code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
def _UpperCAmelCase ( a : Optional[int] = 1_0_0_0 ) -> Any:
"""simple docstring"""
lowercase_ : Optional[int] = 3
lowercase_ : List[Any] = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
... | 701 |
'''simple docstring'''
def _UpperCAmelCase ( a : int , a : int ) -> int:
"""simple docstring"""
while second != 0:
lowercase_ : Any = first & second
first ^= second
lowercase_ : List[str] = c << 1
... | 7 | 0 |
'''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,
)
A: Dict = pytest.mark.integration
@pytest.mark.parametrize('path'... | 702 |
'''simple docstring'''
class __magic_name__ :
"""simple docstring"""
def __init__( self , _lowercase ) -> Union[str, Any]:
lowercase_ : Dict = n
lowercase_ : Dict = [None] * self.n
lowercase_ : Tuple ... | 7 | 0 |
'''simple docstring'''
import os
import sys
import unittest
A: List[Any] = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_du... | 703 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import ... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
from cmath import sqrt
def _UpperCAmelCase ( a : Any , a : Any , a : Tuple ) -> tuple[complex, complex]:
"""simple docstring"""
if a == 0:
raise ValueError('Coefficient \'a\' must not b... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
A: int = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"convert": ["e... | 7 | 0 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
A: Union[str, Any] = [
"good first issue",
"good second issue",
"good difficult issue",
"enhancement",
"new pipeline/model",
"new scheduler",
"wip",
]
def _UpperCAmel... | 705 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
A: Any ... | 7 | 0 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vis... | 706 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A: int = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerCon... | 7 | 0 |
'''simple docstring'''
import warnings
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 __magic_name__ ... | 707 |
'''simple docstring'''
def _UpperCAmelCase ( a : str ) -> str:
"""simple docstring"""
lowercase_ : Dict = 0
# if input_string is "aba" than new_input_string become "a|b|a"
lowercase_ : Dict = ''
lowercase_ : Any = ... | 7 | 0 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .s... | 708 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __magi... | 7 | 0 |
'''simple docstring'''
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
M... | 709 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
... | 7 | 0 |
'''simple docstring'''
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
f... | 710 |
'''simple docstring'''
def _UpperCAmelCase ( a : list ) -> list:
"""simple docstring"""
for i in range(len(a ) - 1 , 0 , -1 ):
lowercase_ : Any = False
for j in range(a , 0 , -1 ):
... | 7 | 0 |
'''simple docstring'''
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def _UpperCAmelCase ( a : List[str] , a : Optional[int] , a : List[str] , a : Optional[Any] , a : List[str] ) -> Dict:... | 711 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=UpperCAmelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = ['transformers', 'torch', 'note_seq']
def __init__( self , *_lowercase ... | 7 | 0 |
import argparse
import os
import re
A: Optional[Any] = "src/diffusers"
