code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 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()
UpperCAmelCase_ : Any = logging.get_logger(__name__)
UpperCAmelCase_ : Optional[int] = {name: get... | 365 |
"""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 datase... | 657 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
_lowercase : List[str] = {
"""configuration_audio_spectrogram_transformer""": [
"""AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINE... | 210 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class _lowerCAmelCase ( unittest.TestCase ):
def _a ( self ) -> Optional[Any]:
_Uppe... | 657 | 0 |
from math import factorial
snake_case_ : Union[str, Any] = {str(d): factorial(d) for d in range(10)}
def __a ( __UpperCAmelCase : int ) -> int:
"""simple docstring"""
return sum(DIGIT_FACTORIAL[d] for d in str(UpperCamelCase__ ) )
def _... | 488 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__magic_name__ = {
'''configuration_electra''': ['''ELECTRA_PRETRAINE... | 657 | 0 |
import operator as op
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : List[str] = []
SCREAMING_SNAKE_CASE : Union[str, Any] = lambda lowercase , lowercase : int(x / y ) # noqa: E731 integer division... | 62 |
"""simple docstring"""
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sente... | 657 | 0 |
from maths.prime_factors import prime_factors
def lowercase__( A ):
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
snake_case__ : List[Any] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(UpperCamelC... | 170 |
"""simple docstring"""
def __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
_UpperCAmelCase = f"Input value of [number={number}] must be an integer"
raise TypeError(UpperCamelCase__ )
if number < 0:
return Fals... | 657 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase : Dict = logging.get_logger(__name__)
lowercase : List[Any] = {
'''YituTech/conv-bert-base''':... | 568 |
"""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_available():
... | 657 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
"configuration_instructblip": [
"INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InstructBlipConfig",
"InstructBlipQ... | 117 |
"""simple docstring"""
def __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
def merge(UpperCamelCase__ , UpperCamelCase__ ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
ret... | 657 | 0 |
import qiskit
def __UpperCAmelCase ( __A = 2 ) -> Any:
'''simple docstring'''
UpperCAmelCase__ = qubits
# Using Aer's simulator
UpperCAmelCase__ = qiskit.Aer.get_backend("aer_simulator" )
# Creating ... | 475 |
"""simple docstring"""
import unittest
from transformers import 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 ModelTesterM... | 657 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_... | 168 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedu... | 657 | 0 |
'''simple docstring'''
from math import pi
def __SCREAMING_SNAKE_CASE ( _UpperCamelCase , _UpperCamelCase ):
"""simple docstring"""
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 620 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unle... | 657 | 0 |
import math
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 SchedulerMixin, SchedulerOutput
class A__ ( __UpperCAmelCase , __UpperCAmelCase ):
"""... | 302 |
"""simple docstring"""
def __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
return 10 - x * x
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
"""simple docstring"""
if equation(UpperCamelCase__ ) * equation(UpperCamelCase__ ) >= 0:
raise Val... | 657 | 0 |
'''simple docstring'''
import gc
import unittest
from transformers import CTRLConfig, 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_co... | 365 |
"""simple docstring"""
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
c... | 657 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase : Any = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_C... | 210 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__magic_name__ = {'''configuration_gpt_neox''': ['''GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXConfig''... | 657 | 0 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@req... | 488 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''YituTech/conv-bert-ba... | 657 | 0 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
snake_case = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned"""
""" Distillation""... | 62 |
"""simple docstring"""
def __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
return "".join([hex(UpperCamelCase__ )[2:].zfill(2 ).upper() for byte in list(UpperCamelCase__ )] )
def __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
if (len(UpperCam... | 657 | 0 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
lowerCamelCase : Any = ['small', 'medium', 'large']
lowerCamelCase : Any = 'lm_head.decoder.weight'
lowerCamelCase : Any = 'lm_head.weight'
def lowercase__( A ... | 170 |
"""simple docstring"""
def __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
try:
_UpperCAmelCase = float(UpperCamelCase__ )
except ValueError:
raise ValueError("Please enter a valid number" )
_UpperCAmelCase = decimal - int(UpperCamelCase__ )
if fractional_part == ... | 657 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase : Dict = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''VisionEncod... | 568 |
"""simple docstring"""
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
"""simple docstring"""
_UpperCAmelCase = {
"en": "Machine learning is grea... | 657 | 0 |
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
UpperCAmelCase__ = {
"facebook/maskformer-swin-base-ad... | 117 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=lowerCamelCase ):
lowercase_ : Dict = ['''torch''', '''torchsde''']
def __init__( self , *a_ , **a_ ) -> Optional[int]:
requires_backends(self ,... | 657 | 0 |
