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'''
from torch import nn
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] ):
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU... | 718 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase... | 653 | 0 |
'''simple docstring'''
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,
... | 719 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( ):
lowercase = []
lowercase = 1
while len(lowercase_ ) < 1E6:
constant.append(str(lowercase_ ) )
i += 1
lowercase = """""".join(lowercase_ )
... | 653 | 0 |
'''simple docstring'''
import tensorflow as tf
from ...tf_utils import shape_list
class __UpperCamelCase (tf.keras.layers.Layer ):
def __init__( self , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase=1 , _lowerCAmelCase=False ,... | 720 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( ):
lowercase = os.path.join(os.path.dirname(lowercase_ ) , """num.txt""" )
with open(lowercase_ ) as file_hand:
return str(sum(int(lowercase_ ) for line in file_hand ) ... | 653 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class __UpperCamelCase (_UpperC... | 721 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 653 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] , lowercase_ : str ):
lowercase = """"""
for i in table:
res += inp[i - 1]
return res
def SCREAMING_SNAKE_CASE ( lowercase_ : List[An... | 700 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeq... | 653 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 701 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 653 | 0 |
from PIL import Image
def SCREAMING_SNAKE_CASE ( lowercase_ : Image , lowercase_ : float ):
def brightness(lowercase_ : int ) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.0:
raise ValueError("""level... | 702 |
'''simple docstring'''
from ... import PretrainedConfig
lowercase_ : int = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class __UpperCamelCase (_UpperCAmelCase ):
__A = NEZHA_PRETRAINED_CONFIG_ARCHIV... | 653 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, 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():
impo... | 703 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
lowercase_ : ... | 653 | 0 |
'''simple docstring'''
import math
lowercase_ : Any = 10
lowercase_ : Any = 7
lowercase_ : str = BALLS_PER_COLOUR * NUM_COLOURS
def SCREAMING_SNAKE_CASE ( lowercase_ : int = 20 ):
lowercase = math.comb(lowercase_ ... | 704 |
'''simple docstring'''
from __future__ import annotations
import os
from typing import Any
import requests
lowercase_ : List[str] = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowercase_ : Any =... | 653 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ : list ):
def merge(lowercase_ : list , lowercase_ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
... | 705 |
'''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 transformers impor... | 653 | 0 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 706 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase_ : Union[str, An... | 653 | 0 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from tra... | 707 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Any = logging.get_logger(__name__)
lowercase_ : str = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config... | 653 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : str = logging.get_logger(__name__)
lowercase_ : Optional[int] = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/r... | 708 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] , lowercase_ : str ):
lowercase = """"""
for i in table:
res += inp[i - 1]
return res
def SCREAMING_SNAKE_CASE ( lowercase_ : List[An... | 653 | 0 |
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
lowercase_ : Optional[Any] = logging.get_logger(__name__)
class __UpperCamelCase (_UpperCAmelCase ):
def __init__( self , *_lowerCAmelCase , **_lowerCAmel... | 709 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase_ : int = 50_0000
lowercase_ , lowercase_ : Union[str, Any] = os.path.split(__file__)
lowercase_ ... | 653 | 0 |
'''simple docstring'''
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] , lowercase_ : Tuple=7 ):
lowercase = None
if token i... | 710 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def SCREAMING_SNAKE_CASE ( lowercase_ : List[str] , lowercase_ : Optional[int] ):
lowercase = int(lowercase_ )
assert noofclusters < len(lowercas... | 653 | 0 |
'''simple docstring'''
import socket
def SCREAMING_SNAKE_CASE ( ):
lowercase = socket.socket(socket.AF_INET , socket.SOCK_STREAM )
lowercase = socket.gethostname()
lowercase = 1_2312
sock.connect((host, port) )
sock... | 711 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int , lowercase_ : list[list[int]] ):
def update_area_of_max_square(lowercase_ : int , lowercase_ : int ) -> int:
# BASE CASE
if row >= r... | 653 | 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,
MobileViTImag... | 712 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase_ : int = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-sant... | 653 | 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 TextInput
