 638 | 0 |
'''simple docstring'''
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def __magic_name__( __UpperCAmelCase ) -> List[Any]:
'''simple docstring'''
_lowerCamelCase ... | 715 | import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='%(message)s')
def __magic_name__( __UpperCAmelCase ) -> np.ndarray:
'''simple docstring'''
return input_array.reshape((input_array.size, 1) )
def... | 638 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
'google/bit-50': 'https://huggingface.co/google/bit-50/resolve/ma... | 716 | from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipeline... | 638 | 0 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> List[str]:
'''simple docstring'''
_lowerCamelCase = list(_lowerCamelCase )
_lowerCamelCase = list... | 717 | import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(__lowercase ) , 'Tatoeba direc... | 638 | 0 |
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class UpperCamelCase ( _UpperCAmelCase ):
'''simple docstring'''
def __lt__( self , A_ ) -> Dict:
"""s... | 718 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_inf... | 638 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tens... | 719 | import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
logging,
)
... | 638 | 0 |
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets import load... | 720 | import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase ( __lowercase ):
'''simple docstring'''
def __init__( self , *A_ , **A_ ) -> None:
... | 638 | 0 |
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def __magic_name__( __UpperCAmelCase ) -> str:
'''simple docstring'''
_lowerCamelCase = [
"""encoder.version""",
... | 721 | import argparse
import json
import subprocess
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = []
_lowerCamelCase = (
F'curl -H "Accept: application/vnd.github+json" -H "Authoriz... | 638 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from trans... | 700 | from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
requi... | 638 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import... | 701 | def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
_lowerCamelCase = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def __magic_name__... | 638 | 0 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. i... | 702 | import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTokenizerFast,
... | 638 | 0 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_im... | 703 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 638 | 0 |
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase ( lowercase__ ):
'''simple docstring'''
def __init__( self , *A_ , **A_ ) -> No... | 704 | from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransformerConfig',
],
}
try:
... | 638 | 0 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class UpperCamelCase ( __SCREAMING_SNAKE_CASE ):... | 705 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils ... | 638 | 0 |
'''simple docstring'''
import math
class UpperCamelCase :
'''simple docstring'''
def __init__( self , A_=0 ) -> str: # a graph with Node 0,1,...,N-1
"""simple docstring"""
_lowerCamelCase = n
_lowerCamelCas... | 706 | import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
snake_case__ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf(), gbe... | 638 | 0 |
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class UpperCamelCase :
'''simple docstring'''
A_ = 42
A_ ... | 707 | import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcess... | 638 | 0 |
import sys
UpperCamelCase__ = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098711121722... | 708 | import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from transformers.model... | 638 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@req... | 709 | def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> bool:
'''simple docstring'''
_lowerCamelCase = len(__UpperCAmelCase )
_lowerCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of z... | 638 | 0 |
from math import isclose, sqrt
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
_lowerCamelCase = point_y / 4 / point_x
_lowerCamelCase = 2 * normal_gradient / (1 + normal_gradient * no... | 710 | from typing import List
import numpy as np
def __magic_name__( __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = {key: len(__UpperCAmelCase ) for key, value in gen_kwargs.items() if isinstance(__UpperCAmelCase , __UpperCAmelCase )}
if le... | 638 | 0 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoToke... | 711 | 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 ImageProcessingSavingTestMixin, prepare_image_inputs
... | 638 | 0 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
... | 712 | import argparse
import json
from tqdm import tqdm
def __magic_name__( ) -> List[str]:
'''simple docstring'''
_lowerCamelCase = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'''--src_path''' , type=__UpperCAmelCase ... | 638 | 0 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase ( __lowercase ):
'''simple docstring'''
A_ = CustomTokenizer
pass | 713 | import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerF... | 638 | 0 |
from __future__ import annotations
def __magic_name__( __UpperCAmelCase ) -> Tuple:
'''simple docstring'''
_lowerCamelCase = len(__UpperCAmelCase )
