code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Tuple = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
r... | 19 |
"""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 a_ ( _UpperC... | 19 | 1 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTe... | 19 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
a : Optional[Any] = '''\
@misc{chen2021evaluating,
title={Eva... | 19 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_utils... | 19 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _UpperCamelCase ( _A , _A , _A , _A , _A ) -> np.array:
"""simple docstring"""
_UpperCAmelCase = int(np.ceil((x_end - xa) / step_size ) )
_U... | 19 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from ... | 19 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 19 | 1 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
... | 19 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCamelCase ( _A , _A=None ) -> Union[str, Any]:
"""simple docstring"""
_UpperCAmelCase = N... | 19 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a : List[str] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else... | 19 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a_ ( _UpperCAmelCase ):
a : Any = ['image_processor', 'tokenizer']
a : Optional[int] = 'AutoImageProcessor'
a : An... | 19 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
a : Optional[int] = logging.get_logger(__name__)
class a_ ( _UpperCAmelCase ):
def __init__( self : str , *__UpperCamelCase : ... | 19 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( _A , _A , _A ) -> float:
"""simple docstring"""
_UpperCAmelCase = x
_UpperCAmelCase = y
for step in range(_A ): # noqa: B007
... | 19 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A , _A , _A ) -> list:
"""simple docstring"""
_UpperCAmelCase = len(_A )
_UpperCAmelCase = [[0] * n for i in range(_A )]
for i in range(_A ):
_UpperCAmelCase = ... | 19 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class a_ ( nn.Module ):
def __init__( self : List[str] , __UpperCamelCase : int = 16 , __UpperCamelCase : ... | 19 | 1 |
"""simple docstring"""
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transfo... | 19 |
"""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 , _A , _A ) -> List[Any]:
"""simple ... | 19 | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class a_ ( _UpperCAmelCase ):
a ... | 19 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
a : str = '''examples/'''
a : List[str] = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(r'''^__... | 19 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a_ ( _UpperCAmelCase ):
a : Optional[Any] = ['image_processor', 'tokenizer']
a : Any = 'ViTImageProcessor'
a : ... | 19 |
"""simple docstring"""
from __future__ import annotations
def _UpperCamelCase ( _A ) -> None:
"""simple docstring"""
create_state_space_tree(_A , [] , 0 , [0 for i in range(len(_A ) )] )
def _UpperCamelCase ( _A , _A , ... | 19 | 1 |
"""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
from ... | 19 |
"""simple docstring"""
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test... | 19 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCAmelCase )
class a_ ( _UpperCAmelCase ):
a : str = field(default='automat... | 19 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_t... | 19 | 1 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {
'''asapp/sew-d-tiny-100k''': '''https://huggingface.co/asapp/sew-d-tiny-100k/res... | 19 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_de... | 19 | 1 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def _UpperCamelCase ( _A = 1_5_0_0_0_0_0 ) -> int:
"""simple docstring"""
_UpperCAmelCase = defaultdict(_A )
_UpperCAmelCase = 2
while 2 * euclid_m * (euclid_m + 1) <= li... | 19 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
a : str = True
except (ImportError, ModuleNotFoundError):
a : List[str] = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet=True)
def _UpperCamelCase ( ... | 19 | 1 |
"""simple docstring"""
from collections.abc import Callable
def _UpperCamelCase ( _A , _A , _A ) -> float:
"""simple docstring"""
_UpperCAmelCase = a
_UpperCAmelCase = b
if function(_A ) == 0: # one of the a or b is a root for the ... | 19 |
"""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_flax_... | 19 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class a_ :
a : torch.Tensor # [batch_size x 3]
a : torch.Tensor # [batch_size x 3]
a : torch.Tensor # [batch_size x 3]
a : torch... | 19 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 19 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _UpperCamelCase ( _A , _A , _A ) -> Optional[int]:
... | 19 |
"""simple docstring"""
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from dat... | 19 | 1 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Tuple = logging.get_logger(__name__)
a : Optional[Any] = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/resolve/mai... | 19 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorForma... | 19 | 1 |
"""simple docstring"""
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
... | 19 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Tuple = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
r... | 19 | 1 |
"""simple docstring"""
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def _UpperCamelCase ( ) -> int:
"""simple docstring"""
_UpperCAmelCase ,_UpperCAmelCase = 9, 1_4 # noqa: F841
_UpperCAmelCase = [... | 19 |
"""simple docstring"""
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
a : int = WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])