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_inpu... | 475 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
class _lowerCAmelCase ( lowerCamelCase ):
lowercase_ : Optional[Any]... | 657 | 0 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __A (__magic_name__ ):
snake_case :Optional[int] = (EulerDiscreteScheduler,)
... | 168 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import _LazyModule
__magic_name__ = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
__magic_name__ = _LazyModule(__name__,... | 657 | 0 |
from __future__ import annotations
from collections.abc import MutableSequence
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> None:
if len(SCREAMING_SNAKE_CASE_ ... | 658 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
__snake_case = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
... | 658 | 1 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
__snake_case = {
"""text_branch""": """text_model""",
"""audio_branch""": """audio_model.audio_encoder""",
"""attn""": """attention.self""",
"""se... | 658 |
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
__snake_case = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
"""text-classification""",
... | 658 | 1 |
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 transformers.utils i... | 658 |
from __future__ import annotations
from collections.abc import Callable
def _A ( SCREAMING_SNAKE_CASE__ : Callable[[int | float], int | float] , SCREAMING_SNAKE_CASE__ : int | float , SCREAMING_SNAKE_CASE__ : int | float , SCREAMING_SNAKE_CASE__ : int = 100 ... | 658 | 1 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _A ( SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : Dict=False ):
UpperCamelCase :Optional[int] = OmegaConf.load(SCREAMING_SNAKE_... | 658 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( lowercase ):
"""simple docstring"""
UpperCamelCase_ : Optional[int] =(CMStochasticIterativeScheduler,)
UpperCamelCase_ ... | 658 | 1 |
def _A ( SCREAMING_SNAKE_CASE__ : int = 10 , SCREAMING_SNAKE_CASE__ : int = 22 ):
UpperCamelCase :Union[str, Any] = range(1 , SCREAMING_SNAKE_CASE__ )
UpperCamelCase :Dict = range(1 , SCREAMING_SNAKE_CASE__ )
return sum(
1 for ... | 658 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnxConfig... | 658 | 1 |
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://openai... | 658 |
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
infer... | 658 | 1 |
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,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
to_channel_dim... | 658 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmR... | 658 | 1 |
print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
| 658 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_co... | 658 | 1 |
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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
__sn... | 658 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 658 | 1 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
__snake_case = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow("""""", """|""", """|"""),
dat... | 658 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :list[list[int]] = []
UpperCamelCase :list[int] = []
UpperCamelCase :List[str] = 0
UpperCamelCase ... | 658 | 1 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="""%(message)s""")
def _A ( SCREAMING_SNAKE_CASE__ : np.ndarray ):
return input_array.reshape((input_array.size, 1) )
def _A ( SCREAMING_SNAKE_C... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise ValueError('''check_bouncy() accepts only integer arguments''' )
UpperCamelCase :int = str(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :O... | 658 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {
"""configuration_trajectory_transformer""": [
"""TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""TrajectoryTransformerConfig""",
... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : str ):
UpperCamelCase :Union[str, Any] = hex_num.strip()
if not hex_num:
raise ValueError('''No value was passed to the function''' )
UpperCamelCase :str = hex_num[0] == '''-'''
if is_negative:
Upper... | 658 | 1 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, ... | 658 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : tuple[int, int] , SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase , UpperCamelCase :List[Any] = position
UpperCamelCase :Any = [
(y + 1, x + 2),
(y - 1, x + 2)... | 658 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = """▁"""
__snake_c... | 658 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class ... | 658 | 1 |
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def _A ( SCREAMING_SNAKE_CASE__ : Dict ):
UpperCamelCase :List[Any] = [
'''encoder.version''',
'''decoder.version''',
... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if length <= 0 or not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for n in range(SCREAMING_SNAKE_CASE__ )]
if __name__ ==... | 658 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""google/vivit-b-16x2-kinetics400""": (
"""https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json"""
),
... | 658 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 658 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logg... | 658 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__snake_case = 10
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , S... | 658 | 1 |
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def _A ( SCREAMING_SNAKE_CASE__ : Union[dict, list, tuple, torch.Tensor] ):
... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : list ):
_enforce_args(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ )
if n == 0:
return 0
UpperCamelCase :Union[str, Any] = float('''-inf''' )
for i in range(1 , n + 1 ... | 658 | 1 |
import heapq as hq
import math
from collections.abc import Iterator
