code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_switch_tr... | 325 |
"""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,
... | 91 | 0 |
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : np.ndarray , SCREAMING_SNAKE_CASE__ : i... | 117 |
import pprint
import requests
_A = 'https://zenquotes.io/api'
def _UpperCAmelCase ( ):
return requests.get(API_ENDPOINT_URL + '/today' ).json()
def _UpperCAmelCase ( ):
return requests.get(API_ENDPOINT_URL + '/random' ).json()
if __name__ == "__main__":
_A ... | 117 | 1 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
a = False
class lowercase_ ( unittest.TestCas... | 315 |
"""simple docstring"""
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils im... | 315 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase : int = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'to... | 361 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowercase : Optional[int] = [
'kernels/rwkv/wkv_cuda.cu',
'kernels/rwkv/wkv_op.cpp',
'kernels/deformable_detr/ms_deform_attn.h',
'kernels/... | 311 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner im... | 230 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_... | 230 | 1 |
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmbeddings,
BertLay... | 231 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCamelCase : Any = {
"""configuration_nezha""": ["""NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NezhaConfig"""],
}
try:
if not is_torch_avai... | 231 | 1 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
UpperCAmelCase : Union[str, Any] = datasets.utils.logging.get_logger(__name__)
@dataclass
class __low... | 252 |
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import SequenceFeatureExtraction... | 252 | 1 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_acceler... | 173 |
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def __lowercase ( _UpperCamelCase ) ->Tuple:
"""simple docstring"""
lowercase : List[str] = [
'''encoder.version''',
... | 173 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( A_ , A_ ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 106 |
"""simple docstring"""
import os
from collections.abc import Iterator
def __SCREAMING_SNAKE_CASE ( A_ = "." ):
for dir_path, dir_names, filenames in os.walk(A_ ):
lowerCAmelCase__ : str = [d for d in dir_names if d != '''scripts''' and d[0] not in '''._''']
for filename in filenames:
i... | 106 | 1 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
UpperCamelCase__ =datasets.logging.get_logger(__name__)
UpperCamelCase__ ='\\n@InProceedings{moosavi2019minimum,\n author = { N... | 325 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftFormerOnnxConfig',... | 325 | 1 |
"""simple docstring"""
from math import isqrt, loga
def lowercase (_lowerCAmelCase ):
__lowerCAmelCase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , _lowerCAmelCase , ... | 301 |
"""simple docstring"""
from __future__ import annotations
def lowercase (_lowerCAmelCase , _lowerCAmelCase ):
__lowerCAmelCase = []
create_all_state(1 , _lowerCAmelCase , _lowerCAmelCase , [] , _lowerCAmelCase )
return result
def lower... | 301 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMix... | 363 |
'''simple docstring'''
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_comm... | 240 | 0 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availab... | 89 |
'''simple docstring'''
__lowerCAmelCase = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE ):
# Make sure the supplied data is a bytes-like object
if not isinstance(_SCREAMING_SNAKE_CASE , ... | 341 | 0 |
class __a :
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> Tuple:
'''simple docstring'''
lowercase__: List[str] = name
lowercase__: Any = value
lowercase__: ... | 288 |
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class __a ( tf.keras.layers.Layer ):
def __init__( self , ... | 288 | 1 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, vali... | 12 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class __UpperCAmelCase :
def __magic_name__ ( self : int, __A : Dict ):
raise NotImplementedError()
def ... | 336 | 0 |
'''simple docstring'''
import numpy as np
def __lowerCamelCase ( _lowercase , _lowercase , _lowercase , _lowercase , _lowercase ) -> Optional[Any]:
UpperCAmelCase : Tuple = int(np.ceil((x_end - xa) / h ) )
UpperCAmelCase : Option... | 338 |
'''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 : Union[str, Any] = logging.get_logger(__name__)
a : ... | 338 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_case__ : Optional[Any] = {
'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve... | 117 |
import heapq
import sys
import numpy as np
snake_case__ : Tuple = tuple[int, int]
class A_ :
def __init__(self :Union[str, Any] )-> Union[str, Any]:
__A = []
__A = set()
def _lowerCAmelCas... | 117 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from... | 366 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : str = {