def _UpperCamelCase ( _A ) ... | 19 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import Counter
from random import random
class a_ :
def __init__( self : List[str] ) ->Optional[Any]:
'''simple docstring'''
_UpperCAmelCase = {}
def ... | 19 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patc... | 19 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class a_ ( _UpperCAmelCase ):
def __init__... | 19 |
"""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 a_ ( _UpperC... | 19 | 1 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..... | 19 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
a : Optional[Any] = '''\
@misc{chen2021evaluating,
title={Eva... | 19 | 1 |
"""simple docstring"""
import os
import pytest
from transformers.dynamic_module_utils import get_imports
a : Union[str, Any] = '''
import os
'''
a : List[str] = '''
def foo():
import os
return False
'''
a : Any = '''
def foo():
def bar():
if True:
... | 19 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _UpperCamelCase ( _A , _A , _A , _A , _A ) -> np.array:
"""simple docstring"""
_UpperCAmelCase = int(np.ceil((x_end - xa) / step_size ) )
_U... | 19 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A , _A ) -> int:
"""simple docstring"""
return int(input_a == input_a == 0 )
def _UpperCamelCase ( ) -> None:
"""simple docstring"""
print("""Truth Table of NOR Gate:""" )
print("""| Input 1... | 19 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 19 | 1 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[Any] = logging.get_logger(__name__)
a : int = {'''vocab_file''': '''vocab.json'''}
a : Any = {
'''... | 19 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCamelCase ( _A , _A=None ) -> Union[str, Any]:
"""simple docstring"""
_UpperCAmelCase = N... | 19 | 1 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
a : Union[str, Any] = False
class a_ ( unittest.T... | 19 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a_ ( _UpperCAmelCase ):
a : Any = ['image_processor', 'tokenizer']
a : Optional[int] = 'AutoImageProcessor'
a : An... | 19 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokeni... | 19 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( _A , _A , _A ) -> float:
"""simple docstring"""
_UpperCAmelCase = x
_UpperCAmelCase = y
for step in range(_A ): # noqa: B007
... | 19 | 1 |
"""simple docstring"""
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_availabl... | 19 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class a_ ( nn.Module ):
def __init__( self : List[str] , __UpperCamelCase : int = 16 , __UpperCamelCase : ... | 19 | 1 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
a : str = '''examples/'''
a : List[str] = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(r'''^__... | 19 |
"""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 , _A , _A ) -> List[Any]:
"""simple ... | 19 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils i... | 19 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
a : str = '''examples/'''
a : List[str] = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(r'''^__... | 19 | 1 |
"""simple docstring"""
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipelin... | 19 |
"""simple docstring"""
from __future__ import annotations
def _UpperCamelCase ( _A ) -> None:
"""simple docstring"""
create_state_space_tree(_A , [] , 0 , [0 for i in range(len(_A ) )] )
def _UpperCamelCase ( _A , _A , ... | 19 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 19 |
"""simple docstring"""
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test... | 19 | 1 |
"""simple docstring"""
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import ... | 19 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_t... | 19 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
a : Any = 1.054571817E-34 # unit of ℏ : J * s
a : Optional[int] = 3E8 # unit of c : m * s^-1
def _UpperCamelCas... | 19 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_de... | 19 | 1 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def _UpperCamelCase ( _A ) -> Optional[int]:
"""simple docstring"""
def decorator(_A ):
_UpperCAmelCase = getattr(_A , """handle_key""" , [] )
... | 19 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
a : str = True
except (ImportError, ModuleNotFoundError):
a : List[str] = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet=True)
def _UpperCamelCase ( ... | 19 | 1 |
"""simple docstring"""
import numpy as np
a : Union[str, Any] = [
['''a''', '''b''', '''c''', '''d''', '''e'''],
['''f''', '''g''', '''h''', '''i''', '''k'''],
['''l''', '''m''', '''n''', '''o''', '''p'''],
['''q''', '''r''', '''s''', '''t''', '''u'''],
['''v''', '''w''', '''x''', ''... | 19 |
"""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_flax_... | 19 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
a : str = logging.get_logger(__name__)
a ... | 19 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 19 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
a : str = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''MegaOnnxConfig'''],
}
try:
if not is... | 19 |
"""simple docstring"""
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from dat... | 19 | 1 |
"""simple docstring"""
from __future__ import annotations
def _UpperCamelCase ( _A , _A , _A ) -> tuple[float, list[float]]:
"""simple docstring"""
_UpperCAmelCase = list(range(len(_A ) ) )
_UpperCAmelCase = [v / w for v, w in... | 19 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorForma... | 19 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
