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 |
|---|---|---|---|---|
'''simple docstring'''
from math import factorial
def __snake_case ( UpperCAmelCase_ : int = 100 ):
return sum(int(UpperCAmelCase_ ) for x in str(factorial(UpperCAmelCase_ ) ) )
if __name__ == "__main__":
print(solution(int(input("""Enter the Number: """).strip()... | 55 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise Opti... | 356 |
'''simple docstring'''
_SCREAMING_SNAKE_CASE = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],
'''G''': ['''C''']... | 217 | 0 |
'''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_common import ModelTe... | 97 |
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
__lowerCAmelCase : str = False
__lowerCAmelCase : List[str] = True
__lowerCAmelCase : Union[str, Any] = False
... | 156 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase_ )
class _UpperCamelCase ( lowerCAmelCase_ ):
# `task` is not a ClassVar since ... | 353 |
def lowerCAmelCase_ ( UpperCamelCase_ ) -> list:
UpperCamelCase_ = int(UpperCamelCase_ )
if n_element < 1:
UpperCamelCase_ = ValueError("a should be a positive number" )
raise my_error
UpperCamelCase_ = ... | 328 | 0 |
"""simple docstring"""
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
re... | 91 |
"""simple docstring"""
def _A (__a = 50 ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
... | 91 | 1 |
'''simple docstring'''
import os
from collections.abc import Iterator
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(SCREAMING_SNAKE_CASE__ ):
UpperCAmelCase__ = [d for d in dir_names if ... | 61 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
UpperCAmelCase_ = logging.get_logger(__name__)
... | 61 | 1 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
a_ : Optional[Any] = logging.g... | 75 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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
#
# ... | 53 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
_snake_case : str = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
_snake_case... | 350 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 207 | 0 |
'''simple docstring'''
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
UpperCamelC... | 23 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():... | 217 | 0 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('''>=''', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distri... | 358 |
"""simple docstring"""
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils i... | 38 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : str = logging.get_logger(__name__)
UpperCAmelCase_ : List[str] = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class lo... | 91 |
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration,
MusicgenProcessor,
... | 328 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=_UpperCamelCase )
class __UpperCAmelCase ( _UpperCamelCase ):
'''simpl... | 18 | '''simple docstring'''
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def _UpperCAmelCase ( _UpperCamelCase : Tuple, _UpperCamelCase : Tuple, _UpperCamelCase : List[str] ) -> int:
A_ = {
'''en''': '''... | 18 | 1 |
"""simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
... | 61 |
"""simple docstring"""
import os
_a = {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1_000}
def __a ( __lowerCamelCase ):
UpperCAmelCase_ : Union[str, Any] = 0
UpperCAmelCase_ : List[str] = 0
while index < len(__lowerCamelCase... | 61 | 1 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_u... | 140 |
from scipy.stats import spearmanr
import datasets
__lowerCamelCase : List[str] = """
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0 implying no correlation.