# Pattern that looks at the indentation in a line.
A: Optional[Any] = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
A: Optional[int] = re.compile(r"^\s*\"([^\"]+)\... | 712 |
'''simple docstring'''
def _UpperCAmelCase ( a : str , a : str ) -> float:
"""simple docstring"""
def get_matched_characters(a : str , a : str ) -> str:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple ... | 7 | 0 |
def _UpperCAmelCase ( a : str ) -> str:
"""simple docstring"""
if not all(char in '01' for char in bin_string ):
raise ValueError('Non-binary value was passed to the function' )
if not bin_string:
raise ValueError('Empty string was passed... | 713 |
'''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( a : int = 4 ) -> list[list[int]]:
"""simple docstring"""
lowercase_ : Tuple = abs(a ) or 4
return [[1 + x + y * row_size for x in range(a )] for y in range(a ... | 7 | 0 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
A: List[Any] = get_tests_dir("fixtures/test_sentence... | 714 |
'''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( a : Dict , a : Optional[int] , a : Tuple ) -> Optional[int]:
"""simple docstring"""
lowercase_ : Any = {
'en':... | 7 | 0 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _UpperCAmelCase ( a : Union[str, Any] , a : Union[str, Any] , a : List[str] ) -> List[Any]:
"""simple docstring"""
lowercase_ : Optional[Any] = 0
if s... | 715 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
A: Tuple = l... | 7 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize... | 716 |
'''simple docstring'''
import os
from distutils.util import strtobool
def _UpperCAmelCase ( a : Any , a : int ) -> Any:
"""simple docstring"""
for e in env_keys:
lowercase_ : Optional[Any] = int(os.environ.get(a , -1 ) ... | 7 | 0 |
'''simple docstring'''
import math
def _UpperCAmelCase ( a : list , a : int ) -> int:
"""simple docstring"""
lowercase_ : Optional[int] = len(a_ )
lowercase_ : Optional[Any] = int(math.floor(math.s... | 717 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
A: int = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two class... | 7 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
A: Any = False
class __magic_name__ ( unittest.TestC... | 718 |
'''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
A: Dict = logging.get_logger(__name__)
A: Optional[Any] ... | 7 | 0 |
class __magic_name__ :
"""simple docstring"""
def __init__( self , _lowercase , _lowercase ) -> Union[str, Any]:
lowercase_ : int = name
lowercase_ : int = val
def __str__( self ) -> Any:
... | 719 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A: int = logging.get_logger(__name__)
A: int = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}
cl... | 7 | 0 |
'''simple docstring'''
import math
import tensorflow as tf
from packaging import version
def _UpperCAmelCase ( a : List[Any] ) -> Dict:
"""simple docstring"""
lowercase_ : int = tf.convert_to_tensor(__UpperCamelCase )
lowercase_ : int ... | 720 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __magic_name__ ( unittest.TestCase ):
"""simple docstring"""
def lowerCamelCase__ ( self ) -> Optional[Any]:
lowercase_ : ... | 7 | 0 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from to... | 721 |
'''simple docstring'''
import argparse
A: List[Any] = "docs/source/_static/js/custom.js"
def _UpperCAmelCase ( a : Optional[Any] ) -> Optional[Any]:
"""simple docstring"""
with open(a , encoding='utf-8' , newline='\n' ) as f:
... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
class __magic_name__ :
"""simple docstring"""
def __init__( self , _lowercase , _lowercase ) -> List[Any]:
lowercase_ , lowercase_ : Tuple = text, pattern
lowe... | 700 |
'''simple docstring'''
def _UpperCAmelCase ( a : list[list[float]] ) -> list[list[float]]:
"""simple docstring"""
lowercase_ : list[list[float]] = []
for data in source_data:
for i, el in enumerate(a ):
if len(a ) <... | 7 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A: Union[str, Any] = logging.get_logger(__name__)
A: Dict = {
"roberta-base": "h... | 701 |
'''simple docstring'''
def _UpperCAmelCase ( a : int , a : int ) -> int:
"""simple docstring"""
while second != 0:
lowercase_ : Any = first & second
first ^= second
lowercase_ : List[str] = c << 1
... | 7 | 0 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
f... | 702 |
'''simple docstring'''
class __magic_name__ :
"""simple docstring"""
def __init__( self , _lowercase ) -> Union[str, Any]:
lowercase_ : Dict = n
lowercase_ : Dict = [None] * self.n
lowercase_ : Tuple ... | 7 | 0 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