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
if not is_torch_available(... | 259 | 0 |
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 ConfigTester
from ...test_mode... | 124 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
a : Union[str, Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
],
"fea... | 311 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def _A ( _a : Tuple , _a : Optional[int] , _... | 77 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def _A ( _a : Callable[[int | float], int | float] , _a : int | float , _a : int | float , _a : int = 1_0_0 , ):
"""simple docs... | 77 | 1 |
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 231 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class _lowerCAmelCase ( __a ):
_lowercase ='''megatron-bert'''
def _... | 231 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import j... | 161 |
"""simple docstring"""
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def __lowerCamelCase ( __UpperCamelCase ) -> Any:
"""simple docstring"""
if not is_accelerate_available():
return method
... | 161 | 1 |
"""simple docstring"""
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
"""split_dict""" , [
SplitDict(),
SplitDict({"""train""": SplitInfo(name="""train""" , num_bytes=1337 ... | 173 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
_UpperCAmelCase = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
_UpperCAmelCase = re.compile(r"""([a-z\d])([A-Z])""")
_UpperCAmelCase = re.compile(r"""(?<!_)_(?!_)""")
_UpperCAmelCase = re.compile(r"""(_{2,})""")
_... | 173 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ ={
'configuration_roberta': ['ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Robe... | 325 |
def lowerCamelCase__ (__lowerCamelCase, __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : Tuple = [0 for i in range(r + 1 )]
# nc0 = 1
_SCREAMING_SNAKE_CASE : Optional[int] = 1
for i in range(1, n + 1 ):
# to compute current row from pre... | 325 | 1 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
SCREAMING_SNAKE_CASE__ = datasets.logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = """\
@InProceedings{moosavi2019minimum,
... | 325 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class A__ ( lowerCAmelCase... | 325 | 1 |
"""simple docstring"""
import math
def lowercase__ ( _UpperCAmelCase , _UpperCAmelCase ) -> int:
'''simple docstring'''
if initial_intensity < 0:
raise ValueError('The value of intensity cannot be negative' )
#... | 363 |
"""simple docstring"""
def lowercase__ ( _UpperCAmelCase ) -> int:
'''simple docstring'''
assert isinstance(_UpperCAmelCase , _UpperCAmelCase ), f'''The input value of [n={number}] is not an integer'''
if number == 1:
ret... | 53 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase_ )
class _lowercase (lowerCamelCase_ ):
'''simple docstring'''
lowercase__ ... | 128 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
snake_case : List[Any] = datasets.logging.get_logger(__name__)
snake_case : List[str] = '''\
@InPro... | 240 | 0 |
import math
def A_ ( _UpperCAmelCase , _UpperCAmelCase ):
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(_UpperCAmelCase )
else:
if x == 0: # 0 raised to any number is 0
... | 127 |
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...test_tokenization_common impo... | 127 | 1 |
"""simple docstring"""
from __future__ import annotations
def _UpperCAmelCase ( __lowerCamelCase : int | float | str , __lowerCamelCase : int | float | str ) -> list[str]:
if nth_term == "":
return [""]
_snake_case = int(__lowerCamelCase )
_... | 288 |
"""simple docstring"""
from math import pow
def _UpperCAmelCase ( __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : int , ) -> tuple[int, int]:
if current_sum =... | 288 | 1 |
def __snake_case ( _lowerCAmelCase : int , _lowerCAmelCase : int ) -> int:
while b:
A_ , A_ : List[str] = b, a % b
return a
def __snake_case ( _lowerCAmelCase : int , _lowerCAmelCase : int ) -> int:
return a if b == 0 else euclidean_gcd_recursive(__lowerC... | 353 |
# 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
_lowerCAmelCase : Optional[Any] = Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
im... | 70 | 0 |
import numpy as np
def SCREAMING_SNAKE_CASE_ ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ ) -> Optional[int]:
lowerCAmelCase = int(np.ceil((x_end - xa) / h ) )
lowerCAmelCase = np.zeros((n + 1,) )
lowerCAm... | 338 | class lowercase_ :
"""simple docstring"""
def __init__( self , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) ->Any:
lowerCAmelCase = name
lowerCAmelCase = value
lowerCAmelCase = weight
def __repr__( ... | 338 | 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,
... | 157 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_SCREAMING_SNAKE_CASE : List[str] = {
"""configuration_bigbird_pegasus""": [