Positive... | 140 | 1 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class __A(... | 6 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _UpperCAmelCase ( ... | 207 | 0 |
from jiwer import compute_measures
import datasets
__A = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: improved evaluation measures for connected spe... | 364 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A = {
'''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig'''],
}
try:
if not is_torch_available():
raise OptionalDependenc... | 278 | 0 |
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():
impor... | 7 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.du... | 38 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescal... | 251 |
'''simple docstring'''
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_... | 251 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : List[Any] = logging.get_logger(__name__)
__lowerCamelCase : List[str] = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV... | 18 | from __future__ import annotations
from math import pi, sqrt
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : float ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise ValueErro... | 18 | 1 |
snake_case : List[str] = frozenset(
[
'''prompt''',
'''height''',
'''width''',
'''guidance_scale''',
'''negative_prompt''',
'''prompt_embeds''',
'''negative_prompt_embeds''',
'''cross_attention_kwargs''',
]
)
snake_case : Opti... | 368 |
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.utils.data import DataLoader, Rand... | 281 | 0 |
def UpperCamelCase ( __lowercase : int = 10_00 ):
'''simple docstring'''
A_ : Tuple = -1
A_ : List[str] = 0
for a in range(1 ,n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
A_ : List[str] = (n *... | 140 | from queue import PriorityQueue
from typing import Any
import numpy as np
def UpperCamelCase ( __lowercase : dict ,__lowercase : str ,__lowercase : set ,__lowercase : set ,__lowercase : dict ,__lowercase : dict ,__lowercase : P... | 140 | 1 |
"""simple docstring"""
def _A ( UpperCamelCase_ : str, UpperCamelCase_ : list[str]) -> str:
'''simple docstring'''
__lowercase = ""
for word_or_phrase in separated:
if not isinstance(UpperCamelCase_, UpperCamelCase_):
raise Exception("join() ac... | 350 |
"""simple docstring"""
import argparse
import os
import re
_a = 'src/transformers/models/auto'
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
_a = re.compile(r'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+Order... | 144 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=__UpperCAmelCase ):
'''simple docstring'''
UpperCamelCase_ : int = ["""speech"""]
def __init__( self : Di... | 319 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCamelCase ( _A ):
lowerCAmelCase_ = 384
... | 278 | 0 |
"""simple docstring"""
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config... | 309 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : list[int] , _UpperCAmelCase : str ):
lowerCAmelCase = int(_UpperCAmelCase )
# Initialize Result
lowerCAmelCase = []
# Traverse through all denomination
for denomination in reversed(_UpperCAmelCa... | 309 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase_ = {
"configuration_instructblip": [
"INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InstructBlipConfig",... | 251 |
'''simple docstring'''
from itertools import product
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = sides_number
SCREAMING_SNAKE_CASE : str = max_face_number * dic... | 251 | 1 |
def __lowerCamelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowercase__ : List[Any] = int(lowerCamelCase__ )
# Initialize Result
lowercase__ : Tuple = []
# Traverse through all denomina... | 363 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer, Fl... | 121 | 0 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_to... | 86 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowerCAmelCase_ ( _snake_case : str = "laptop" ) -> DataFrame:
'''simple docstring'''
__magic_name__ : Tuple = F'''https://www.amazon.in/laptop/s?k={product... | 281 | 0 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import log... | 122 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_co... | 122 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase: int = logging.get_logger(__name__)
_lowercase: List[str] = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/google/pix2struct-te... | 227 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import D... | 144 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
'''distilbert-base-unc... | 174 |
'''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBe... | 174 | 1 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
f... | 309 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
UpperCamelCase_ = logging.get_logger(__name__)
class a_ (_a ):
def __init__( self , *snake_case_ , **snake_case_ ):
warnings.w... | 309 | 1 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def snake_case (__lowercase , __lowercase , __lowercase ) -> int:
'''simple docstring'''
_snake_case : Optional[int] = ("dense.weight", "attention.sel... | 284 | # Copyright 2023 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
#
# Unless required by applicabl... | 284 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase = {
'configuration_instructblip': [
'INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InstructBlipConfig',
'Instruc... | 173 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ : Dict = logging.get_logger(__name__)