from... | 713 |
'''simple docstring'''
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
lowercase = {"""Content-Type""": """application/json"""}
lowercase = requests.post(lowercase_ , json={"""text""": message_body} , ... | 653 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : list[int] , lowercase_ : int ):
def count_of_possible_combinations(lowercase_ : int ) -> int:
if target < 0:
return 0
if target ... | 714 |
'''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,
MobileViTImage... | 653 | 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_ : Any = importlib.util.find_spec('''s3fs''') is not None
if _has_safs:
... | 715 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 653 | 0 |
'''simple docstring'''
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CON... | 716 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def SCREAMING_SNAKE_CASE ( ):
lowercase = HfArgumentParser(lowercase_ )
lowercase = parser.parse_args_into_dataclasses()[0]
lowerca... | 653 | 0 |
'''simple docstring'''
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available... | 717 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 653 | 0 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] ):
lowercase = os.path.join(args.tf_model_dir , """pa... | 718 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase... | 653 | 0 |
'''simple docstring'''
import argparse
import collections
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import TaConfig, TaEncoderModel, TaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CA... | 719 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( ):
lowercase = []
lowercase = 1
while len(lowercase_ ) < 1E6:
constant.append(str(lowercase_ ) )
i += 1
lowercase = """""".join(lowercase_ )
... | 653 | 0 |
'''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __UpperCamelCase (_UpperCAmelCase ):
__A = ... | 720 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( ):
lowercase = os.path.join(os.path.dirname(lowercase_ ) , """num.txt""" )
with open(lowercase_ ) as file_hand:
return str(sum(int(lowercase_ ) for line in file_hand ) ... | 653 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : str ):
lowercase = 0
for ch in input_str:
lowercase = ord(lowercase_ )
lowercase = pow(2 , lowercase_ )
# If we alr... | 721 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 653 | 0 |
'''simple docstring'''
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ : Any ):
lowercase = {}
lowercase = job["""started_at"""]
lowercase = ... | 700 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeq... | 653 | 0 |
'''simple docstring'''
from __future__ import annotations
from PIL import Image
# Define glider example
lowercase_ : List[str] = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0,... | 701 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 653 | 0 |
from manim import *
class __UpperCamelCase (_UpperCAmelCase ):
def _a ( self ) -> List[str]:
'''simple docstring'''
lowercase = Rectangle(height=0.5 , width=0.5 )
lowercase = Rectangle(height=0.46 , width=0.46... | 702 |
'''simple docstring'''
from ... import PretrainedConfig
lowercase_ : int = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class __UpperCamelCase (_UpperCAmelCase ):
__A = NEZHA_PRETRAINED_CONFIG_ARCHIV... | 653 | 0 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int , lowercase_ : int , lowercase_ : int , lowercase_ : int , ... | 703 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
lowercase_ : ... | 653 | 0 |
'''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_uti... | 704 |
'''simple docstring'''
from __future__ import annotations
import os
from typing import Any
import requests
lowercase_ : List[str] = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowercase_ : Any =... | 653 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( lowercase_ : list[int] ):
return len(set(lowercase_ ) ) == len(lowercase_ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 705 |
'''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 transformers impor... | 653 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from ... | 706 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase_ : Union[str, An... | 653 | 0 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
... | 707 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Any = logging.get_logger(__name__)
lowercase_ : str = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config... | 653 | 0 |
'''simple docstring'''
from collections.abc import Callable
def SCREAMING_SNAKE_CASE ( lowercase_ : Callable[[float], float] , lowercase_ : float , lowercase_ : float ):
lowercase = a
lowercase = b
if function(lowercase_ ... | 708 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] , lowercase_ : str ):
lowercase = """"""
for i in table:
res += inp[i - 1]
return res
def SCREAMING_SNAKE_CASE ( lowercase_ : List[An... | 653 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ : Optional[int] , lowercase_ : int , lowercase_ : Optional[int] , lowercase_ : Tuple ):
if height >= 1:
move_tower(height - 1 , lowercase_ , lowercase_ , lowercase_ )
move_disk(lowercase_ ,... | 709 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase_ : int = 50_0000
lowercase_ , lowercase_ : Union[str, Any] = os.path.split(__file__)
lowercase_ ... | 653 | 0 |
'''simple docstring'''
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("""repo_id""" , ["""canonical_dataset_name""", """org-name/dataset-name"""] )
@pytest.mark.parametrize("""path""" , ["""filename.csv""", """filename with blanks.cs... | 710 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def SCREAMING_SNAKE_CASE ( lowercase_ : List[str] , lowercase_ : Optional[int] ):
lowercase = int(lowercase_ )
assert noofclusters < len(lowercas... | 653 | 0 |
'''simple docstring'''
import torch
from diffusers import DiffusionPipeline
class __UpperCamelCase (_UpperCAmelCase ):
def __init__( self , _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
'''simple docstring'''
super().__init__()
self.reg... | 711 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int , lowercase_ : list[list[int]] ):
def update_area_of_max_square(lowercase_ : int , lowercase_ : int ) -> int:
# BASE CASE
if row >= r... | 653 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase_ : Any = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenizatio... | 712 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase_ : int = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-sant... | 653 | 0 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
... | 713 |
'''simple docstring'''
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
lowercase = {"""Content-Type""": """application/json"""}
lowercase = requests.post(lowercase_ , json={"""text""": message_body} , ... | 653 | 0 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class __UpperCamelCase (unittest.Tes... | 714 |
'''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,
MobileViTImage... | 653 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ : Dict = logging.get_logger(__name__)
lowercas... | 715 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 653 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_ax... | 716 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def SCREAMING_SNAKE_CASE ( ):
lowercase = HfArgumentParser(lowercase_ )
lowercase = parser.parse_args_into_dataclasses()[0]
lowerca... | 653 | 0 |
'''simple docstring'''
lowercase_ : List[str] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'''
def SCREAMING_SNAKE_CASE ( lowercase_ : bytes ):
# Make sure the supplied data is a bytes-like object
if not isinstan... | 717 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 653 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase_ : Tuple = logging.get_logger(__name__)
lowercase_ : Optional[int] ... | 718 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase... | 653 | 0 |
'''simple docstring'''
from collections import namedtuple
lowercase_ : List[str] = namedtuple('''from_to''', '''from_ to''')
lowercase_ : List[Any] = {
'''cubicmeter''': from_to(1, 1),
'''litre''': from_to(0.001, 1000),
'''kilolitre''': from_to(1, 1),
'''gallo... | 719 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( ):
lowercase = []
lowercase = 1
while len(lowercase_ ) < 1E6:
constant.append(str(lowercase_ ) )
i += 1
lowercase = """""".join(lowercase_ )
... | 653 | 0 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
lowercase_ : Optional[Any] ... | 720 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( ):
lowercase = os.path.join(os.path.dirname(lowercase_ ) , """num.txt""" )
with open(lowercase_ ) as file_hand:
return str(sum(int(lowercase_ ) for line in file_hand ) ... | 653 | 0 |
'''simple docstring'''
import torch
from ..models.auto import AutoModelForSequenceClassification, AutoTokenizer
from .base import PipelineTool
class __UpperCamelCase (_UpperCAmelCase ):
__A = '''facebook/bart-large-mnli'''
__A = (
'''This is a tool that c... | 721 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 653 | 0 |
'''simple docstring'''
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class A ( UpperCAmelCase ):
a_ = CustomTokenizer
pass
| 654 | '''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
fro... | 654 | 1 |
'''simple docstring'''
import heapq
import sys
import numpy as np
__lowerCAmelCase : Any = tuple[int, int]
class A :
def __init__( self : Optional[int] ) -> int:
__UpperCAmelCase = []
__UpperCAmelCase ... | 654 | '''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__lowerCAmelCase : Any = ""
__lowerCAmelCase : int = ""
__lowerCAmelCase : Union[str, Any] = ""
__lowerCAmelCase : Any =... | 654 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import ... | 654 | '''simple docstring'''
from pathlib import Path
import fire
def lowerCAmelCase ( UpperCamelCase__ : str , UpperCamelCase__ : str , UpperCamelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase = Path(UpperCamelCase__ )
__UpperC... | 654 | 1 |
'''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
... | 654 | '''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : int ):
"""simple docstring"""