"""BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BigBi... | 157 | 1 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('''socket.socket''' )
@patch('''builtins.open''' )
def lowerCamelCase_ ( _a , _a ):
"""simple docstring"""
lowerCAmelCase__ : Optional[Any] ... | 131 |
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case = logging.get_logger(__name__)
__snake_case = """https://... | 259 | 0 |
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
UpperCAmelCase = '\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for Text Simplification},\n authors={Xu, Wei and ... | 358 |
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 TokenizerTesterMixin
UpperCAm... | 267 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
_UpperCamelCase : List[str] = {
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/confi... | 77 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/re... | 77 | 1 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowerCAmelCase__( __lowercase , unittest.TestCase ... | 325 |
from timeit import timeit
def lowerCamelCase__ (__lowerCamelCase ):
if number < 0:
raise ValueError("the value of input must not be negative" )
_SCREAMING_SNAKE_CASE : str = 0
while number:
number &= number - 1
result += 1
return... | 325 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
def snake_case ( UpperCAmelCase )-> None:
"""simple docstring"""
create_state_space_tree(UpperCAmelCase , [] , 0 )
def snake_case ... | 161 |
'''simple docstring'''
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase__ ( SCREAMING_SNAKE_CASE):
def __init__( self :Optional[int] , _A ... | 161 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepa... | 106 | '''simple docstring'''
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
SCREAMING_SNAKE_CASE_: Any =logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_: ... | 106 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_roberta""": ["""ROBERTA_PRETRAINED_CONFIG_ARCHIVE_M... | 325 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {name: getattr(transformers, name + """Fast""") for n... | 325 | 1 |
from collections.abc import Iterable
from typing import Any
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Optional[int] , SCREAMING_SNAKE_CASE__ : Union[str, Any] = None ) -> str:
a_ : Optional[int] = value
a_ : Node | None = ... | 367 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : Any = {
'configuration_mobilebert': [
'MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_... | 120 | 0 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_availab... | 100 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class snake_case ( __lowerCamelCase ):
"""simple docstring"""
pass
class snake_case :
"""simple docstring"""
def __init__( self : List[Any] , __A : ... | 53 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A ={
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenizati... | 283 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _snake_case ( a__ ):
lowerCAmelCase :Optional[int] = ''''''
lowerCAmelCase :str ... | 283 | 1 |
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
_SCREAMING_SNAKE_CASE : Optional[Any] = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
... | 127 |
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( snake_case__ , unittest.TestCase )... | 127 | 1 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultiste... | 255 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from... | 255 | 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... | 1 |
'''simple docstring'''
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = [0 for i in range(r + 1 )]
# nc0 = 1
_lowerCAmelCase = 1
for i in range(1... | 70 | 0 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
_lowercase : Tuple = datasets.load_iris()
_lowercase : List[str] = np.array(data["data"])
_lowercase : Union[str, An... | 356 | '''simple docstring'''
import os
import numpy
import onnx
def lowerCamelCase ( UpperCAmelCase__ : Optional[int] , UpperCAmelCase__ : str ) -> Tuple:
lowercase_ : Tuple = a.name
lowercase_ : Tuple = b.name
lowercase_ : Any ... | 21 | 0 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
_snake_case = logging.get_logger(__name__)
class _snake_case ( _lowercase ):
def __init__( self: int , *__lowerCamelCase: Tuple , **__lowerCamelCase: Optional[... | 157 | 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_tf_common import T... | 157 | 1 |
"""simple docstring"""
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
lowe... | 353 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransfor... | 215 | 0 |
"""simple docstring"""
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __UpperCamelCase ( a__ ... | 105 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
_enforce_args(a__ , a__ )
if n == 0:
return 0
__SCREAMING_SNAKE_CASE = float("""-inf""" )
for i in range(1 , n + 1 ):
