code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import heapq
import sys
import numpy as np
lowerCAmelCase_ = tuple[int, int]
class lowerCamelCase :
def __init__( self ) -> Any:
snake_case = []
snake_case = set()
def _lowerCamelCase ( self ) -> Optional[Any]:
... | 361 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"roberta-base": "https://h... | 332 | 0 |
'''simple docstring'''
from collections import UserDict
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():
... | 362 |
'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrate... | 332 | 0 |
'''simple docstring'''
def __magic_name__ ( A , A ) -> str:
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(A , int(b / 2 ) ) * actual_power(A , int(b / 2 ) )
else:
return a * actual_power(A , int(b / 2 ) ) * actual_pow... | 363 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __magic_name__ ( A ) -> Tuple:
snake_case ... | 332 | 0 |
'''simple docstring'''
from __future__ import annotations
class lowerCamelCase :
def __init__( self, lowercase_, lowercase_ ) -> str:
snake_case , snake_case = text, pattern
snake_case , snake_case = len(lowercase_ ), len(lowercase_ )
def _lowerCamelCa... | 364 |
'''simple docstring'''
from pathlib import Path
import fire
def __magic_name__ ( A , A , A ) -> Union[str, Any]:
snake_case = Path(A )
snake_case = Path(A )
dest_dir.mkdir(exist_ok=A )
for path in src_dir.iterdir():
snake_case = [... | 332 | 0 |
'''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils imp... | 365 |
'''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
lowerCAmelCase_ = pytest.mark.integration
@pytest.mark.parametrize('path' , ... | 332 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import ceil, floor, sqrt
def __magic_name__ ( A = 2_0_0_0_0_0_0 ) -> int:
snake_case = [0]
snake_case = 4_2
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ):
triangle_numb... | 366 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ = {
"configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"],
"processing_git": ["GitProcessor"],
}
try:
... | 332 | 0 |
'''simple docstring'''
def __magic_name__ ( A ) -> float:
return 1_0 - x * x
def __magic_name__ ( A , A ) -> float:
# Bolzano theory in order to find if there is a root between a and b
if equation(A ) * equation(A ) >= 0:
raise ValueError('Wrong ... | 367 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import Lear... | 332 | 0 |
'''simple docstring'''
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
fr... | 368 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class lowerCamelCase ( metaclass=__lowerCAmelCase ):
snake_case_ = ['''note_seq''']
def __init__( self, *lowercase_, **lowercase_ ) -> str:
requires_backends(self, ['note_seq'] )
@cla... | 332 | 0 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
... | 369 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowerCAmelCase_ = logging.get_logger(__name__)
class lowerCamelCase ( __lowerCAmelCase ):
def __init__( self, *lowercase_, **lowercase_ ) -> None:
war... | 332 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchm... | 370 |
'''simple docstring'''
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing... | 332 | 0 |
from __future__ import annotations
def __magic_name__ ( A , A = None , A = None , A = False , ) -> tuple[int, float, str]:
snake_case = cipher_alphabet or [chr(A ) for i in range(9_7 , 1_2_3 )]
# If the argument is None or the user provided an empty ... | 371 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class lowerCamelCase ( __lowerCAmelCase ):
snake_case_ = ''''''
snake_case_ = (
None # pr... | 332 | 0 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
Uppe... | 333 | import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCamelCase = 4
UpperCamelCase = 3
class snake_case_ ( __A ):
pass
... | 333 | 1 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class snake_case_ ( unittest.TestCase ):
def __UpperCamelCase ( self : Optional[int] ) -> Tuple:
lowercase__ : str = [
"safety_checker/pytorch_m... | 333 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''microsoft/unispeech-large-1500h-cv''': (
'''https://huggingface.co/microsoft/unispeec... | 333 | 1 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTokenizerFast,
... | 333 | def lowercase_ ( _lowerCamelCase : list):
for i in range(len(_lowerCamelCase) - 1 , 0 , -1):
lowercase__ : int = False
for j in range(_lowerCamelCase , 0 , -1):
if unsorted[j] < unsorted[j - 1]:
lowercase__ , ... | 333 | 1 |
UpperCamelCase = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def lowercase_ ( _lowerCamelCase : List[Any] , _lowerCamelCase : int , _lowerCamelCase ... | 333 | import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_sco... | 333 | 1 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertForMaskedLM... | 333 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Mask2FormerConfig''',
],
... | 333 | 1 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as P... | 333 | # Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def lowercase_ ( _lowerCamelCase : List[str]):