a : str = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'''
''' Dist... | 19 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Tuple = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
r... | 19 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test... | 19 |
"""simple docstring"""
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
a : int = WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])
def _UpperCamelCase ( _A ) ... | 19 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A ) -> str:
"""simple docstring"""
_UpperCAmelCase = int(_A )
if decimal in (0, 1): # Exit cases for the recursion
return str(_A )
_UpperCAmelCase ,_UpperCAmelCase = divmod(_A , 2 ... | 19 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patc... | 19 | 1 |
"""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_flax_... | 19 |
"""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 a_ ( _UpperC... | 19 | 1 |
"""simple docstring"""
import string
from math import logaa
def _UpperCamelCase ( _A , _A ) -> int:
"""simple docstring"""
_UpperCAmelCase = document.translate(
str.maketrans("""""" , """""" , string.punctuation ) ).replace("""\n... | 19 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
a : Optional[Any] = '''\
@misc{chen2021evaluating,
title={Eva... | 19 | 1 |
"""simple docstring"""
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from dat... | 19 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _UpperCamelCase ( _A , _A , _A , _A , _A ) -> np.array:
"""simple docstring"""
_UpperCAmelCase = int(np.ceil((x_end - xa) / step_size ) )
_U... | 19 | 1 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class a_ ( _UpperCAmelCase ):
# to overwrite at feature extractactor specific... | 19 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 19 | 1 |
"""simple docstring"""
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
a : Optional[int] = Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_path))
import dataclasses # ... | 19 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCamelCase ( _A , _A=None ) -> Union[str, Any]:
"""simple docstring"""
_UpperCAmelCase = N... | 19 | 1 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def _UpperCamelCase ( _A , _A ) -> np.ndarray:
"""simple docstring"""
_UpperCAmelCase = math.sqrt(_A )
_UpperCAmelCase = 1 / (sigma * math.sqrt(2 * math.pi ))
... | 19 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a_ ( _UpperCAmelCase ):
a : Any = ['image_processor', 'tokenizer']
a : Optional[int] = 'AutoImageProcessor'
a : An... | 19 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
"""simple docstring"""
try:
_UpperCAmelCase = int(_A )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable to int.""" )
if ... | 19 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( _A , _A , _A ) -> float:
"""simple docstring"""
_UpperCAmelCase = x
_UpperCAmelCase = y
for step in range(_A ): # noqa: B007
... | 19 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
a : Union[str, Any] = logging.getLogger(__name__)
def _UpperCamelCase ( ) -> int:
"""simple docstring"""
_UpperCAmelCase = ... | 19 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class a_ ( nn.Module ):
def __init__( self : List[str] , __UpperCamelCase : int = 16 , __UpperCamelCase : ... | 19 | 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, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a ... | 19 |
"""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 , _A , _A ) -> List[Any]:
"""simple ... | 19 | 1 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
a : List[Any] = '''\
'''
a : List[Any] = '''
Perplexity (PPL) is one of the most common me... | 19 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
a : str = '''examples/'''
a : List[str] = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(r'''^__... | 19 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A , _A ) -> Optional[Any]:
"""simple docstring"""
_UpperCAmelCase = """"""
for i in table:
res += inp[i - 1]
return res
def _UpperCamelCase ( _A ) -> Optional[Any]:
"""simple docs... | 19 |
"""simple docstring"""
from __future__ import annotations
def _UpperCamelCase ( _A ) -> None:
"""simple docstring"""
create_state_space_tree(_A , [] , 0 , [0 for i in range(len(_A ) )] )
def _UpperCamelCase ( _A , _A , ... | 19 | 1 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import jit
... | 19 |
"""simple docstring"""
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test... | 19 | 1 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, 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] = loggi... | 19 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_t... | 19 | 1 |
"""simple docstring"""
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _UpperCamelCase ( ) -> List[str]:
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as original_r... | 19 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_de... | 19 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A ) -> list[int]:
"""simple docstring"""
_UpperCAmelCase = len(_A )
for i in range(_A ):
for j in range(i + 1 , _A ):
if numbers[j] < numbers[i]:
_UpperCAmelCase ,... | 19 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
a : str = True
except (ImportError, ModuleNotFoundError):
a : List[str] = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet=True)
def _UpperCamelCase ( ... | 19 | 1 |
"""simple docstring"""
class a_ :
def __init__( self : Optional[Any] , __UpperCamelCase : int , __UpperCamelCase : Optional[int] ) ->Optional[Any]:
'''simple docstring'''
_UpperCAmelCase = name
_UpperCAme... | 19 |