__SCREAMING_SN... | 267 | 0 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def snake_case (__lowercase , __lowercase=False ) -> str:
'''simple docstring'''
_snake_case : int = OmegaConf.load(__lowercase )
if display:
... | 284 | import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowercase_ ( __snake_case ):
_lowerCamelCase = 'M-CLIP'
def __init__( self , lowercase_=1_024 , lowercase_=768 , **lowercase_ ):
_snake_case ... | 284 | 1 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class A__ ( lowerCAmelCase__ , unittest.TestCase ):
lower... | 325 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass... | 325 | 1 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate... | 365 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
UpperCAmelCase : List[str] = datasets.utils.logging.get_logger(__name__)
@... | 331 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transforme... | 106 |
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
__UpperCamelCase : int ... | 106 | 1 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class UpperCamelCase ( ctypes.Structure ):
"""simple docstring"""
# _fields is a specific attr expected by ctypes
... | 336 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
UpperCAmelCase: List[str] = True
except (ImportError, ModuleNotFoundError):
UpperCAmelCase: int = False
if NLTK_AVAILABLE:
with FileLock(""".lock""") as lock:
nltk.download("""... | 336 | 1 |
"""simple docstring"""
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_com... | 102 |
'''simple docstring'''
def UpperCamelCase_ ( A__ : str , A__ : list[str] ):
'''simple docstring'''
lowerCAmelCase_ : Dict = """"""
for word_or_phrase in separated:
if not isinstance(A__ , A__ ):
raise Exception("... | 120 | 0 |
def __a ( lowerCAmelCase_ : int = 1_00_00_00 ) -> 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 ,limit + 1 ... | 277 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def __a ( lowerCAmelCase_ : Optional[int] ) -> List[Any]:
'''simple docstring'''
UpperCAmelCase_= [
"""decoder.version"... | 277 | 1 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"files" , [
["full:README.md", "dataset_infos.json"],
["empty:README.md", "dataset_info... | 283 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if "model" in orig_key:
lowerCamelCase : Dict = orig_key.replace("model." , "" )
if "norm1" in orig_key:
... | 283 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3... | 248 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Dict = logging.get_logger(__name__)
lowerCAmelCase_ : List[str] = {
'''microsoft/unispeech-large-1500h-cv''': (... | 248 | 1 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtract... | 255 |
"""simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class a__ ( unittest.TestCase ):
def lowercase ( se... | 255 | 1 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCamelCase = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned"""
""" Disti... | 65 |
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_available,
)
from . import BaseT... | 65 | 1 |
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase , UpperCAmelCase=sys.... | 5 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class _lowerCamelCase( unittest.TestCase ):
lowercase_ : Dict = JukeboxTokenizer
lowercase_ : Dict = {
"""artist""": """Zac Brown Band""",
"""ge... | 21 | 0 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
lowerCamelCase__ = TypeVar("""T""")
class A__ ( Generic[T] ):
def __init__( self : List[Any] , a : list[T] , a : C... | 307 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
OpenAIG... | 307 | 1 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
def __magic_name__ ( self : List[Any] ) -> Tuple:
SCREAMING_SNAKE_CASE__ : st... | 152 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
... | 215 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCamelCase__ = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5OnnxConfig"""],
}
try:
if no... | 364 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> str:
stooge(SCREAMING_SNAKE_CASE_ , 0 , len(SCREAMING_SNAKE_CASE_ ) - 1 )
return arr
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> Dict:
... | 307 | 0 |
import os
from datetime import datetime as dt
from github import Github
_snake_case : int = [
'good first issue',
'feature request',
'wip',
]
def a_ ( ):
__lowerCAmelCase = Github(os.environ['GITHUB_TOKEN'] )
__lowerCAmelCase = g.get_repo('huggingface/acceler... | 284 |
def a_ ( lowerCAmelCase_ : int ):
if number < 0:
raise ValueError('number must not be negative' )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 284 | 1 |
def __SCREAMING_SNAKE_CASE ( __UpperCamelCase : list[int] , __UpperCamelCase : list[int] , __UpperCamelCase : int ) -> Dict:
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(... | 360 | import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.testing_utils ... | 204 | 0 |
def a__ ( A_ = 10**9 ):
'''simple docstring'''