UpperCAmelCase__ : Union[str, Any] = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/... | 121 | 0 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = 0
SCREAMING_SNAKE_CASE_ = 0
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : Optional[Any] ,... | 210 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class lowerCamelCase_ ( _SCREAMING_S... | 210 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple repository c... | 122 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
renew_... | 122 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( __a , unittest.TestCase ):
lowerCAme... | 360 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import Mode... | 299 | 0 |
'''simple docstring'''
def __magic_name__( lowerCamelCase = 1_0, lowerCamelCase = 2_2):
__lowerCAmelCase = range(1, lowerCamelCase)
__lowerCAmelCase = range(1, lowerCamelCase)
return sum(
1 for power in powers for base in bases if len(str(base**power)... | 174 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : Optional[Any] = {
"""config... | 174 | 1 |
"""simple docstring"""
def lowercase__(A , A ) ->float:
"""simple docstring"""
return base * power(lowercase_ , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print("""Raise base to the power of exponent using recursi... | 357 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
... | 150 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case : Tuple = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'AutoformerConfig',
... | 284 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_... | 284 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
SCREAMING_SNAKE_CASE_ = ['small', 'medium', 'large']
SCREAMING_SNAKE_CASE_ = 'lm_head.decoder.weight'
SCREAMING_SNAKE_CASE_ = 'lm_head.weight'
def __SCREAMING_SNA... | 353 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface/autoformer-touri... | 189 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : str = logging.get_logger(__name__)
__a : int = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json""",
# See all W... | 210 | import argparse
import gc
import json
import os
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator,... | 210 | 1 |
import os
import unicodedata
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
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_fi... | 90 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 1 |
"""simple docstring"""
from manim import *
class lowerCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : Union[str, Any]):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ : Union[str, Any] ... | 91 |
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class UpperCamelCase__ ( __... | 299 | 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
from ..auto import CONFIG_MAPPING
lowerCAmelCase :List[str] = logging... | 275 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow ha... | 275 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class UpperCAmelCase :
_lowercase: int
_lowercase: TreeNode | None = None
_lowercase: TreeNode | No... | 70 | """simple docstring"""
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
SCREAMING_SNAKE_CASE__ = HfArgumentParser(InitializationArguments)
SCREAMING_SNAKE_CASE__ = parser.parse_args()
... | 150 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mod... | 111 |
'''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()
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {name: getattr(transformers, name + 'Fast... | 111 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
... | 65 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from... | 189 | 0 |
"""simple docstring"""
def UpperCAmelCase ( ):
'''simple docstring'''
return 1
def UpperCAmelCase ( a_ ):
'''simple docstring'''
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def UpperCAmelCase ( a_ ):
'''simple docstring'''
return 0 if x < 0 else five... | 367 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
... | 205 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
... | 90 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common impo... | 90 | 1 |
"""simple docstring"""
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCamelCase_ = version.parse(importlib_metadata.version('''nltk'''))
if NLTK_VERSION >= version.Version('''3.6.4'''):
from nltk import word... | 356 |
"""simple docstring"""
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class UpperCamelCase_ :
def __init__( self : Optional[Any] , lowerCAmelCase_ : Collection[float] | None = None ) -> ... | 253 | 0 |
from manim import *
class lowerCamelCase (_snake_case ):
'''simple docstring'''
def __UpperCAmelCase ( self ) -> Any:
UpperCAmelCase_ : Tuple = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase_ ... | 29 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def __lowerCamelCase ( ... | 274 | 0 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def A(__a: Tuple ):
monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings" , set() )
@pytest.fixture
def A(__a: int ):
class __magic_name__ :
... | 22 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TimeSeriesTransformerConfig''... | 22 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__lowerCamelCase )
class __snake_case ( __lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase... | 111 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__UpperCAmelCase : Union[str, Any] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDepend... | 111 | 1 |
"""simple docstring"""
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
SCREAMING_SNAKE_CASE__ = "."