return 1 / (1 + np.exp(-z))
def lowercase_ ... | 333 | 1 |
def lowercase_ ( _lowerCamelCase : str , _lowerCamelCase : str):
lowercase__ : List[str] = len(_lowerCamelCase)
lowercase__ : Dict = len(_lowerCamelCase)
lowercase__ : Optional[Any] = [[False for _ in range(m + 1)] for _ in range(n ... | 333 | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__A )
class snake_case_ ( __A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output f... | 333 | 1 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import... | 333 | def lowercase_ ( _lowerCamelCase : int = 10 , _lowerCamelCase : int = 1000 , _lowerCamelCase : bool = True):
assert (
isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerC... | 333 | 1 |
def lowercase_ ( _lowerCamelCase : dict):
lowercase__ : int = set()
# edges = list of graph's edges
lowercase__ : Union[str, Any] = get_edges(_lowerCamelCase)
# While there are still elements in edges list, take an arbitrary edge
# (from_node, t... | 333 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies # noqa: E402
# This is... | 333 | 1 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
UpperCamelCase = logging.getLogger(__name__)
if __name__ == "__main__"... | 333 | from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils impo... | 333 | 1 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.co... | 333 | import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : Any , _lowerCamelCase : str):
lowercase__ : Optional[Any] = AutoConfig.from_pretrain... | 333 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 333 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pil... | 333 | 1 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
UpperCamelCase = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
UpperCamelCase = [file for file in f... | 333 | class snake_case_ :
def __init__( self : int ) -> Optional[int]:
lowercase__ : Optional[int] = 0
lowercase__ : List[str] = 0
lowercase__ : Any = {}
def __UpperCamelCase ( self : Dict ... | 333 | 1 |
class snake_case_ :
def __init__( self : int ) -> Optional[int]:
lowercase__ : Optional[int] = 0
lowercase__ : List[str] = 0
lowercase__ : Any = {}
def __UpperCamelCase ( self : Dict ... | 333 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
... | 333 | 1 |
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.co... | 333 | def lowercase_ ( _lowerCamelCase : int = 1 , _lowerCamelCase : int = 1000):
lowercase__ : Union[str, Any] = 1
lowercase__ : int = 0
for divide_by_number in range(_lowerCamelCase , digit + 1):
lowercase__ : list[int] = ... | 333 | 1 |
from typing import Dict, Optional
import numpy as np
import datasets
UpperCamelCase = '''
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or multi-cla... | 333 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diff... | 333 | 1 |
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import... | 333 | import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, Par... | 333 | 1 |
from scipy.stats import pearsonr
import datasets
UpperCamelCase = '''
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that each... | 333 | from ..utils import DummyObject, requires_backends
class snake_case_ ( metaclass=__A ):
__A : List[Any] = ["flax"]
def __init__( self : Optional[int] , *lowercase_ : Optional[int] , **lowercase_ : List[Any] ) -> Tuple:
... | 333 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/ma... | 333 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE model... | 333 | 1 |
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_vision_available
fro... | 333 | def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
while a != 0:
lowercase__ , lowercase__ : Dict = b % a, a
return b
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
if gcd(_lowerC... | 333 | 1 |
import sys
import turtle
def lowercase_ ( _lowerCamelCase : tuple[float, float] , _lowerCamelCase : tuple[float, float]):
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowercase_ ( _lowerCamelCase : tuple[float, float] , _lowerCamelCase : t... | 333 | import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import... | 333 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
... | 333 | import argparse
import datetime
def lowercase_ ( _lowerCamelCase : str):
lowercase__ : Optional[Any] = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturda... | 333 | 1 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class snake_case_ ( __A ):
def __init__( self : Dict , lowercase_ : Any , lowercase_ : str ) -> List[str]:
lowercase__ : Tuple =... | 333 | import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCamelCase = 4
UpperCamelCase = 3
class snake_case_ ( __A ):
pass
... | 333 | 1 |
def lowercase_ ( _lowerCamelCase : Optional[Any] , _lowerCamelCase : Union[str, Any]):
lowercase__ : str = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def lowercase_ ( _lowerCamelCase... | 333 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''microsoft/unispeech-large-1500h-cv''': (