__magic_name__ = 1
__magic_name__ = 2
__magic_name__ = 0
__magic_name__ = 0
__magic_name__ = 0
while perimeter <= max_perimeter:
perimeter... | 88 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'''t5-small''': '''https://huggingface.co/t... | 268 | 0 |
from numpy import exp, pi, sqrt
def UpperCamelCase_( _snake_case : int , _snake_case : float = 0.0 , _snake_case : float = 1.0 ):
"""simple docstring"""
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) ... | 370 |
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMix... | 308 | 0 |
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __UpperCAmelCase ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
UpperCamelCase = [("""size... | 336 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCamelCase : Tuple = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
],
"feature_extractio... | 336 | 1 |
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def _snake_case( SCREAMING_SNAKE_CA... | 282 |
from __future__ import annotations
from typing import Any
def _snake_case( SCREAMING_SNAKE_CASE__ : list ) -> int:
'''simple docstring'''
if not postfix_notation:
return 0
A__ = {'+', '-', '*', '/'}
A__ = [... | 282 | 1 |
def lowercase_ (A : Optional[int] ):
snake_case__ : str = len(A )
while cur > 1:
# Find the maximum number in arr
snake_case__ : Dict = arr.index(max(arr[0:cur] ) )
# Reverse from 0 to mi
snake_c... | 277 |
from collections import deque
from .hash_table import HashTable
class snake_case__ ( lowerCAmelCase_ ):
"""simple docstring"""
def __init__( self : Optional[Any], *_snake_case : Optional[Any], **_snake_case : List[Any] ) ->Optional[int]:
super... | 277 | 1 |
"""simple docstring"""
import re
def UpperCAmelCase ( a_ ) -> bool:
"""simple docstring"""
__A = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.search(a_ , a_ ) )
if __na... | 351 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def UpperCAmelCase ( a_ ) -> None:
"""simple docstring"""
__A , __A = analyze_text(a_ )
__A = list(" " + ascii_... | 124 | 0 |
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet impor... | 248 |
from typing import Any
class A__:
"""simple docstring"""
def __init__( self , _lowercase ) -> List[str]:
a_ : List[str] = data
a_ : Optional[int] = None
def __repr__( self ) -> str:
return F'''Node({self... | 248 | 1 |
'''simple docstring'''
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase : ... | 352 |
'''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_ ( snake_ca... | 311 | 0 |
import math
def lowerCAmelCase_ ( __A ) -> bool:
'''simple docstring'''
return math.sqrt(__A ) * math.sqrt(__A ) == num
def lowerCAmelCase_ ( __A ) -> bool:
'''simple docstring'''
UpperC... | 65 | 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 patch
import pya... | 65 | 1 |
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, r... | 362 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCAmelCase : int = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailab... | 308 | 0 |
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_d... | 307 |
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __SCREAMING_SNAKE_CASE( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
_Uppe... | 307 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_camembert i... | 102 |
import math
def _a ( SCREAMING_SNAKE_CASE_ : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
r... | 102 | 1 |
"""simple docstring"""
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
__UpperCAmelCase = version.parse(importlib_metadata.version('nltk'))
if NLTK_VERSION >= version.Version('3.6.4'):
from nltk impo... | 84 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import... | 307 | 0 |
'''simple docstring'''
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__A : List[Any] = logging.get_logger(__name__)
def UpperCAmelCase ( lowerCamelCa... | 8 |
'''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.ut... | 8 | 1 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def __lowerCAmelCase ( a__ ) -> Tuple:
__a ... | 6 |
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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 204 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ : List[Any] = {
'facebook/dpr-ctx_encoder-single-nq-base': (
'https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/re... | 120 |
from string import ascii_uppercase
UpperCAmelCase_ : Dict = {char: i for i, char in enumerate(ascii_uppercase)}
UpperCAmelCase_ : Optional[int] = dict(enumerate(ascii_uppercase))
def SCREAMING_SNAKE_CASE_ ( __A : str , __A : str ) -> str:
... | 120 | 1 |
"""simple docstring"""
lowerCamelCase__ = {
"""A""": """.-""", """B""": """-...""", """C""": """-.-.""", """D""": """-..""", """E""": """.""", """F""": """..-.""", """G""": """--.""",
"""H""": """....""", """I""": """..""", """J""": """.---""", """K""": """-.-""", """L""": """.-..""", """M""": "... | 86 |
import os