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE_ ) -> Tuple:
UpperCamelCase :Any = str(id_ )
UpperCamelCase :U... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""microsoft/focalnet-tiny""": """https://hugg... | 658 | 1 |
import requests
from bsa import BeautifulSoup
def _A ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : dict ):
UpperCamelCase :Dict = BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE__ , params=SCREAMING_SNAKE_CASE__ ).content , '''html.parser''' ... | 658 |
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_configuration_commo... | 658 | 1 |
from __future__ import annotations
import unittest
from transformers import LEDConfig, 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
from ...test_pipeline_mixin... | 658 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_inf... | 658 | 1 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCAmelCase_ ( enum.Enum ):
... | 658 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfi... | 658 | 1 |
from __future__ import annotations
import os
from typing import Any
import requests
__snake_case = """https://api.github.com"""
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
__snake_case = BASE_URL + """/user"""
# https://github.com/setti... | 658 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
__snake_case = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
... | 658 | 1 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('''repo_id''' , ['''canonical_dataset_name''', '''org-name/dataset-name'''] )
@pytest.mark.parametrize('''path''' , ['''filename.csv''', '''filename with blanks.csv'''] )
@pytest.mark.par... | 658 |
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
__snake_case = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
"""text-classification""",
... | 658 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}
class UpperCAmel... | 658 |
from __future__ import annotations
from collections.abc import Callable
def _A ( SCREAMING_SNAKE_CASE__ : Callable[[int | float], int | float] , SCREAMING_SNAKE_CASE__ : int | float , SCREAMING_SNAKE_CASE__ : int | float , SCREAMING_SNAKE_CASE__ : int = 100 ... | 658 | 1 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class Up... | 658 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( lowercase ):
"""simple docstring"""
UpperCamelCase_ : Optional[int] =(CMStochasticIterativeScheduler,)
UpperCamelCase_ ... | 658 | 1 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if number > 0:
raise ValueError('''input must be a negative integer''' )
UpperCamelCase :Any = len(bin(SCREAMING_SNAKE_CASE__ )[3:] )
UpperCamelCase :Tuple = bin(abs(SCREAMING_SNAKE_CASE__ ) - (1 << ... | 658 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnxConfig... | 658 | 1 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataStructureLike, Pat... | 658 |
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
infer... | 658 | 1 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggi... | 658 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmR... | 658 | 1 |
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_utils import r... | 658 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_co... | 658 | 1 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding,... | 658 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 658 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json""",
# See all ViT MSN models at https:... | 658 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :list[list[int]] = []
UpperCamelCase :list[int] = []
UpperCamelCase :List[str] = 0
UpperCamelCase ... | 658 | 1 |
from typing import 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 import BatchFeature
from ....file_utils import P... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise ValueError('''check_bouncy() accepts only integer arguments''' )
UpperCamelCase :int = str(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :O... | 658 | 1 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
__snake_case = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : str ):
UpperCamelCase :Union[str, Any] = hex_num.strip()
if not hex_num:
raise ValueError('''No value was passed to the function''' )
UpperCamelCase :str = hex_num[0] == '''-'''
if is_negative:
Upper... | 658 | 1 |
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def _A ( SCREAMING_SNAKE_CASE__ : Optional[int] ):
... | 658 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : tuple[int, int] , SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase , UpperCamelCase :List[Any] = position
UpperCamelCase :Any = [
(y + 1, x + 2),
(y - 1, x + 2)... | 658 | 1 |
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
return x if y == 0 else greatest_common_divisor(SCREAMING_SNAKE_CASE__ , x % y )
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
return (x... | 658 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class ... | 658 | 1 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class UpperCAmelCase_ ( lowercase ):
"""simple docstring"""
def __in... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if length <= 0 or not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for n in range(SCREAMING_SNAKE_CASE__ )]
if __name__ ==... | 658 | 1 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("""3.8"""):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
__snake_case = """"""
... | 658 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 658 | 1 |
__snake_case = """
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.git
... | 658 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__snake_case = 10
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , S... | 658 | 1 |
import numpy as np
def _A ( SCREAMING_SNAKE_CASE__ : np.ndarray ):
return 1 / (1 + np.exp(-vector ))
def _A ( SCREAMING_SNAKE_CASE__ : np.ndarray ):
return vector * sigmoid(SCREAMING_SNAKE_CASE__ )