... | 703 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import ... | 7 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( a : int = 4_0_0_0_0_0_0 ) -> Any:
"""simple docstring"""
lowercase_ : Dict = [0, 1]
lowercase_ : str = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if ... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
A: int = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"convert": ["e... | 7 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
A: int = logging.get_logger(__name_... | 705 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
A: Any ... | 7 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _UpperCAmelCase ( a : Any , a : Optional[Any] , a : Optional[Any] , a : List[str] , a : ... | 706 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A: int = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerCon... | 7 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A: Tuple = logging.get_logger(__name__)
A: Union[str, Any] = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __magic_name__ ... | 707 |
'''simple docstring'''
def _UpperCAmelCase ( a : str ) -> str:
"""simple docstring"""
lowercase_ : Dict = 0
# if input_string is "aba" than new_input_string become "a|b|a"
lowercase_ : Dict = ''
lowercase_ : Any = ... | 7 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import Tokeni... | 708 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __magi... | 7 | 0 |
'''simple docstring'''
A: str = {
0: '''0''',
1: '''1''',
2: '''2''',
3: '''3''',
4: '''4''',
5: '''5''',
6: '''6''',
7: '''7''',
8: '''8''',
9: '''9''',
1_0: '''a''',
1_1: '''b''',
1_2: '''c''',
1_3: '''d''',
1_4: '''e''',
1_5: '''f''... | 709 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configu... | 710 |
'''simple docstring'''
def _UpperCAmelCase ( a : list ) -> list:
"""simple docstring"""
for i in range(len(a ) - 1 , 0 , -1 ):
lowercase_ : Any = False
for j in range(a , 0 , -1 ):
... | 7 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class __magic_name__ ( UpperCam... | 711 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=UpperCAmelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = ['transformers', 'torch', 'note_seq']
def __init__( self , *_lowercase ... | 7 | 0 |
def _UpperCAmelCase ( a : int , a : Optional[Any] ) -> str:
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise ValueError('iterations must be defined as integers' )
if not isinstance(__UpperCamelCase ... | 712 |
'''simple docstring'''
def _UpperCAmelCase ( a : str , a : str ) -> float:
"""simple docstring"""
def get_matched_characters(a : str , a : str ) -> str:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple ... | 7 | 0 |
from __future__ import annotations
def _UpperCAmelCase ( a : int ) -> Dict:
"""simple docstring"""
lowercase_ : List[Any] = len(a )
# We need to create solution object to save path.
lowercase_ : Optional[Any] = [[0 for _ in ... | 713 |
'''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( a : int = 4 ) -> list[list[int]]:
"""simple docstring"""
lowercase_ : Tuple = abs(a ) or 4
return [[1 + x + y * row_size for x in range(a )] for y in range(a ... | 7 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A: str = {}
try:
if not is_sentencepiece_available():
rais... | 714 |
'''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( a : Dict , a : Optional[int] , a : Tuple ) -> Optional[int]:
"""simple docstring"""
lowercase_ : Any = {
'en':... | 7 | 0 |
import random
def _UpperCAmelCase ( a : List[Any] ) -> bool:
"""simple docstring"""
lowercase_ : List[Any] = num - 1
lowercase_ : Union[str, Any] = 0
while s % 2 == 0:
lowercase_ : List[Any] = s // 2
... | 715 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
A: Tuple = l... | 7 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A: Dict = {'''configuration_mbart... | 716 |
'''simple docstring'''
import os
from distutils.util import strtobool
def _UpperCAmelCase ( a : Any , a : int ) -> Any:
"""simple docstring"""
for e in env_keys:
lowercase_ : Optional[Any] = int(os.environ.get(a , -1 ) ... | 7 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A: str = {
"configuration_instructblip": [
"INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InstructBlipConfig",
... | 717 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
A: int = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two class... | 7 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from trans... | 718 |
'''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
A: Dict = logging.get_logger(__name__)
A: Optional[Any] ... | 7 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A: Optional[Any] = logging.get_logger(__name__)