# We need to create solution object to save path.
_lowerCamelCase = [[0 for _ in range(__Upp... | 714 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ = {
'configuration_whisper': ['WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Whis... | 638 | 0 |
'''simple docstring'''
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testi... | 715 | import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='%(message)s')
def __magic_name__( __UpperCAmelCase ) -> np.ndarray:
'''simple docstring'''
return input_array.reshape((input_array.size, 1) )
def... | 638 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json""",
}
class UpperCamelCase ( __snake_case ):
... | 716 | from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipeline... | 638 | 0 |
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
snake_case__ = logging.get_logger(__name__)
snake_case__ = {'''vocab_file''': '''sentencepiece.model'''}
snake_case__ ... | 717 | import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(__lowercase ) , 'Tatoeba direc... | 638 | 0 |
from __future__ import annotations
def __magic_name__( __UpperCAmelCase ) -> str:
'''simple docstring'''
return [ord(__lowerCAmelCase ) - 96 for elem in plain]
def __magic_name__( __UpperCAmelCase ) -> str:
'''simple docstring'''
return "".j... | 718 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_inf... | 638 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
snake_case__ = logging.get_logger(__name__)
snake_case__ = {
'google/bit-50': 'https://huggingface.co/google/bit-50/re... | 719 | import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
logging,
)
... | 638 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 720 | import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase ( __lowercase ):
'''simple docstring'''
def __init__( self , *A_ , **A_ ) -> None:
... | 638 | 0 |
from __future__ import annotations
import math
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> Dict:
'''simple docstring'''
if depth < 0:
raise ValueError('''Depth cannot be l... | 721 | import argparse
import json
import subprocess
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = []
_lowerCamelCase = (
F'curl -H "Accept: application/vnd.github+json" -H "Authoriz... | 638 | 0 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
fr... | 700 | from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
requi... | 638 | 0 |
from math import factorial
snake_case__ = {str(d): factorial(d) for d in range(10)}
def __magic_name__( __UpperCAmelCase ) -> int:
'''simple docstring'''
return sum(DIGIT_FACTORIAL[d] for d in str(_SCREAMING_SNAKE_CASE ) )
def __magic_name__( ) -> int:
... | 701 | def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
_lowerCamelCase = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def __magic_name__... | 638 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelera... | 702 | import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTokenizerFast,
... | 638 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
snake_case__ = {
'configuration_vivit': ['VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VivitConfig'],
}
try:
if not i... | 703 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 638 | 0 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
snake_case__ = {
'facebook/mask2former-swin-small-coco-instance': (
'https://huggingface.co/facebook/mask2former-swin-sma... | 704 | from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransformerConfig',
],
}
try:
... | 638 | 0 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_... | 705 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils ... | 638 | 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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextCla... | 706 | import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
snake_case__ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf(), gbe... | 638 | 0 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase ( _UpperCamelCase ):
'''simple docstring'''
def __init__( self , *A_ , **A_ ) -> None:
... | 707 | import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcess... | 638 | 0 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
UpperCamelCase__ = 'sshleifer/bart-tiny-random'
UpperCamelC... | 708 | import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from transformers.model... | 638 | 0 |
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__( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> Optional[Any]:
... | 709 | def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> bool:
'''simple docstring'''
_lowerCamelCase = len(__UpperCAmelCase )
_lowerCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of z... | 638 | 0 |
from math import loga
def __magic_name__( __UpperCAmelCase ) -> List[str]:
'''simple docstring'''
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(snake_case_ , snake_case_ ):
raise TypeError('''Input... | 710 | from typing import List
import numpy as np
def __magic_name__( __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = {key: len(__UpperCAmelCase ) for key, value in gen_kwargs.items() if isinstance(__UpperCAmelCase , __UpperCAmelCase )}
if le... | 638 | 0 |
import numpy as np
snake_case__ = [
['a', 'b', 'c', 'd', 'e'],
['f', 'g', 'h', 'i', 'k'],
['l', 'm', 'n', 'o', 'p'],
['q', 'r', 's', 't', 'u'],
['v', 'w', 'x', 'y', 'z'],
]
class UpperCamelCase :
'''simple docstring'''
def __init__( self ) -> Union[... | 711 | 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 ImageProcessingSavingTestMixin, prepare_image_inputs
... | 638 | 0 |
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_pyazr, require_... | 712 | import argparse
import json
from tqdm import tqdm
def __magic_name__( ) -> List[str]:
'''simple docstring'''
_lowerCamelCase = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'''--src_path''' , type=__UpperCAmelCase ... | 638 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.ut... | 713 | import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerF... | 638 | 0 |
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from transformers.fi... | 714 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case__ = {
'configuration_whisper': ['WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Whis... | 638 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ = {
'configuration_informer': [
'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Informer... | 715 | import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='%(message)s')
def __magic_name__( __UpperCAmelCase ) -> np.ndarray:
'''simple docstring'''
return input_array.reshape((input_array.size, 1) )
def... | 638 | 0 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
snake_case__ = '''src/diffusers'''
... | 716 | from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipeline... | 638 | 0 |
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_common import ConfigTester
from ...test_... | 717 | import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(__lowercase ) , 'Tatoeba direc... | 638 | 0 |
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils import float... | 718 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_inf... | 638 | 0 |
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 UpperCamelCase ( __snake_case , __snake_case ):
'''simple docst... | 719 | import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
logging,
)
... | 638 | 0 |
import enum
import shutil
import sys
snake_case__ = shutil.get_terminal_size()
snake_case__ = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class UpperCamelCase ( enum.Enum ):
'''simple docstring'''
A_ = 0
A_ = 1
def __magic_nam... | 720 | import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase ( __lowercase ):
'''simple docstring'''
def __init__( self , *A_ , **A_ ) -> None:
... | 638 | 0 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class UpperCAmelCase__ :
'''simple docstring'''
@property
def Up... | 721 | import argparse
import json
import subprocess
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> int:
'''simple docstring'''
_lowerCamelCase = []
_lowerCamelCase = (
F'curl -H "Accept: application/vnd.github+json" -H "Authoriz... | 638 | 0 |
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_vision, slow, torch_device
from tran... | 700 | from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
requi... | 638 | 0 |
import re
def __magic_name__( __UpperCAmelCase ) -> Any:
'''simple docstring'''
_lowerCamelCase = 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(__UpperCAmelCase , __UpperCAm... | 701 | def __magic_name__( __UpperCAmelCase , __UpperCAmelCase ) -> str:
'''simple docstring'''
_lowerCamelCase = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def __magic_name__... | 638 | 0 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPM... | 702 | import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTokenizerFast,
... | 638 | 0 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
snake_case__ = logging.get_logger(__name__)
class UpperCamelCase ( __lowercase ):
'''simple docstring'''
def __init__( self , *A_ , **A_ ) -> ... | 703 | from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_... | 638 | 0 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from... | 704 | from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransformerConfig',
],
}
try:
... | 638 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def __magic_name__( __UpperCAmelCase , __UpperCAmelCase=1000 ):
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
_lowerCamelCase... | 705 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils ... | 638 | 0 |
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