code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import string
from math import logaa
def lowercase ( __snake_case : str , __snake_case : str ):
lowercase_ : Union[str, Any] = document.translate(
str.maketrans('''''' , '''''' , string.punctuation ) ).replace(... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A : Union[str, Any] = {}
try:
if not is_s... | 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : str , __snake_case : str ):
lowercase_ : int = len(__snake_case )
lowercase_ : int = len(__snake_case )
lowercase_ : int = (
first_str_length if first_str_length... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divisor for di... | 33 | 1 |
"""simple docstring"""
import functools
def lowercase ( __snake_case : str , __snake_case : str ):
lowercase_ : int = len(__snake_case )
lowercase_ : Tuple = len(__snake_case )
@functools.cache
def min_distance(__snake_case ... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : Optional[int] ):
lowercase_ : int = 0
lowercase_ : Optional[Any] = len(__snake_case )
for i in range(n - 1 ):
for j in range(i + 1 , __snake_case ):
if arr[i] > arr[j]:
... | 33 | 1 |
"""simple docstring"""
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'''kwargs, expected''' , [
({'''num_shards''': 0, '''max_num_jobs''': 1}, []),
({'''num_sha... | 33 |
"""simple docstring"""
__A : Any = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''':... | 33 | 1 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__A : List[str] = '''examples/'''
__A : int = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : List[Any] = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''M... | 33 | 1 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_model... | 33 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__A : List[str] = '''examples/'''
__A : int = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
... | 33 | 1 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class _UpperCAmelCase ( datasets.BuilderConfig ):
... | 33 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase ( __snake_case : str , __snake_case : str , __snake_case : Optional[str] = None ):
if version.par... | 33 | 1 |
"""simple docstring"""
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _UpperCAmelCase ( _A ):
SCREAMING_SNAKE_CASE_ : List[Any] = ""
... | 33 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_v... | 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : int , __snake_case : int ):
return x if y == 0 else greatest_common_divisor(__snake_case , x % y )
def lowercase ( __snake_case : int , __snake_case : int ):
return (x * y) // great... | 33 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
__A : Dict = '''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that ... | 33 | 1 |
"""simple docstring"""
import argparse
import copy
def lowercase ( __snake_case : Any ):
lowercase_ : Any = {}
with open(__snake_case ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
lowercase_ : Any ... | 33 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 33 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( __snake_case : float , __snake_case : float , __snake_case : float ):
if days_between_payments <= 0:
raise ValueError('''days_between_payments must be > 0''' )
if daily_interes... | 33 |
"""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
| 33 | 1 |
"""simple docstring"""
import collections
import importlib.util
import os
import re
from pathlib import Path
__A : int = '''src/transformers'''
# Matches is_xxx_available()
__A : Optional[int] = re.compile(R'''is\_([a-z_]*)_available()''')
# Catches a one-l... | 33 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWit... | 33 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
def lowercase ( __snake_case : Union[tf.Tensor, np.ndarray] ):
... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : list[int] ):
lowercase_ : List[Any] = len(__snake_case )
for i in range(__snake_case ):
for j in range(i + 1 , __snake_case ):
if numbers[j] < numbers[i]:
lowercase_ , lower... | 33 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_con... | 33 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcess... | 33 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
__A : Tuple = {
'''configuration_trocr''': ['''TROCR... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0 ):
lowercase_ : str = 0
lowercase_ : List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
... | 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divisor for di... | 33 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__A : str = argparse.ArgumentParser()
parser.add_ar... | 33 | 1 |
"""simple docstring"""
import functools
def lowercase ( __snake_case : list[int] , __snake_case : list[int] ):
# Validation
if not isinstance(__snake_case , __snake_case ) or not all(isinstance(__snake_case , __snake_case ) for day in days ):
rai... | 33 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
... | 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0_0 ):
lowercase_ , lowercase_ : str = 1, 1
lowercase_ : List[str] = 2
while True:
lowercase_ : Tuple = 0
lowercase_ : List[Any] = ... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0_0 ):
lowercase_ , lowercase_ : str = 1, 1
lowercase_ : List[str] = 2
while True:
lowercase_ : Tuple = 0
lowercase_ : List[Any] = ... | 33 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _UpperCAmelCase ( _A , unittest.TestCase ):