A: Any = {
'microsoft/trocr-base-handwritten': (
'https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json'
),
... | 719 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A: int = logging.get_logger(__name__)
A: int = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}
cl... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf,... | 720 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __magic_name__ ( unittest.TestCase ):
"""simple docstring"""
def lowerCamelCase__ ( self ) -> Optional[Any]:
lowercase_ : ... | 7 | 0 |
'''simple docstring'''
from manim import *
class __magic_name__ ( __a ):
"""simple docstring"""
def lowerCamelCase__ ( self ) -> str:
lowercase_ : Any = Rectangle(height=0.5 , width=0.5 )
lowercase_ : Any ... | 721 |
'''simple docstring'''
import argparse
A: List[Any] = "docs/source/_static/js/custom.js"
def _UpperCAmelCase ( a : Optional[Any] ) -> Optional[Any]:
"""simple docstring"""
with open(a , encoding='utf-8' , newline='\n' ) as f:
... | 7 | 0 |
'''simple docstring'''
import random
from typing import Any
def _UpperCAmelCase ( a : Optional[int] ) -> list[Any]:
"""simple docstring"""
for _ in range(len(_SCREAMING_SNAKE_CASE ) ):
lowercase_ : Union[str, Any] = random.randint(0 ... | 700 |
'''simple docstring'''
def _UpperCAmelCase ( a : list[list[float]] ) -> list[list[float]]:
"""simple docstring"""
lowercase_ : list[list[float]] = []
for data in source_data:
for i, el in enumerate(a ):
if len(a ) <... | 7 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def _UpperCAmelCase ( a : int , a : Optional[Any] , a : Optional[Any] ... | 701 |
'''simple docstring'''
def _UpperCAmelCase ( a : int , a : int ) -> int:
"""simple docstring"""
while second != 0:
lowercase_ : Any = first & second
first ^= second
lowercase_ : List[str] = c << 1
... | 7 | 0 |
'''simple docstring'''
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
A: Union[str, Any] = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2... | 702 |
'''simple docstring'''
class __magic_name__ :
"""simple docstring"""
def __init__( self , _lowercase ) -> Union[str, Any]:
lowercase_ : Dict = n
lowercase_ : Dict = [None] * self.n
lowercase_ : Tuple ... | 7 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class __magic_name__ ( _UpperCAmelCase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any] = ["""image_processor""", """feature_extractor"""]
SCREAMING_SNAKE_CASE_ : Lis... | 703 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import ... | 7 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( a : int ) -> Tuple: # noqa: E741
"""simple docstring"""
lowercase_ : List[Any] = len(a_ )
lowercase_ : List[str] = 0
lowercase_ : Union[str, Any] = [0] * n
lower... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
A: int = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"convert": ["e... | 7 | 0 |
'''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 as dist_cp
from tor... | 705 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
A: Any ... | 7 | 0 |
'''simple docstring'''
from math import loga
def _UpperCAmelCase ( a : Optional[Any] ) -> int:
"""simple docstring"""
if a < 0:
raise ValueError('Input value must be a positive integer' )
elif isinstance(lowercase_ , lowercase_ ):
... | 706 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A: int = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerCon... | 7 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A: Optional[int] = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_... | 707 |
'''simple docstring'''
def _UpperCAmelCase ( a : str ) -> str:
"""simple docstring"""
lowercase_ : Dict = 0
# if input_string is "aba" than new_input_string become "a|b|a"
lowercase_ : Dict = ''
lowercase_ : Any = ... | 7 | 0 |
'''simple docstring'''
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils i... | 708 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __magi... | 7 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 709 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
... | 7 | 0 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Tok... | 710 |
'''simple docstring'''
def _UpperCAmelCase ( a : list ) -> list:
"""simple docstring"""
for i in range(len(a ) - 1 , 0 , -1 ):
lowercase_ : Any = False
for j in range(a , 0 , -1 ):
... | 7 | 0 |
'''simple docstring'''
class __magic_name__ :
"""simple docstring"""
def __init__( self ) -> Optional[int]:
lowercase_ : Any = ''
lowercase_ : Union[str, Any] = ''
lowercase_ : Any = []
def lowe... | 711 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=UpperCAmelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = ['transformers', 'torch', 'note_seq']