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
__UpperCAmelCase = f"""Input value of [number={number}] must be an integer"""
raise TypeError(UpperCamelCa... | 654 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : List[str] = logging.get_logger(__name__)
__lowerCAmelCase : Union[str, Any] = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https:/... | 654 | '''simple docstring'''
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def lowerCAmelCase ( ):
"""simple docstring"""
raise RuntimeError('''CUDA out ... | 654 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
__lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
class A ( UpperCAmelCase ):
def __init__( self : ... | 654 | '''simple docstring'''
from __future__ import annotations
import math
def lowerCAmelCase ( UpperCamelCase__ : float , UpperCamelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase = u
for i in range(1 , UpperCamelCase__ ):
__Uppe... | 654 | 1 |
'''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoA... | 654 | '''simple docstring'''
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
Vi... | 654 | 1 |
'''simple docstring'''
import re
def lowerCAmelCase ( UpperCamelCase__ : str ):
"""simple docstring"""
if len(re.findall('''[ATCG]''' , UpperCamelCase__ ) ) != len(UpperCamelCase__ ):
raise ValueError('''Invalid Strand''' )
return dna... | 654 | '''simple docstring'''
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
... | 654 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
__lowerCAmelCase : str = {}
class A ( UpperCAmelCase ):
a_ = ... | 654 | '''simple docstring'''
import argparse
import os
import re
import packaging.version
__lowerCAmelCase : Optional[int] = "examples/"
__lowerCAmelCase : Dict = {
"examples": (re.compile(r"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VER... | 654 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from ... | 654 | '''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : Tuple ):
"""simple docstring"""
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
__UpperCAmelCase = len(UpperCamelCase__ )
__... | 654 | 1 |
'''simple docstring'''
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, ToTe... | 654 | '''simple docstring'''
import requests
from bsa import BeautifulSoup
def lowerCAmelCase ( UpperCamelCase__ : str = "AAPL" ):
"""simple docstring"""
__UpperCAmelCase = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
__UpperCAmelCase = Beautif... | 654 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCAmelCase : Any = logging.get_logger(__name__)
__lowerCAmelCase : str ... | 654 | '''simple docstring'''
from __future__ import annotations
from statistics import mean
def lowerCAmelCase ( UpperCamelCase__ : list[int] , UpperCamelCase__ : list[int] , UpperCamelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase = [0... | 654 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
__lowerCAmelCase : Optional[int] = 500_000
__lowerCAmelCase , __lowerCAmelCase : str = os.path.split(_... | 654 | '''simple docstring'''
from ..utils import DummyObject, requires_backends
class A ( metaclass=UpperCAmelCase ):
a_ = ['''torch''']
def __init__( self : Optional[int] , *__a : List[str] , **__a : Union[str, Any]... | 654 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
... | 654 | '''simple docstring'''
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| 654 | 1 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class A :
def __init__( self : ... | 654 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCAmelCase : Optional[Any] = {
"configuration_llama":... | 654 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... | 654 | '''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTraine... | 654 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A ( UpperCA... | 654 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, id... | 654 | 1 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils imp... | 654 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__lowerCAmelCase : List[Any] = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_... | 654 | 1 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
... | 654 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
class A ( UpperCAmelCase ):
a_ = '''bert-generation'''
def __init__( self : str , __a : str=5_0_3_5_8 , __a : int=1_0_2_4 , __a ... | 654 | 1 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
... | 654 | '''simple docstring'''
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__lowerCAmelCase : str = 299_792_458
# Symbols
__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase : Any ... | 654 | 1 |
'''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : int = 3 , UpperCamelCase__ : int = 7 , UpperCamelCase__ : int = 1_0_0_0_0_0_0 ):
"""simple docstring"""
__UpperCAmelCase = 0
__UpperCAmelCase = 1
for current_denominator in ran... | 654 | '''simple docstring'''
import heapq
import sys
import numpy as np
__lowerCAmelCase : Any = tuple[int, int]
class A :
def __init__( self : Optional[int] ) -> int:
__UpperCAmelCase = []
__UpperCAmelCase ... | 654 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICEN... | 654 | '''simple docstring'''
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent yo... | 654 | 1 |
'''simple docstring'''
from ....utils import logging
__lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
class A ( UpperCAmelCase ):
def __init__( self : Optional[int] , __a : int , __a : int=Non... | 654 | '''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
fro... | 654 | 1 |
'''simple docstring'''
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class A ( UpperCAmelCase ):
def __init__( self : int , __a... | 654 | '''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__lowerCAmelCase : Any = ""
__lowerCAmelCase : int = ""
__lowerCAmelCase : Union[str, Any] = ""
__lowerCAmelCase : Any =... | 654 | 1 |
'''simple docstring'''
import requests
__lowerCAmelCase : Dict = "YOUR API KEY"
def lowerCAmelCase ( UpperCamelCase__ : str , UpperCamelCase__ : str = giphy_api_key ):
"""simple docstring"""
__UpperCAmelCase = '''+'''.join(query.spli... | 654 | '''simple docstring'''
from pathlib import Path
import fire
def lowerCAmelCase ( UpperCamelCase__ : str , UpperCamelCase__ : str , UpperCamelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase = Path(UpperCamelCase__ )
__UpperC... | 654 | 1 |
'''simple docstring'''
import unittest
from knapsack import knapsack as k
class A ( unittest.TestCase ):
def snake_case__ ( self : int ) -> Tuple:
__UpperCAmelCase = 0
__UpperCAmelCase = [0]
__Up... | 654 | '''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : int ):
"""simple docstring"""
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
__UpperCAmelCase = f"""Input value of [number={number}] must be an integer"""
raise TypeError(UpperCamelCa... | 654 | 1 |
'''simple docstring'''
from torch import nn
def lowerCAmelCase ( UpperCamelCase__ : Any ):
"""simple docstring"""
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise V... | 654 | '''simple docstring'''
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def lowerCAmelCase ( ):
"""simple docstring"""
raise RuntimeError('''CUDA out ... | 654 | 1 |
'''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : int = 5_0 ):
"""simple docstring"""
__UpperCAmelCase = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - t... | 654 | '''simple docstring'''
from __future__ import annotations
import math
def lowerCAmelCase ( UpperCamelCase__ : float , UpperCamelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase = u
for i in range(1 , UpperCamelCase__ ):
__Uppe... | 654 | 1 |
'''simple docstring'''
import math
def lowerCAmelCase ( ):
"""simple docstring"""
__UpperCAmelCase = input('''Enter message: ''' )
__UpperCAmelCase = int(input(f"""Enter key [2-{len(UpperCamelCase__ ) - 1}]: """ ) )
__UpperCAmelCase = ... | 654 | '''simple docstring'''
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
Vi... | 654 | 1 |
'''simple docstring'''
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pip... | 654 | '''simple docstring'''
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
... | 654 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__lowerCAmelCase : List[Any] = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_... | 654 | '''simple docstring'''
import argparse
import os
import re
import packaging.version
__lowerCAmelCase : Optional[int] = "examples/"
__lowerCAmelCase : Dict = {
"examples": (re.compile(r"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VER... | 654 | 1 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
__lowerCAmelCase : int = "docs/source/en/_toctree.yml"
def lowerCAmelCase ( UpperCamelCase__ : List[str] ):
"""simple docstring"""
__UpperCAmelCase = de... | 654 | '''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : Tuple ):
"""simple docstring"""
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
__UpperCAmelCase = len(UpperCamelCase__ )
__... | 654 | 1 |
'''simple docstring'''
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME... | 654 | '''simple docstring'''
import requests
from bsa import BeautifulSoup
def lowerCAmelCase ( UpperCamelCase__ : str = "AAPL" ):
"""simple docstring"""
__UpperCAmelCase = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
__UpperCAmelCase = Beautif... | 654 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, id... | 654 | '''simple docstring'''
from __future__ import annotations
from statistics import mean
def lowerCAmelCase ( UpperCamelCase__ : list[int] , UpperCamelCase__ : list[int] , UpperCamelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase = [0... | 654 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils ... | 654 | '''simple docstring'''
from ..utils import DummyObject, requires_backends
class A ( metaclass=UpperCAmelCase ):
a_ = ['''torch''']
def __init__( self : Optional[int] , *__a : List[str] , **__a : Union[str, Any]... | 654 | 1 |
'''simple docstring'''
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent yo... | 654 | '''simple docstring'''
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"The `image_to_image.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionImg2ImgPipeline` instead."