if __name__ == "__main__":
import doctest
doctest.te... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : list ):
_enforce_args(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ )
if n == 0:
return 0
UpperCamelCase :Union[str, Any] = float('''-inf''' )
for i in range(1 , n + 1 ... | 658 | 1 |
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
while b:
UpperCamelCase , UpperCamelCase :int = b, a % b
return a
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
r... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""microsoft/focalnet-tiny""": """https://hugg... | 658 | 1 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 658 |
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_configuration_commo... | 658 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""facebook/convnextv2-tiny-1k-224""": """http... | 658 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_inf... | 658 | 1 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if length <= 0 or not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for n in range(SCREAMING_SNAKE_CASE__ )]
if __name__ ==... | 658 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfi... | 658 | 1 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def _A ( SCREAMING_SNAKE_CASE__ : List[str] ):
if "model" in orig_key:
UpperCamelCase :Any = orig_key.replace('''model.''' , '''''' )
if "norm1" in orig_key:
UpperCa... | 658 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
__snake_case = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
... | 658 | 1 |
from __future__ import annotations
from random import random
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE_ = None ) -> Dict:
UpperCamelCase :Optional[int] = value
UpperCamelCase ... | 658 |
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
__snake_case = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
"""text-classification""",
... | 658 | 1 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : tuple[int, int] , SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase , UpperCamelCase :List[Any] = position
UpperCamelCase :Any = [
(y + 1, x + 2),
(y - 1, x + 2)... | 658 |
from __future__ import annotations
from collections.abc import Callable
def _A ( SCREAMING_SNAKE_CASE__ : Callable[[int | float], int | float] , SCREAMING_SNAKE_CASE__ : int | float , SCREAMING_SNAKE_CASE__ : int | float , SCREAMING_SNAKE_CASE__ : int = 100 ... | 658 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {"""vocab_file""": """sentencepiece.model... | 658 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( lowercase ):
"""simple docstring"""
UpperCamelCase_ : Optional[int] =(CMStochasticIterativeScheduler,)
UpperCamelCase_ ... | 658 | 1 |
__snake_case = {"""a""": ["""c""", """b"""], """b""": ["""d""", """e"""], """c""": [], """d""": [], """e""": []}
__snake_case = ["""a""", """b""", """c""", """d""", """e"""]
def _A ( SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE__ : List[Any] , ... | 658 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnxConfig... | 658 | 1 |
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 datasets import load_datase... | 658 |
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
infer... | 658 | 1 |
import re
def _A ( SCREAMING_SNAKE_CASE__ : str ):
UpperCamelCase :Dict = 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(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) )
if __... | 658 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmR... | 658 | 1 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
__snake_case = logging.getLogger(__name__)
class UpperCAmelCase_ ( lowercase ):
"""simple docstring"""
def... | 658 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_co... | 658 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTower/bridgetower-base/blob/ma... | 658 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 658 | 1 |
import baseaa
def _A ( SCREAMING_SNAKE_CASE__ : str ):
return baseaa.aaaencode(string.encode('''utf-8''' ) )
def _A ( SCREAMING_SNAKE_CASE__ : bytes ):
return baseaa.aaadecode(SCREAMING_SNAKE_CASE__ ).decode('''utf-8''' )
if __name__ == "__main__":
... | 658 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :list[list[int]] = []
UpperCamelCase :list[int] = []
UpperCamelCase :List[str] = 0
UpperCamelCase ... | 658 | 1 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
__snake_case = """\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},
title = {BLEU: a Method for Automatic... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise ValueError('''check_bouncy() accepts only integer arguments''' )
UpperCamelCase :int = str(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :O... | 658 | 1 |
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__snake_case = """
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplification},
authors={Xu, Wei a... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : str ):
UpperCamelCase :Union[str, Any] = hex_num.strip()
if not hex_num:
raise ValueError('''No value was passed to the function''' )
UpperCamelCase :str = hex_num[0] == '''-'''
if is_negative:
Upper... | 658 | 1 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__snake_case = 10
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , S... | 658 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : tuple[int, int] , SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase , UpperCamelCase :List[Any] = position
UpperCamelCase :Any = [
(y + 1, x + 2),
(y - 1, x + 2)... | 658 | 1 |
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
return "\n".join(
F'''{number} * {i} = {number * i}''' for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication_table(number=5, number_of_terms=10))
... | 658 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class ... | 658 | 1 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise ValueError('''check_bouncy() accepts only integer arguments''' )