def snake_case( __magic_name__ = "input.txt" ) -> int:
'''simple docstring'''
with open(os.path.join(os.path.dirname(__magic_name__ ) , __magic_name__ ) ) as input_file:
lowercase : Any = [
[int(... | 308 | 0 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_... | 0 |
'''simple docstring'''
from __future__ import annotations
A__ : str = '''Muhammad Umer Farooq'''
A__ : int = '''MIT'''
A__ : Optional[int] = '''1.0.0'''
A__ : List[Any] = '''Muhammad Umer Farooq'''
A__ : Optional[Any] = '''contact@muhammadumerfa... | 0 | 1 |
from __future__ import annotations
def a_ ( __lowercase : list[int] , __lowercase : list[int] , __lowercase : list[int] , __lowercase : list[list[str]] , __lowercase : int , ) -> None:
_snake_case = len(__lowercase )
# If row is... | 282 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_lowerCamelCase : List[Any] = HfApi()
_lowerCamelCase : Dict = {}
# fmt: off
_lowerCamelCase : List[Any] = torch.tensor([
-0.7_5_1_5, -1.6_8_8_3, 0.2_4_2_0, 0.0_3_0... | 282 | 1 |
"""simple docstring"""
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.util... | 296 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP... | 296 | 1 |
"""simple docstring"""
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''google/umt5-small''': '''https:... | 108 |
from typing import List
from .keymap import KEYMAP, get_character
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> Tuple:
def decorator(lowercase ):
snake_case : Tuple = getattr(lowercase ,"""handle_key""" ,[] )
handle += [key]
setattr(lo... | 124 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jn... | 371 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
UpperCamelCase__ = logging.get_l... | 299 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json',
# See all ViT MAE models at https://huggi... | 24 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class UpperCamelCase__ ( unittest.TestCase )... | 311 | 0 |
"""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
lowerCAmelCase : Union[str, Any] = logging.get_logg... | 351 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
Rober... | 168 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
lowerCamelCase_ = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-la... | 268 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, log... | 268 | 1 |
"""simple docstring"""
def snake_case ( A__ ):
if number > 0:
raise ValueError("input must be a negative integer" )
UpperCAmelCase_ : Union[str, Any] = len(bin(A__ )[3:] )
UpperCAmelCase_ : Union[str, Any] = bin(abs(A__ ) - (1 <... | 253 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, 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,
... | 253 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : List[str] = {
"""configuration_time_series_transformer""": [
"""TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 102 |
"""simple docstring"""
from math import factorial, radians
def lowercase ( _snake_case : float , _snake_case : int = 18 , _snake_case : int = 10 ) ->float:
"""simple docstring"""
__snake_case : Any = angle_in_degrees - ((angle_in... | 102 | 1 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def _a ... | 355 |
from __future__ import annotations
snake_case__ : Dict = [True] * 1000001
snake_case__ : int = 2
while i * i <= 1000000:
if seive[i]:
for j in range(i * i, 1000001, i):
snake_case__ : str = Fa... | 250 | 0 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
lowerCAmelCase_ = logging.get_logger(__name__)
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMIN... | 8 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ = {'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 8 | 1 |
"""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_retribert import RetriBertTokenizer
lowerCAmelCase : List[str] ... | 168 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_uti... | 168 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A : Dict = {
"configuration_data2vec_audio": ["DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP", "Data2VecAudio... | 120 |
'''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/... | 120 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_proce... | 185 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 185 | 1 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_availa... | 0 |
from __future__ import annotations
UpperCAmelCase__ = "Muhammad Umer Farooq"
UpperCAmelCase__ = "MIT"
UpperCAmelCase__ = "1.0.0"
UpperCAmelCase__ = "Muhammad Umer Farooq"
UpperCAmelCase__ = "contact@muhammadumerfarooq.me"
UpperCAmelCase__ = "Alpha"
impo... | 0 | 1 |
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def __lowerCamelCase ( snake_case__ ,snake_case__ ,snake_case__ ,snake_case__=5 ) -> Dict:
"""simple docstring"""
assert masked_input.count("""<mask>""" ) == 1
_S... | 351 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
... | 125 | 0 |
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