'''https://huggingface.co/microsoft/unispeec... | 333 | 1 |
import requests
from bsa import BeautifulSoup
def lowercase_ ( _lowerCamelCase : str = "https://www.worldometers.info/coronavirus"):
lowercase__ : str = BeautifulSoup(requests.get(_lowerCamelCase).text , "html.parser")
lowercase__ : Union[str, Any] = so... | 333 | def lowercase_ ( _lowerCamelCase : list):
for i in range(len(_lowerCamelCase) - 1 , 0 , -1):
lowercase__ : int = False
for j in range(_lowerCamelCase , 0 , -1):
if unsorted[j] < unsorted[j - 1]:
lowercase__ , ... | 333 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
... | 333 | import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_sco... | 333 | 1 |
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy as np
from .import_u... | 333 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Mask2FormerConfig''',
],
... | 333 | 1 |
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
UpperCamelCase = 3
def lowercase_ ( _lowerCamelCase : int):
print("Generating primitive root of p")
while True:
lowercase__ : Any = ra... | 333 | # Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def lowercase_ ( _lowerCamelCase : List[str]):
return 1 / (1 + np.exp(-z))
def lowercase_ ... | 333 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
UpperCamelCase = ... | 333 | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__A )
class snake_case_ ( __A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output f... | 333 | 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, ... | 333 | def lowercase_ ( _lowerCamelCase : int = 10 , _lowerCamelCase : int = 1000 , _lowerCamelCase : bool = True):
assert (
isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerC... | 333 | 1 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
UpperCamelCase = '''2.13.1'''
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse('''3.7''')... | 333 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies # noqa: E402
# This is... | 333 | 1 |
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class snake_case_ ( __A ):
def __UpperCamelCase ( self : int , lowercase_ : str ) -> Optional[Any]:
with open(lowercase_ , en... | 333 | from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils impo... | 333 | 1 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : List[str] , _lower... | 333 | import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : Any , _lowerCamelCase : str):
lowercase__ : Optional[Any] = AutoConfig.from_pretrain... | 333 | 1 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowercase_ ( _lowerCamelCase : str , _lowerCamelCase : str = "cpu" , _lowerCamelCase : Union[str, None] = None):
lowercase__ : Optional[int] = torch.load(_lowerCamelCase , ... | 333 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pil... | 333 | 1 |
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.'''
)
| 333 | class snake_case_ :
def __init__( self : int ) -> Optional[int]:
lowercase__ : Optional[int] = 0
lowercase__ : List[str] = 0
lowercase__ : Any = {}
def __UpperCamelCase ( self : Dict ... | 333 | 1 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClassificati... | 333 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
... | 333 | 1 |
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 .tokenization_big_b... | 333 | def lowercase_ ( _lowerCamelCase : int = 1 , _lowerCamelCase : int = 1000):
lowercase__ : Union[str, Any] = 1
lowercase__ : int = 0
for divide_by_number in range(_lowerCamelCase , digit + 1):
lowercase__ : list[int] = ... | 333 | 1 |
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_up_block
@data... | 333 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diff... | 333 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__A )
class snake_case_ ( __A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output f... | 333 | import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, Par... | 333 | 1 |
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCamelCase = logging.get_logger(__name__)
class snake_case_ ( __A ):
__A : Any = ... | 333 | from ..utils import DummyObject, requires_backends
class snake_case_ ( metaclass=__A ):
__A : List[Any] = ["flax"]
def __init__( self : Optional[int] , *lowercase_ : Optional[int] , **lowercase_ : List[Any] ) -> Tuple:
... | 333 | 1 |
import os
def lowercase_ ( _lowerCamelCase : str = "input.txt"):
with open(os.path.join(os.path.dirname(_lowerCamelCase) , _lowerCamelCase)) as input_file:
lowercase__ : Tuple = [
[int(_lowerCamelCase) for element in line.split(",")]
fo... | 333 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE model... | 333 | 1 |
def lowercase_ ( _lowerCamelCase : list , _lowerCamelCase : list , _lowerCamelCase : int):
lowercase__ : Tuple = len(_lowerCamelCase)
lowercase__ : Any = [[0] * n for i in range(_lowerCamelCase)]
for i in range(_lowerCamelCase):
... | 333 | def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
while a != 0:
lowercase__ , lowercase__ : Dict = b % a, a