UpperCamelCase :int = str(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :O... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if length <= 0 or not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for n in range(SCREAMING_SNAKE_CASE__ )]
if __name__ ==... | 658 | 1 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
__snake_case = {
"""cola""... | 658 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 658 | 1 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
... | 658 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__snake_case = 10
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , S... | 658 | 1 |
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
infer... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : list ):
_enforce_args(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ )
if n == 0:
return 0
UpperCamelCase :Union[str, Any] = float('''-inf''' )
for i in range(1 , n + 1 ... | 658 | 1 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStructTextConfig,
... | 658 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""microsoft/focalnet-tiny""": """https://hugg... | 658 | 1 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class UpperCAmelCase_ ( pl.LightningModule ):
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE... | 658 |
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_configuration_commo... | 658 | 1 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
__snake_case = ... | 658 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_inf... | 658 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 658 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfi... | 658 | 1 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""vocab_file""": """vocab.json""",
"""merges_fil... | 658 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
__snake_case = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Arora
... | 658 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__snake_case = {"""configuration_speech_encoder_decoder""": ["""SpeechEncoderDecoderConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAva... | 658 |
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
__snake_case = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
"""text-classification""",
... | 658 | 1 |
import math
def _A ( SCREAMING_SNAKE_CASE__ : int ):
assert isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif numb... | 658 |
from __future__ import annotations
from collections.abc import Callable
def _A ( SCREAMING_SNAKE_CASE__ : Callable[[int | float], int | float] , SCREAMING_SNAKE_CASE__ : int | float , SCREAMING_SNAKE_CASE__ : int | float , SCREAMING_SNAKE_CASE__ : int = 100 ... | 658 | 1 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : list[int] ):
UpperCamelCase :Optional[Any] = len(SCREAMING_SNAKE_CASE__ ) // 2
# choose the middle 3 elements
UpperCamelCase :Optional[Any] = lst[m - 1 : m + 2]
# if middle elem... | 658 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( lowercase ):
"""simple docstring"""
UpperCamelCase_ : Optional[int] =(CMStochasticIterativeScheduler,)
UpperCamelCase_ ... | 658 | 1 |
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers import Au... | 658 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""GroupViTOnnxConfig... | 658 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake_case = logging.get_logger(__name__)
__snake_case = {
"""microsoft/focalnet-tiny""": """https://hugg... | 658 |
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
infer... | 658 | 1 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, re... | 658 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmR... | 658 | 1 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class UpperCAmelCase_ ( unittest.TestCase ):
"""simple docstring"""
def ... | 658 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_co... | 658 | 1 |
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
__snake_case = parse(importlib.metadata.version("""torch"""))
def _A ( SCREAMING_SNAKE_CASE__ : Union[str, Version] , SCREAMING_SNAKE_C... | 658 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 658 | 1 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _A ( SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :int = int(number**0.5 )
return number == sq * sq
def _A ( SCREAMING_SNAKE_CASE__ : int , SCRE... | 658 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :list[list[int]] = []
UpperCamelCase :list[int] = []
UpperCamelCase :List[str] = 0
UpperCamelCase ... | 658 | 1 |
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__snake_case = get_tests_dir("""fixtures/test_sentencepiece_with_bytefallback.mo... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : int ):
if not isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise ValueError('''check_bouncy() accepts only integer arguments''' )
UpperCamelCase :int = str(SCREAMING_SNAKE_CASE__ )
UpperCamelCase :O... | 658 | 1 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def _A ( SCREAMING_SNAKE_CASE__ : Any ):
UpperCamelCase :Tuple = os.path.join(args.tf_model_dir , '''parameters.json''' )
UpperCamelCa... | 658 |
def _A ( SCREAMING_SNAKE_CASE__ : str ):
UpperCamelCase :Union[str, Any] = hex_num.strip()
if not hex_num:
raise ValueError('''No value was passed to the function''' )
UpperCamelCase :str = hex_num[0] == '''-'''
if is_negative:
Upper... | 658 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()... | 658 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : tuple[int, int] , SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase , UpperCamelCase :List[Any] = position
UpperCamelCase :Any = [
(y + 1, x + 2),
(y - 1, x + 2)... | 658 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils i... | 658 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class ... | 658 | 1 |
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