def __init__( self , *_lowercase ... | 7 | 0 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import Backbone... | 712 |
'''simple docstring'''
def _UpperCAmelCase ( a : str , a : str ) -> float:
"""simple docstring"""
def get_matched_characters(a : str , a : str ) -> str:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple ... | 7 | 0 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A: List[Any] = logging.get_logger(__name__)
... | 713 |
'''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( a : int = 4 ) -> list[list[int]]:
"""simple docstring"""
lowercase_ : Tuple = abs(a ) or 4
return [[1 + x + y * row_size for x in range(a )] for y in range(a ... | 7 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A: Dict = "▁"
A: Any = {"vocab_file": "spiece.model"}
A:... | 714 |
'''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( a : Dict , a : Optional[int] , a : Tuple ) -> Optional[int]:
"""simple docstring"""
lowercase_ : Any = {
'en':... | 7 | 0 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
fr... | 715 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
A: Tuple = l... | 7 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class __mag... | 716 |
'''simple docstring'''
import os
from distutils.util import strtobool
def _UpperCAmelCase ( a : Any , a : int ) -> Any:
"""simple docstring"""
for e in env_keys:
lowercase_ : Optional[Any] = int(os.environ.get(a , -1 ) ... | 7 | 0 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
A: Optional[Any] = lo... | 717 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
A: int = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two class... | 7 | 0 |
'''simple docstring'''
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit,
... | 718 |
'''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
A: Dict = logging.get_logger(__name__)
A: Optional[Any] ... | 7 | 0 |
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_... | 719 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A: int = logging.get_logger(__name__)
A: int = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}
cl... | 7 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def _UpperCAmelCase ( ) -> int:
"""simple docstring"""
lowercase_ : Optional[Any] = ArgumentParser('Diffusers CLI tool' , usage='diffusers-cli <command> [<args>]... | 720 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __magic_name__ ( unittest.TestCase ):
"""simple docstring"""
def lowerCamelCase__ ( self ) -> Optional[Any]:
lowercase_ : ... | 7 | 0 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
f... | 721 |
'''simple docstring'''
import argparse
A: List[Any] = "docs/source/_static/js/custom.js"
def _UpperCAmelCase ( a : Optional[Any] ) -> Optional[Any]:
"""simple docstring"""
with open(a , encoding='utf-8' , newline='\n' ) as f:
... | 7 | 0 |
'''simple docstring'''
def _UpperCAmelCase ( ) -> Tuple:
"""simple docstring"""
lowercase_ : Optional[int] = [3_1, 2_8, 3_1, 3_0, 3_1, 3_0, 3_1, 3_1, 3_0, 3_1, 3_0, 3_1]
lowercase_ : int = 6
lowercase_ : Tuple = 1
lower... | 700 |
'''simple docstring'''
def _UpperCAmelCase ( a : list[list[float]] ) -> list[list[float]]:
"""simple docstring"""
lowercase_ : list[list[float]] = []
for data in source_data:
for i, el in enumerate(a ):
if len(a ) <... | 7 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_ver... | 701 |
'''simple docstring'''
def _UpperCAmelCase ( a : int , a : int ) -> int:
"""simple docstring"""
while second != 0:
lowercase_ : Any = first & second
first ^= second
lowercase_ : List[str] = c << 1
... | 7 | 0 |
'''simple docstring'''
import math
def _UpperCAmelCase ( a : Dict , a : Any ) -> Optional[int]:
"""simple docstring"""
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(SCREAMING_SNAKE_CA... | 702 |
'''simple docstring'''
class __magic_name__ :
"""simple docstring"""
def __init__( self , _lowercase ) -> Union[str, Any]:
lowercase_ : Dict = n
lowercase_ : Dict = [None] * self.n
lowercase_ : Tuple ... | 7 | 0 |
'''simple docstring'''
from math import sqrt
def _UpperCAmelCase ( a : int = 1_0_0_0_0_0_0 ) -> Dict:
"""simple docstring"""
lowercase_ : int = 0
lowercase_ : int = 0
lowercase_ : int
while num_cuboids <= limit:
... | 703 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import ... | 7 | 0 |
'''simple docstring'''
A: Tuple = {
"joule": 1.0,
"kilojoule": 1_0_0_0,
"megajoule": 1_0_0_0_0_0_0,
"gigajoule": 1_0_0_0_0_0_0_0_0_0,
"wattsecond": 1.0,
"watthour": 3_6_0_0,
"kilowatthour": 3_6_0_0_0_0_0,
"newtonmeter": 1.0,
"calorie_nutr": 4_1_8_6.8,
"kiloca... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