return b
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
if gcd(_lowerC... | 333 | 1 |
from ...configuration_utils import PretrainedConfig
UpperCamelCase = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-finetuned-wtq''': (
'''https://huggingface.co/g... | 333 | import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import... | 333 | 1 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class snake_case_ :
__A : int
__A : int
class snake_case_ :
def __init__( self : str , lowercase... | 333 | import argparse
import datetime
def lowercase_ ( _lowerCamelCase : str):
lowercase__ : Optional[Any] = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturda... | 333 | 1 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase ... | 333 | import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCamelCase = 4
UpperCamelCase = 3
class snake_case_ ( __A ):
pass
... | 333 | 1 |
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 require_keras_nlp, require_t... | 333 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''microsoft/unispeech-large-1500h-cv''': (
'''https://huggingface.co/microsoft/unispeec... | 333 | 1 |
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCamelCase = 300 # TEMPERATURE (unit = K)
def lowercase_ ( _lowerCamelCase : float , _lowerCamelCase : float , _lowerCamelCase : float , ):
if donor_conc <= 0:
... | 333 | def lowercase_ ( _lowerCamelCase : list):
for i in range(len(_lowerCamelCase) - 1 , 0 , -1):
lowercase__ : int = False
for j in range(_lowerCamelCase , 0 , -1):
if unsorted[j] < unsorted[j - 1]:
lowercase__ , ... | 333 | 1 |
import functools
def lowercase_ ( _lowerCamelCase : list[int] , _lowerCamelCase : list[int]):
# Validation
if not isinstance(_lowerCamelCase , _lowerCamelCase) or not all(isinstance(_lowerCamelCase , _lowerCamelCase) for day in days):
raise ValueError("Th... | 333 | import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_sco... | 333 | 1 |
from __future__ import annotations
UpperCamelCase = 10
def lowercase_ ( _lowerCamelCase : list[int]):
lowercase__ : List[Any] = 1
lowercase__ : int = max(_lowerCamelCase)
while placement <= max_digit:
# declare and initialize emp... | 333 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Mask2FormerConfig''',
],
... | 333 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
... | 333 | # Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def lowercase_ ( _lowerCamelCase : List[str]):
return 1 / (1 + np.exp(-z))
def lowercase_ ... | 333 | 1 |
def lowercase_ ( _lowerCamelCase : int = 10 , _lowerCamelCase : int = 1000 , _lowerCamelCase : bool = True):
assert (
isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerC... | 333 | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__A )
class snake_case_ ( __A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output f... | 333 | 1 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowercase_ ( _lowerCamelCase : dict):
return (data["data"... | 333 | def lowercase_ ( _lowerCamelCase : int = 10 , _lowerCamelCase : int = 1000 , _lowerCamelCase : bool = True):
assert (
isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerC... | 333 | 1 |
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome is truly tiny -
# all files ~60KB. As compared to ... | 333 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies # noqa: E402
# This is... | 333 | 1 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
UpperCamelCase = {
'... | 333 | from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils impo... | 333 | 1 |
import os
import numpy
import onnx
def lowercase_ ( _lowerCamelCase : List[Any] , _lowerCamelCase : List[Any]):
lowercase__ : str = a.name
lowercase__ : str = b.name
lowercase__ : Any = ""
lowercase__ : Optiona... | 333 | import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : Any , _lowerCamelCase : str):
lowercase__ : Optional[Any] = AutoConfig.from_pretrain... | 333 | 1 |
from __future__ import annotations
import math
class snake_case_ :
def __init__( self : List[Any] , lowercase_ : int ) -> None:
lowercase__ : Tuple = size
# approximate the overall size of segment tree with given value
low... | 333 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pil... | 333 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer... | 333 | class snake_case_ :
def __init__( self : int ) -> Optional[int]:
lowercase__ : Optional[int] = 0
lowercase__ : List[str] = 0
lowercase__ : Any = {}
def __UpperCamelCase ( self : Dict ... | 333 | 1 |
class snake_case_ :
def __init__( self : Optional[Any] , lowercase_ : int ) -> Any:
lowercase__ : Optional[int] = n
lowercase__ : List[str] = [None] * self.n
lowercase__ : Tuple = 0 # index of the first ... | 333 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
... | 333 | 1 |
def lowercase_ ( _lowerCamelCase : list[int] , _lowerCamelCase : list[int]):
# Check if the input is valid
if not len(_lowerCamelCase) == len(_lowerCamelCase) == 3:
raise ValueError("Please enter a valid equation.")