)
| 654 | 1 |
'''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 A ( UpperCAme... | 654 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCAmelCase : Optional[Any] = {
"configuration_llama":... | 654 | 1 |
'''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : list[int] ):
"""simple docstring"""
__UpperCAmelCase = []
if len(UpperCamelCase__ ) == 1:
return [nums.copy()]
for _ in range(len(UpperCamelCase__ ) ):
__UpperCAmelCase = nums.po... | 654 | '''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTraine... | 654 | 1 |
'''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : Tuple ):
"""simple docstring"""
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
__UpperCAmelCase = len(UpperCamelCase__ )
__... | 654 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, id... | 654 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class A ( UpperCAmelCase ):
... | 654 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__lowerCAmelCase : List[Any] = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_... | 654 | 1 |
'''simple docstring'''
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTok... | 654 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
class A ( UpperCAmelCase ):
a_ = '''bert-generation'''
def __init__( self : str , __a : str=5_0_3_5_8 , __a : int=1_0_2_4 , __a ... | 654 | 1 |
'''simple docstring'''
#
# This a `torch.distributed` diagnostics script that checks that all GPUs in the cluster (one or
# many nodes) can talk to each other via nccl and allocate gpu memory.
#
# To run first adjust the number of processes and nodes:
#
# python -m torch.distributed.run --nproc_per_node 2 --... | 654 | '''simple docstring'''
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__lowerCAmelCase : str = 299_792_458
# Symbols
__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase : Any ... | 654 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_... | 654 | '''simple docstring'''
import heapq
import sys
import numpy as np
__lowerCAmelCase : Any = tuple[int, int]
class A :
def __init__( self : Optional[int] ) -> int:
__UpperCAmelCase = []
__UpperCAmelCase ... | 654 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCAmelCase : str = logging.get_logger(__name__)
__lowerCAmelCase : Optional[int] = {
"nielsr/can... | 654 | '''simple docstring'''
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent yo... | 654 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils i... | 654 | '''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
fro... | 654 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBloc... | 654 | '''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__lowerCAmelCase : Any = ""
__lowerCAmelCase : int = ""
__lowerCAmelCase : Union[str, Any] = ""
__lowerCAmelCase : Any =... | 654 | 1 |
'''simple docstring'''
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,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscret... | 654 | '''simple docstring'''
from pathlib import Path
import fire
def lowerCAmelCase ( UpperCamelCase__ : str , UpperCamelCase__ : str , UpperCamelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase = Path(UpperCamelCase__ )
__UpperC... | 654 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase ( UpperCamelCase__ : list[list[int]] ):
"""simple docstring"""
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# p... | 654 | '''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : int ):
"""simple docstring"""
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
__UpperCAmelCase = f"""Input value of [number={number}] must be an integer"""
raise TypeError(UpperCamelCa... | 654 | 1 |
'''simple docstring'''
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class A ( unittest.TestCase ):
a_ = JukeboxTokenizer
a_ = {
'''artist''': '''Zac Brown Band''',
... | 654 | '''simple docstring'''
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def lowerCAmelCase ( ):
"""simple docstring"""
raise RuntimeError('''CUDA out ... | 654 | 1 |
'''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : int ):
"""simple docstring"""
if upper_limit < 0:
raise ValueError('''Limit for the Catalan sequence must be ≥ 0''' )
__UpperCAmelCase = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__Upp... | 654 | '''simple docstring'''
from __future__ import annotations
import math
def lowerCAmelCase ( UpperCamelCase__ : float , UpperCamelCase__ : int ):
"""simple docstring"""
__UpperCAmelCase = u
for i in range(1 , UpperCamelCase__ ):
__Uppe... | 654 | 1 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators impo... | 654 | '''simple docstring'''
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
Vi... | 654 | 1 |
'''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
__lowerCAmelCase : Dict ... | 654 | '''simple docstring'''
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
... | 654 | 1 |
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