... | 33 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : Union[str, Any] = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/ma... | 33 | 1 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
__A : int = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def lowercase ( ):
lowercase_ : Optional[Any] = os.path.dirname(os.path.realpath(__snake_case )... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if n == 1 or not isinstance(__snake_case , __snake_case ):
return 0
elif n == 2:
return 1
else:
lowercase_ : Dict = [0, 1]
for i in range(2 , n + 1 ):
sequence.ap... | 33 | 1 |
"""simple docstring"""
class _UpperCAmelCase : # Public class to implement a graph
def __init__( self : Optional[int] , A : int , A : int , A : list[list[bool]] ) -> None:
lowercase_ : Union[str, An... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__A : List[str] = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 33 | 1 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
... | 33 |
"""simple docstring"""
from __future__ import annotations
__A : List[Any] = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
__A : str = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def lowercase ( __snake_case : list[floa... | 33 | 1 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A : Union[str, Any] = {}
try:
if not is_s... | 33 | 1 |
"""simple docstring"""
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForI... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divisor for di... | 33 | 1 |
"""simple docstring"""
from __future__ import annotations
import requests
__A : Optional[Any] = set(
'''approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : Optional[int] ):
lowercase_ : int = 0
lowercase_ : Optional[Any] = len(__snake_case )
for i in range(n - 1 ):
for j in range(i + 1 , __snake_case ):
if arr[i] > arr[j]:
... | 33 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def lowercase ( __snake_case : Sequence[float] , __snake_case : bool = False ):
if not arr:
return 0
lowercase_ : List[str] = 0 if allow_empty_subarrays else float('''-inf''' )
l... | 33 |
"""simple docstring"""
__A : Any = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''':... | 33 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A : List[str] = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : List[Any] = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''M... | 33 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : int = {
'''s-JoL/Open-Llama-V1''': '''https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/confi... | 33 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__A : List[str] = '''examples/'''
__A : int = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
... | 33 | 1 |
"""simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
__A : List[Any] = '''\
@inproceedings{wang2019glue,
title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Und... | 33 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase ( __snake_case : str , __snake_case : str , __snake_case : Optional[str] = None ):
if version.par... | 33 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
class _UpperCAmelCase ( _A ):
SCREAMING_SNAKE_CASE_ : int = "bert-generation"
def __init__( self : List[Any] , A : Optional[int]=5_... | 33 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_v... | 33 | 1 |
"""simple docstring"""
from __future__ import annotations
__A : List[Any] = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
__A : str = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def lowercase ( __snake_case : list[floa... | 33 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
__A : Dict = '''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that ... | 33 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__A : List[Any] = {
'''configuration_gpt_neo''': ['''GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoConfig'''... | 33 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 33 | 1 |
"""simple docstring"""
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import log... | 33 |
"""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
| 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : int , __snake_case : int ):
return 1 if input_a == input_a else 0
def lowercase ( ):
assert xnor_gate(0 , 0 ) == 1
assert xnor_gate(0 , 1 ) == 0
assert xnor_gate(1 , 0 ) == 0
... | 33 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWit... | 33 | 1 |
"""simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A : Any = [
'''Prosecutor: "No videos were used in the crash investigation" German pa... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : list[int] ):
lowercase_ : List[Any] = len(__snake_case )
for i in range(__snake_case ):
for j in range(i + 1 , __snake_case ):
if numbers[j] < numbers[i]:
lowercase_ , lower... | 33 | 1 |
"""simple docstring"""
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _UpperCAmelCase :
def __init__( self : Optional[Any] , A : List[Any] , A : int , A : int )... | 33 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcess... | 33 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _UpperCAmelCase ( _A , unittest.TestCase ... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0 ):
lowercase_ : str = 0
lowercase_ : List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
... | 33 | 1 |
"""simple docstring"""
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
__A : Any = logging.get_logger(__name__)
class _Uppe... | 33 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__A : str = argparse.ArgumentParser()