A: int = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"convert": ["e... | 7 | 0 |
'''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: int = logging.get_logger(__name__)
A: int = ... | 705 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
A: Any ... | 7 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A: Union[str, Any] = {"configuration_vit_mae": ["VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTM... | 706 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A: int = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerCon... | 7 | 0 |
'''simple docstring'''
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class __magic_name__ :
"""simple docstring"""
def lowerCamelCase__ ( self , _lowercase ) -> Option... | 707 |
'''simple docstring'''
def _UpperCAmelCase ( a : str ) -> str:
"""simple docstring"""
lowercase_ : Dict = 0
# if input_string is "aba" than new_input_string become "a|b|a"
lowercase_ : Dict = ''
lowercase_ : Any = ... | 7 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docst... | 708 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __magi... | 7 | 0 |
'''simple docstring'''
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __magic_name__ ( _A ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = ['image_processor', 'tokenizer']
SCREAM... | 709 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
... | 7 | 0 |
'''simple docstring'''
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def _UpperCAmelCase ( a : Dict = 8 ) -> str:
"""simple docstring"""
lowercase_ : Union[str, Any] = ascii... | 710 |
'''simple docstring'''
def _UpperCAmelCase ( a : list ) -> list:
"""simple docstring"""
for i in range(len(a ) - 1 , 0 , -1 ):
lowercase_ : Any = False
for j in range(a , 0 , -1 ):
... | 7 | 0 |
'''simple docstring'''
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from uti... | 711 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=UpperCAmelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = ['transformers', 'torch', 'note_seq']
def __init__( self , *_lowercase ... | 7 | 0 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
A: List[Any] = ["small", "medium", "large"]
A: int = "lm_head.decoder.weight"
A: Optional[Any] = "lm_head.weight"
def _UpperCAmelCase ( a : Union[str, Any] , a : int ... | 712 |
'''simple docstring'''
def _UpperCAmelCase ( a : str , a : str ) -> float:
"""simple docstring"""
def get_matched_characters(a : str , a : str ) -> str:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple ... | 7 | 0 |
def _UpperCAmelCase ( a : str ) -> Optional[int]:
"""simple docstring"""
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
lowercase_ : int = sorted(string.lower() ... | 713 |
'''simple docstring'''
from __future__ import annotations
def _UpperCAmelCase ( a : int = 4 ) -> list[list[int]]:
"""simple docstring"""
lowercase_ : Tuple = abs(a ) or 4
return [[1 + x + y * row_size for x in range(a )] for y in range(a ... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from trans... | 714 |
'''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( a : Dict , a : Optional[int] , a : Tuple ) -> Optional[int]:
"""simple docstring"""
lowercase_ : Any = {
'en':... | 7 | 0 |
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from .... | 715 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
A: Tuple = l... | 7 | 0 |
'''simple docstring'''
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from ... | 716 |
'''simple docstring'''
import os
from distutils.util import strtobool
def _UpperCAmelCase ( a : Any , a : int ) -> Any:
"""simple docstring"""
for e in env_keys:
lowercase_ : Optional[Any] = int(os.environ.get(a , -1 ) ... | 7 | 0 |
'''simple docstring'''
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 (
... | 717 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
A: int = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two class... | 7 | 0 |
'''simple docstring'''
import os
def _UpperCAmelCase ( a : Optional[int] = "input.txt" ) -> int:
"""simple docstring"""
with open(os.path.join(os.path.dirname(a ) , a ) ) as input_file:
lowercase_ : Optional[Any] = [
... | 718 |
'''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
A: Dict = logging.get_logger(__name__)
A: Optional[Any] ... | 7 | 0 |
def _UpperCAmelCase ( a : int = 1_0_0_0 ) -> List[Any]:
"""simple docstring"""
lowercase_ : Union[str, Any] = 2**power
lowercase_ : List[str] = str(__a )
lowercase_ : Any = list(__a )
lowercase_ : ... | 719 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A: int = logging.get_logger(__name__)
A: int = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}