"""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_flax_... | 19 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from ... | 19 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 19 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
a : Tuple = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that genera... | 19 |
"""simple docstring"""
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from dat... | 19 | 1 |
"""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_avai... | 19 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorForma... | 19 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageRes... | 19 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Tuple = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
r... | 19 | 1 |
"""simple docstring"""
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
a : Dict = logging.get_logger(__name__)
a : Tuple = {name: getattr(transformers, name + '''Fast''') fo... | 19 |
"""simple docstring"""
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
a : int = WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])
def _UpperCamelCase ( _A ) ... | 19 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizer... | 19 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patc... | 19 | 1 |
"""simple docstring"""
import math
def _UpperCamelCase ( _A ) -> bool:
"""simple docstring"""
assert isinstance(_A , _A ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
... | 19 |
"""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 a_ ( _UpperC... | 19 | 1 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailabl... | 19 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
a : Optional[Any] = '''\
@misc{chen2021evaluating,
title={Eva... | 19 | 1 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _UpperCamelCase ( _A , _A , _A , _A , _A ) -> np.array:
"""simple docstring"""
_UpperCAmelCase = int(np.ceil((x_end - xa) / step_size ) )
_U... | 19 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _UpperCamelCase ( _A , _A , _A , _A , _A ) -> np.array:
"""simple docstring"""
_UpperCAmelCase = int(np.ceil((x_end - xa) / step_size ) )
_U... | 19 | 1 |
"""simple docstring"""
import math
def _UpperCamelCase ( _A ) -> str:
"""simple docstring"""
_UpperCAmelCase = 0
_UpperCAmelCase = 0
while num > 0:
_UpperCAmelCase = num % 8
_UpperCAmelCase = octal + (remainder * math... | 19 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 19 | 1 |
"""simple docstring"""
a : dict[tuple[int, int, int], int] = {}
def _UpperCamelCase ( _A , _A , _A ) -> int:
"""simple docstring"""
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not failed any other rules,
# we ... | 19 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCamelCase ( _A , _A=None ) -> Union[str, Any]:
"""simple docstring"""
_UpperCAmelCase = N... | 19 | 1 |
"""simple docstring"""
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _UpperCamelCase ( _A , _A , **_A ) -> str:
"""simple docstring"""
_UpperCAmelCase = AutoConfig.from_pretrained(_A , **_A )
_... | 19 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a_ ( _UpperCAmelCase ):
a : Any = ['image_processor', 'tokenizer']
a : Optional[int] = 'AutoImageProcessor'
a : An... | 19 | 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,
resize,
to_channel... | 19 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( _A , _A , _A ) -> float:
"""simple docstring"""
_UpperCAmelCase = x
_UpperCAmelCase = y
for step in range(_A ): # noqa: B007
... | 19 | 1 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def _UpperCamelCase ( _A ) -> Optional[int]:
"""simple docstring"""
_UpperCAmelCase = [
"""encoder.version""",
""... | 19 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class a_ ( nn.Module ):
def __init__( self : List[str] , __UpperCamelCase : int = 16 , __UpperCamelCase : ... | 19 | 1 |
"""simple docstring"""
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transfor... | 19 |
"""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 , _A , _A ) -> List[Any]:
"""simple ... | 19 | 1 |
"""simple docstring"""
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : str = logging.get_logger(__name__)
a : List[str] = {
'''facebook/encodec_24khz''': '''https://huggingface.co/facebook/... | 19 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
a : str = '''examples/'''
a : List[str] = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(r'''^__... | 19 | 1 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
a : Optional[Any] = '''\
@misc{chen2021evaluating,
title={Eva... | 19 |
"""simple docstring"""
from __future__ import annotations
def _UpperCamelCase ( _A ) -> None:
"""simple docstring"""
create_state_space_tree(_A , [] , 0 , [0 for i in range(len(_A ) )] )
def _UpperCamelCase ( _A , _A , ... | 19 | 1 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _UpperCamelCase ( ) -> Dict:
"""simple docstring"""
_UpperCAmelCase = ArgumentParser(
d... | 19 |
"""simple docstring"""
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test... | 19 | 1 |
"""simple docstring"""
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conver... | 19 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_t... | 19 | 1 |
"""simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
a ... | 19 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_de... | 19 | 1 |
"""simple docstring"""
import random
class a_ :
@staticmethod
def _snake_case ( __UpperCamelCase : str ) ->tuple[list[int], list[int]]:
'''simple docstring'''
_UpperCAmelCase = [ord(__UpperCamelCase ) for i in text]
... | 19 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