parser.add_ar... | 33 | 1 |
"""simple docstring"""
from functools import reduce
__A : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050... | 33 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
... | 33 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenizati... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0_0 ):
lowercase_ , lowercase_ : str = 1, 1
lowercase_ : List[str] = 2
while True:
lowercase_ : Tuple = 0
lowercase_ : List[Any] = ... | 33 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A : str ... | 33 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : Union[str, Any] = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/ma... | 33 | 1 |
"""simple docstring"""
import sys
__A : str = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if n == 1 or not isinstance(__snake_case , __snake_case ):
return 0
elif n == 2:
return 1
else:
lowercase_ : Dict = [0, 1]
for i in range(2 , n + 1 ):
sequence.ap... | 33 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A : Union[str, Any] = {
'''config... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__A : List[str] = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 33 | 1 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
... | 33 |
"""simple docstring"""
from __future__ import annotations
__A : List[Any] = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
__A : str = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def lowercase ( __snake_case : list[floa... | 33 | 1 |
"""simple docstring"""
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class _UpperCAmelCase ( _A ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = "EncodecFeatureEx... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A : Union[str, Any] = {}
try:
if not is_s... | 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : int , __snake_case : int ):
return int((input_a, input_a).count(0 ) != 0 )
def lowercase ( ):
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0 , 1 ) == 1
assert nand_gate(1 , 0... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divisor for di... | 33 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
fro... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : Optional[int] ):
lowercase_ : int = 0
lowercase_ : Optional[Any] = len(__snake_case )
for i in range(n - 1 ):
for j in range(i + 1 , __snake_case ):
if arr[i] > arr[j]:
... | 33 | 1 |
"""simple docstring"""
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_... | 33 |
"""simple docstring"""
__A : Any = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''':... | 33 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from d... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : List[Any] = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''M... | 33 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _UpperCAm... | 33 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__A : List[str] = '''examples/'''
__A : int = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
... | 33 | 1 |
"""simple docstring"""
from math import factorial
def lowercase ( __snake_case : int = 2_0 ):
lowercase_ : Tuple = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
lowercase_ : Optional[Any] = n //... | 33 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase ( __snake_case : str , __snake_case : str , __snake_case : Optional[str] = None ):
if version.par... | 33 | 1 |
"""simple docstring"""
from typing import Dict, Optional
import numpy as np
import datasets
__A : Tuple = '''
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 tru... | 33 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_v... | 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : list[int] ):
lowercase_ : List[Any] = len(__snake_case )
for i in range(__snake_case ):
for j in range(i + 1 , __snake_case ):
if numbers[j] < numbers[i]:
lowercase_ , lower... | 33 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
__A : Dict = '''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that ... | 33 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE... | 33 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 33 | 1 |
"""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 TensorF... | 33 |
"""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
| 33 | 1 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class _UpperCAmelCase ( nn.Module ):
SCREAMING_SNAKE_CASE_ : int
SCREAMING_SNAKE_CASE_ : jnp.dtype = jnp.floataa
def A ( self : ... | 33 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWit... | 33 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subpr... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : list[int] ):
lowercase_ : List[Any] = len(__snake_case )
for i in range(__snake_case ):
for j in range(i + 1 , __snake_case ):
if numbers[j] < numbers[i]:
lowercase_ , lower... | 33 | 1 |
"""simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic... | 33 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcess... | 33 | 1 |
"""simple docstring"""
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transfor... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0 ):
lowercase_ : str = 0
lowercase_ : List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
... | 33 | 1 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor... | 33 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__A : str = argparse.ArgumentParser()
parser.add_ar... | 33 | 1 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
__A : int = {'''UserAgent''': UserAgent().random}
def lowercase ( __snake_case : Optional[int] ):