cl... | 7 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.... | 720 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __magic_name__ ( unittest.TestCase ):
"""simple docstring"""
def lowerCamelCase__ ( self ) -> Optional[Any]:
lowercase_ : ... | 7 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def _UpperCAmelCase ( a : Callable[[int | float], int | float] , a : int | float , a : int | float , a : int = 1_0_0 , ) -> float:
"""simple docstring"""
... | 721 |
'''simple docstring'''
import argparse
A: List[Any] = "docs/source/_static/js/custom.js"
def _UpperCAmelCase ( a : Optional[Any] ) -> Optional[Any]:
"""simple docstring"""
with open(a , encoding='utf-8' , newline='\n' ) as f:
... | 7 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
fro... | 700 |
'''simple docstring'''
def _UpperCAmelCase ( a : list[list[float]] ) -> list[list[float]]:
"""simple docstring"""
lowercase_ : list[list[float]] = []
for data in source_data:
for i, el in enumerate(a ):
if len(a ) <... | 7 | 0 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vis... | 701 |
'''simple docstring'''
def _UpperCAmelCase ( a : int , a : int ) -> int:
"""simple docstring"""
while second != 0:
lowercase_ : Any = first & second
first ^= second
lowercase_ : List[str] = c << 1
... | 7 | 0 |
'''simple docstring'''
import argparse
import os
from accelerate.utils import ComputeEnvironment
from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file # noqa: F401
from .config_utils import _ask_field, _ask_options, _co... | 702 |
'''simple docstring'''
class __magic_name__ :
"""simple docstring"""
def __init__( self , _lowercase ) -> Union[str, Any]:
lowercase_ : Dict = n
lowercase_ : Dict = [None] * self.n
lowercase_ : Tuple ... | 7 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from tran... | 703 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import ... | 7 | 0 |
'''simple docstring'''
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoi... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..utils import _LazyModule
A: int = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"convert": ["e... | 7 | 0 |
'''simple docstring'''
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
A: List[str] = HUGGINGFACE_HUB_CACHE
A: Union[str, Any] = 'config.json'
A: List[Any] = 'diffusion_pytorch_model.bin'
A: Dict = 'diffusion_flax_mode... | 705 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
A: Any ... | 7 | 0 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_f... | 706 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A: int = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerCon... | 7 | 0 |
'''simple docstring'''
class __magic_name__ :
"""simple docstring"""
def __init__( self ) -> Optional[Any]:
lowercase_ : Any = """"""
lowercase_ : List[str] = """"""
lowercase_ : List[Any] = []
def ... | 707 |
'''simple docstring'''
def _UpperCAmelCase ( a : str ) -> str:
"""simple docstring"""
lowercase_ : Dict = 0
# if input_string is "aba" than new_input_string become "a|b|a"
lowercase_ : Dict = ''
lowercase_ : Any = ... | 7 | 0 |
'''simple docstring'''
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
A: Optional[Any] = 5_0_0_0_0
A: Dict = 5_0_0_0
A , A: List[str] = os.path.split(__file__)
A: List[str] = os.path.join(... | 708 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __magi... | 7 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A: Optional[Any] = {
"configuration_autoformer": [
"AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Au... | 709 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
... | 7 | 0 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( a : int , a : int , a : int , a : int , a : int , a : int ) -> str:
"""simple docstring"""... | 710 |
'''simple docstring'''
def _UpperCAmelCase ( a : list ) -> list:
"""simple docstring"""
for i in range(len(a ) - 1 , 0 , -1 ):
lowercase_ : Any = False
for j in range(a , 0 , -1 ):
... | 7 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A: Optional[Any] = logging.get_logger(__name__)
A: str = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593... | 711 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=UpperCAmelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = ['transformers', 'torch', 'note_seq']
def __init__( self , *_lowercase ... | 7 | 0 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import... | 712 |
'''simple docstring'''
def _UpperCAmelCase ( a : str , a : str ) -> float:
"""simple docstring"""
def get_matched_characters(a : str , a : str ) -> str:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple ... | 7 | 0 |
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