if equationa[0] == equationa[1] == equationa[0]... | 333 | def lowercase_ ( _lowerCamelCase : int = 1 , _lowerCamelCase : int = 1000):
lowercase__ : Union[str, Any] = 1
lowercase__ : int = 0
for divide_by_number in range(_lowerCamelCase , digit + 1):
lowercase__ : list[int] = ... | 333 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 333 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diff... | 333 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase = {
'''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
'''tokenization_canine''': ['''Ca... | 333 | import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, Par... | 333 | 1 |
class snake_case_ :
def __init__( self : List[Any] , lowercase_ : str = "" , lowercase_ : bool = False ) -> None:
# Mapping from the first character of the prefix of the node
lowercase__ : dict[str, RadixNode] = {}
... | 333 | from ..utils import DummyObject, requires_backends
class snake_case_ ( metaclass=__A ):
__A : List[Any] = ["flax"]
def __init__( self : Optional[int] , *lowercase_ : Optional[int] , **lowercase_ : List[Any] ) -> Tuple:
... | 333 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required... | 333 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE model... | 333 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''s-JoL/Open-Llama-V1''': '''https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json''',
}
class snake_case_ ( __... | 333 | def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
while a != 0:
lowercase__ , lowercase__ : Dict = b % a, a
return b
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
if gcd(_lowerC... | 333 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case_ ( __A ):
__A : Any = ["image_processor", "tokenizer"]
__A : List[Any] = "CLIPImageProcessor"
__A : List[Any] ... | 333 | import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import... | 333 | 1 |
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive")
lowercase__ : Tuple = str(bin(_lowerCamelCase))[2:] # remove the leading "0b"
lowercase__ : List... | 333 | import argparse
import datetime
def lowercase_ ( _lowerCamelCase : str):
lowercase__ : Optional[Any] = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturda... | 333 | 1 |
import functools
from typing import Any
def lowercase_ ( _lowerCamelCase : str , _lowerCamelCase : list[str]):
# Validation
if not isinstance(_lowerCamelCase , _lowerCamelCase) or len(_lowerCamelCase) == 0:
raise ValueError("the string should be not empty str... | 333 | import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCamelCase = 4
UpperCamelCase = 3
class snake_case_ ( __A ):
pass
... | 333 | 1 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils impo... | 333 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''microsoft/unispeech-large-1500h-cv''': (
'''https://huggingface.co/microsoft/unispeec... | 333 | 1 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class snake_case_ ( yaml.SafeLoader ):
def __UpperCamelCase ( self : Optional[Any] , lowercase_ : List[str] ) -> Union[str, Any]:
lowerca... | 333 | def lowercase_ ( _lowerCamelCase : list):
for i in range(len(_lowerCamelCase) - 1 , 0 , -1):
lowercase__ : int = False
for j in range(_lowerCamelCase , 0 , -1):
if unsorted[j] < unsorted[j - 1]:
lowercase__ , ... | 333 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''distilbert-base-uncased''': '''h... | 333 | import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_sco... | 333 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase = {
'''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
'''tokenization_roc_bert''':... | 333 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Mask2FormerConfig''',
],
... | 333 | 1 |
from __future__ import annotations
from typing import Any
def lowercase_ ( _lowerCamelCase : list[Any]):
create_state_space_tree(_lowerCamelCase , [] , 0)
def lowercase_ ( _lowerCamelCase : list[Any] , _lowerCamelCase : list[Any] , _lowerCa... | 333 | # Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def lowercase_ ( _lowerCamelCase : List[str]):
return 1 / (1 + np.exp(-z))
def lowercase_ ... | 333 | 1 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''nielsr/canine-s''': 2048,
}
# Unicode defines 1,114,112 total “codep... | 333 | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__A )
class snake_case_ ( __A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output f... | 333 | 1 |
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