... | 33 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
... | 33 | 1 |
"""simple docstring"""
import torch
from torch import nn
class _UpperCAmelCase ( nn.Module ):
def __init__( self : int , A : Union[str, Any] , A : Optional[Any] , A : Tuple , A : ... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0_0 ):
lowercase_ , lowercase_ : str = 1, 1
lowercase_ : List[str] = 2
while True:
lowercase_ : Tuple = 0
lowercase_ : List[Any] = ... | 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0 ):
lowercase_ : str = 0
lowercase_ : List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
... | 33 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : Union[str, Any] = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/ma... | 33 | 1 |
"""simple docstring"""
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
__A : str = logging.get_logger(__name__)
class _UpperCAmelCase ... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if n == 1 or not isinstance(__snake_case , __snake_case ):
return 0
elif n == 2:
return 1
else:
lowercase_ : Dict = [0, 1]
for i in range(2 , n + 1 ):
sequence.ap... | 33 | 1 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcess... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__A : List[str] = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 33 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : int = {}
class _UpperCAmelCase ( _A ):
SCREAMING_SNAKE_CASE_ : Any ... | 33 |
"""simple docstring"""
from __future__ import annotations
__A : List[Any] = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
__A : str = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def lowercase ( __snake_case : list[floa... | 33 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( __snake_case : list[float] ):
lowercase_ : str = 0.00
lowercase_ : str = 0
for resistor in resistors:
if resistor <= 0:
lowercase_ : str = ... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A : Union[str, Any] = {}
try:
if not is_s... | 33 | 1 |
"""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 DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
f... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divisor for di... | 33 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__A : List[str] = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : Optional[int] ):
lowercase_ : int = 0
lowercase_ : Optional[Any] = len(__snake_case )
for i in range(n - 1 ):
for j in range(i + 1 , __snake_case ):
if arr[i] > arr[j]:
... | 33 | 1 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('''>=''', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint ... | 33 |
"""simple docstring"""
__A : Any = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''':... | 33 | 1 |
"""simple docstring"""
import sys
def lowercase ( __snake_case : Dict ):
lowercase_ : int = len(__snake_case )
lowercase_ : Tuple = [[0 for x in range(__snake_case )] for x in range(__snake_case )]
lowercase_ : int = [[0 fo... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : List[Any] = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''M... | 33 | 1 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase ( __snake_case : str , __snake_case : str , __snake_case : Optional[str] = None ):
if version.par... | 33 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__A : List[str] = '''examples/'''
__A : int = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
... | 33 | 1 |
"""simple docstring"""
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import... | 33 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase ( __snake_case : str , __snake_case : str , __snake_case : Optional[str] = None ):
if version.par... | 33 | 1 |
"""simple docstring"""
from typing import Any
class _UpperCAmelCase :
def __init__( self : Optional[Any] , A : Any ) -> Tuple:
lowercase_ : List[Any] = data
lowercase_ : Union[str, Any] ... | 33 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_v... | 33 | 1 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_... | 33 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
__A : Dict = '''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that ... | 33 | 1 |
"""simple docstring"""
from collections import Counter
from timeit import timeit
def lowercase ( __snake_case : str = "" , ):
return sum(c % 2 for c in Counter(input_str.replace(''' ''' , '''''' ).lower() ).values() ) < 2
def lowercase ( __snak... | 33 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 33 | 1 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVec... | 33 |
"""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
| 33 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A : Any = {'''configuration_deit''': ['''DEIT_PRETRAINED_CONFIG_AR... | 33 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWit... | 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : float , __snake_case : float ):
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(125.50, 0.05) = }""")
| 33 |
"""simple docstring"""
def lowercase ( __snake_case : list[int] ):
lowercase_ : List[Any] = len(__snake_case )
for i in range(__snake_case ):
for j in range(i + 1 , __snake_case ):
if numbers[j] < numbers[i]:
lowercase_ , lower... | 33 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A : Union[str, Any] = logging.get_... | 33 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcess... | 33 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A : Dict = {
'''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''],
... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0 ):
lowercase_ : str = 0
lowercase_ : List[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
... | 33 | 1 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
__A : Dict = '''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that ... | 33 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__A : str = argparse.ArgumentParser()
parser.add_ar... | 33 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( __snake_case : int ):
lowercase_ : Tuple = [True] * limit
lowercase_ : List[str] = False
lowercase_ : Tuple = False
lowercase_ : List[str] ... | 33 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
... | 33 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class _UpperCAmelCase :
SCREAMING_SNAKE_CASE_ : int
SCREAMING_SNAKE_CASE_ : TreeNode | None = None
... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int = 1_0_0_0 ):
lowercase_ , lowercase_ : str = 1, 1
lowercase_ : List[str] = 2
while True:
lowercase_ : Tuple = 0
lowercase_ : List[Any] = ... | 33 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : Union[str, Any] = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/ma... | 33 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : Union[str, Any] = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/ma... | 33 | 1 |
"""simple docstring"""
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class _UpperCAmelCase ( _A ):
SCREAMING_SNAKE_CASE_ : Optional[int] = CustomTokenizer
pass
| 33 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if n == 1 or not isinstance(__snake_case , __snake_case ):
return 0
elif n == 2:
return 1
else:
lowercase_ : Dict = [0, 1]
for i in range(2 , n + 1 ):
sequence.ap... | 33 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
__A : Dict = logging.get_logger(__name__)
class _UpperCAmelCase ( _A ):
def __init__( self : ... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__A : List[str] = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 33 | 1 |
"""simple docstring"""
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
__A : Union[str, Any] = 4
__A : List[Any] ... | 33 |
"""simple docstring"""
from __future__ import annotations
__A : List[Any] = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
__A : str = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def lowercase ( __snake_case : list[floa... | 33 | 1 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionMod... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A : Union[str, Any] = {}
try:
if not is_s... | 33 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A : List[Any] = logging.get_logger... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : int ):
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must be positive''' )
return sum(
divisor for di... | 33 | 1 |
"""simple docstring"""
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Any = logging.get_logger(__name__)
__A : List[str] = {
'''huggingface/autoformer-tourism-monthly''': '''https://... | 33 |
"""simple docstring"""
def lowercase ( __snake_case : Optional[int] ):
lowercase_ : int = 0
lowercase_ : Optional[Any] = len(__snake_case )
for i in range(n - 1 ):
for j in range(i + 1 , __snake_case ):
if arr[i] > arr[j]:
... | 33 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from... | 33 |
"""simple docstring"""
__A : Any = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''':... | 33 | 1 |
"""simple docstring"""
def lowercase ( __snake_case : int , __snake_case : int , __snake_case : list[list[int]] ):
def update_area_of_max_square(__snake_case : int , __snake_case : int ) -> int:
# BASE CASE
if row >= rows or col >= cols:
... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : List[Any] = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''M... | 33 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
... | 33 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__A : List[str] = '''examples/'''
__A : int = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
... | 33 | 1 |
"""simple docstring"""
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def lowercase ( __snake_case : List[str] ):
monkeypatch.setattr('''datasets.utils.deprecation_utils._emitted_deprecation_warnings''' , set() )
... | 33 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowercase ( __snake_case : str , __snake_case : str , __snake_case : Optional[str] = None ):
if version.par... | 33 | 1 |
"""simple docstring"""
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch impo... | 33 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_v... | 33 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : List[Any] = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''M... | 33 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
__A : Dict = '''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that ... | 33 | 1 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def lowercase ( __snake_case : str ):
def decorator(__snake_case : int ):
lowercase_ : int = getattr(__snake_case , '''handle_key''' , [] )
ha... | 33 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 33 | 1 |
"""simple docstring"""
__A : Any = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''':... | 33 |
"""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
| 33 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, ... | 33 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWit... | 33 | 1 |
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