a : str = True
except (ImportError, ModuleNotFoundError):
a : List[str] = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet=True)
def _UpperCamelCase ( ... | 19 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from dataset... | 19 |
"""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_flax_... | 19 | 1 |
"""simple docstring"""
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="""session""" )
def _UpperCamelCase ( ) ... | 19 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 19 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_... | 19 |
"""simple docstring"""
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from dat... | 19 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A , _A ) -> str:
"""simple docstring"""
if not isinstance(_A , _A ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstance(_A , _A ) or not number >= 1:
... | 19 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorForma... | 19 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a : Dict = {
'''configuration_groupvit''': [
'''GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''GroupViTConfig''',
'''... | 19 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Tuple = {
'''configuration_pegasus_x''': ['''PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PegasusXConfig'''],
}
try:
if not is_torch_available():
r... | 19 | 1 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ... | 19 |
"""simple docstring"""
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
a : int = WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])
def _UpperCamelCase ( _A ) ... | 19 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A = 1_0_0_0_0_0_0 ) -> int:
"""simple docstring"""
_UpperCAmelCase = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , ... | 19 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patc... | 19 | 1 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCamelCase ( _A , _A=None ) -> Union[str, Any]:
"""simple docstring"""
_UpperCAmelCase = N... | 19 |
"""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 a_ ( _UpperC... | 19 | 1 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when s... | 19 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
a : Optional[Any] = '''\
@misc{chen2021evaluating,
title={Eva... | 19 | 1 |
"""simple docstring"""
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def _UpperCamelCase ( _A , _A , _A , _A , _A ) -> np.ndarray:
"""simple docstring"""
_UpperCAmelCase = cva.getAffineTransf... | 19 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _UpperCamelCase ( _A , _A , _A , _A , _A ) -> np.array:
"""simple docstring"""
_UpperCAmelCase = int(np.ceil((x_end - xa) / step_size ) )
_U... | 19 | 1 |
"""simple docstring"""
a : List[Any] = [0, 2, 4, 6, 8]
a : List[Any] = [1, 3, 5, 7, 9]
def _UpperCamelCase ( _A , _A , _A , _A ) -> int:
"""simple docstring"""
if remaining_length == 0:
if digits[0] == 0 or digits[-1] == 0:
... | 19 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 19 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 19 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCamelCase ( _A , _A=None ) -> Union[str, Any]:
"""simple docstring"""
_UpperCAmelCase = N... | 19 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A , _A ) -> Optional[int]:
"""simple docstring"""
_enforce_args(_A , _A )
if n == 0:
return 0
_UpperCAmelCase = float("""-inf""" )
for i in range(1 , n + 1 ):
_... | 19 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class a_ ( _UpperCAmelCase ):
a : Any = ['image_processor', 'tokenizer']
a : Optional[int] = 'AutoImageProcessor'
a : An... | 19 | 1 |
"""simple docstring"""
import fire
from utils import calculate_rouge, save_json
def _UpperCamelCase ( _A , _A , _A=None , **_A ) -> Optional[Any]:
"""simple docstring"""
_UpperCAmelCase = [x.strip() for x in open(_A ).readlines()]
_Upper... | 19 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( _A , _A , _A ) -> float:
"""simple docstring"""
_UpperCAmelCase = x
_UpperCAmelCase = y
for step in range(_A ): # noqa: B007
... | 19 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configura... | 19 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class a_ ( nn.Module ):
def __init__( self : List[str] , __UpperCamelCase : int = 16 , __UpperCamelCase : ... | 19 | 1 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : str = logging.get_logger(__name__)
a : Dict = {
'''microsoft/xprophetnet-large-wiki100-cased''': (
'''https://huggingface.co/... | 19 |
"""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 , _A , _A ) -> List[Any]:
"""simple ... | 19 | 1 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require... | 19 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
a : str = '''examples/'''
a : List[str] = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(r'''^__... | 19 | 1 |
"""simple docstring"""
from random import randint, random
def _UpperCamelCase ( _A , _A , _A , _A = False , _A = False , _A = 5 , ) -> list:
"""simple docstring"""
_UpperCAmelCase = [[-1] * number_of_cells] # Create a highwa... | 19 |
"""simple docstring"""
from __future__ import annotations
def _UpperCamelCase ( _A ) -> None:
"""simple docstring"""
create_state_space_tree(_A , [] , 0 , [0 for i in range(len(_A ) )] )
def _UpperCamelCase ( _A , _A , ... | 19 | 1 |
"""simple docstring"""
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class a_ ( _UpperCA... | 19 |
"""simple docstring"""
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test... | 19 | 1 |
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