UpperCamelCase = logging.get_logger(__name__)
def ... | 333 | def lowercase_ ( _lowerCamelCase : int = 10 , _lowerCamelCase : int = 1000 , _lowerCamelCase : bool = True):
assert (
isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerC... | 333 | 1 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Con... | 333 | import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies # noqa: E402
# This is... | 333 | 1 |
import requests
from bsa import BeautifulSoup
def lowercase_ ( _lowerCamelCase : str = "AAPL"):
lowercase__ : int = f'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
lowercase__ : Optional[Any] = BeautifulSoup(requests.get(_lowerCamelCase).text ... | 333 | from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils impo... | 333 | 1 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = [
['''attention''', '''attn'''],
... | 333 | import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : Any , _lowerCamelCase : str):
lowercase__ : Optional[Any] = AutoConfig.from_pretrain... | 333 | 1 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case_ ( __A ):
__A : Dict = (DDIMParallelScheduler,)
__A : int = (("eta", 0.0), ("num_inference_steps", 50))
def __UpperCa... | 333 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pil... | 333 | 1 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : Optional[int]=None):
lowercase__ : int = None
if to... | 333 | class snake_case_ :
def __init__( self : int ) -> Optional[int]:
lowercase__ : Optional[int] = 0
lowercase__ : List[str] = 0
lowercase__ : Any = {}
def __UpperCamelCase ( self : Dict ... | 333 | 1 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.... | 333 | import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
... | 333 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.ut... | 333 | def lowercase_ ( _lowerCamelCase : int = 1 , _lowerCamelCase : int = 1000):
lowercase__ : Union[str, Any] = 1
lowercase__ : int = 0
for divide_by_number in range(_lowerCamelCase , digit + 1):
lowercase__ : list[int] = ... | 333 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''shi-labs/nat-mini-in1k-224''':... | 333 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diff... | 333 | 1 |
from __future__ import annotations
class snake_case_ :
def __init__( self : Optional[Any] , lowercase_ : list[list[int]] ) -> Dict:
lowercase__ : Optional[Any] = TypeError(
"Matrices must be formed from a list of zero or more lis... | 333 | import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, Par... | 333 | 1 |
import numpy as np
from PIL import Image
def lowercase_ ( _lowerCamelCase : np.ndarray , _lowerCamelCase : int , _lowerCamelCase : int):
lowercase__ : str = np.array(_lowerCamelCase)
if arr.shape[0] != arr.shape[1]:
raise ValueError("The inp... | 333 | from ..utils import DummyObject, requires_backends
class snake_case_ ( metaclass=__A ):
__A : List[Any] = ["flax"]
def __init__( self : Optional[int] , *lowercase_ : Optional[int] , **lowercase_ : List[Any] ) -> Tuple:
... | 333 | 1 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_... | 333 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE model... | 333 | 1 |
def lowercase_ ( _lowerCamelCase : Union[str, Any]):
lowercase__ : List[Any] = []
lowercase__ : Any = set({"(", "[", "{"})
lowercase__ : Any = set({")", "]", "}"})
lowercase__ : Any = {"{": "}", "[": "]", "(": ")"}
fo... | 333 | def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
while a != 0:
lowercase__ , lowercase__ : Dict = b % a, a
return b
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
if gcd(_lowerC... | 333 | 1 |
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def lowercase_ ( _lowerCamelCase : List[str]):
return 1 / (1 + np.exp(-z))
def lowercase_ ... | 333 | import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from transformers import... | 333 | 1 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCamelCase = 4
UpperCamelCase = 3
class snake_case_ ( __A ):
pass
... | 333 | import argparse
import datetime
def lowercase_ ( _lowerCamelCase : str):
lowercase__ : Optional[Any] = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturda... | 333 | 1 |
import argparse
import datetime
def lowercase_ ( _lowerCamelCase : str):
lowercase__ : Optional[Any] = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturda... | 333 | import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
UpperCamelCase = 4
UpperCamelCase = 3
class snake_case_ ( __A ):
pass
... | 333 | 1 |
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