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = os.path.join(REPO_PATH, "utils/d... | 149 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE__ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm": ... | 149 | 1 |
import os
import sys
import unittest
UpperCAmelCase__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, re... | 339 |
import os
def a ( A__ : str = "input.txt" ) -> int:
"""simple docstring"""
with open(os.path.join(os.path.dirname(A__ ) , A__ ) ) as input_file:
_lowercase =[
[int(A__ ) for element in line.split(','... | 205 | 0 |
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
lowerCAmelCase_ = {
"""debug""... | 260 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common impor... | 260 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__a = {
"configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"],
}
try:
if not is_torch_a... | 66 |
import os
def A_ ( a = "matrix.txt" ):
"""simple docstring"""
with open(os.path.join(os.path.dirname(a ) , a ) ) as in_file:
SCREAMING_SNAKE_CASE_ : Dict = in_file.read()
SCREAMING_SNAKE_CASE_ : Dict = [[int(a ) fo... | 253 | 0 |
def lowerCamelCase ( a_ , a_ ) -> int:
return int(input_a == input_a == 0 )
def lowerCamelCase ( ) -> None:
print('Truth Table of NOR Gate:' )
print('| Input 1 | Input 2 | Output |' )
print(F'''| 0 ... | 14 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impor... | 14 | 1 |
'''simple docstring'''
from torch import nn
def UpperCAmelCase_ ( __lowercase : Optional[int] ) -> int:
'''simple docstring'''
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn ==... | 22 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"kwargs, expected" , [
({"num_shards": 0, "max_num_jobs": 1}, []),
({"num_shards": 10, "max_num_jobs": 1}, [range... | 22 | 1 |
'''simple docstring'''
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = [[0 for _ in range(__A )] for _ in range(m + 1 )]
for i in range(m + 1 ):
__UpperCamelCase = 1
for n in range(m + 1 ):
for k in range(1 ,__A ):... | 243 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
a__ : Optional[Any] = logging.getLogger(__name__)
class UpperCAmelCase__ ... | 243 | 1 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from s... | 149 |
from torch import nn
def lowerCAmelCase_ ( A_):
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(F"Unsupported activation funct... | 149 | 1 |
"""simple docstring"""
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def _lowe... | 259 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mode... | 259 | 1 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : list ):
'''simple docstring'''
for i in range(len(_SCREAMING_SNAKE_CASE ) - 1 , 0 , -1 ):
_UpperCAmelCase = False
for j in range(_SCREAMING_SNAKE_CASE , 0 ... | 260 |
"""simple docstring"""
def lowercase ( ):
'''simple docstring'''
_UpperCAmelCase = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
_UpperCAmelCase = 6
_UpperCAmelCase = 1
_UpperCAmelCase = 1901
_UpperCAmelCase ... | 260 | 1 |
"""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 |
"""simple docstring"""
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def _lowerCAmelCase ( lowerCAmelCase ):
... | 248 | 1 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> int:
"""simple docstring"""
return int(input_a == input_a == 0 )
def SCREAMING_SNAKE_CASE ( ) -> None:
"""simple docstring"""
print('''Truth Table of NOR Gate:''' )... | 14 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> Any:
"""simple docstring"""
A__ = [0] * len(lowercase_ )
A__ = []
A__ = [1] * len(lowercase_ )
for values in graph.values():
for i in values:
... | 14 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_tor... | 353 |
"""simple docstring"""
import pprint
import requests
UpperCAmelCase: Tuple = """https://zenquotes.io/api"""
def __SCREAMING_SNAKE_CASE ( ):
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def __SCREAMING_SNAKE_CASE ( ):
return requests.ge... | 336 | 0 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) ->int:
"""simple docstring"""
a_ = 0
if start < end:
a_ = randint(UpperCAm... | 243 |
"""simple docstring"""
import math
import os
import sys
def UpperCamelCase ( UpperCAmelCase ) ->str:
"""simple docstring"""
a_ = ""
try:
with open(UpperCAmelCase , "rb" ) as binary_file:
a_ = binary_file.read()
for dat in data:
a_ ... | 243 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
fro... | 228 |
'''simple docstring'''
from collections.abc import Iterable
from typing import Any
class a__ :
'''simple docstring'''
def __init__( self , lowerCamelCase_ = None ) -> List[str]:
lowerCAmelCase__ = value
... | 228 | 1 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : list[float] , SCREAMING_SNAKE_CASE__ : Dict ):
print(F'''Vertex\tShortest Distance from vertex {src}''' )
for i, d in enumerate(SCREAMING_SNAKE_CASE__ ):
print(F'''{i}\t\t{d}''' )
def ... | 259 |
def _A ( SCREAMING_SNAKE_CASE__ : list[int] , SCREAMING_SNAKE_CASE__ : list[int] ):
UpperCamelCase :Tuple = len(SCREAMING_SNAKE_CASE__ )
print('''The following activities are selected:''' )
# The first activity is always selected
UpperCamelCase ... | 259 | 1 |
"""simple docstring"""
def a_ ( _lowercase , _lowercase ):
"""simple docstring"""
_UpperCamelCase : int = [1]
for i in range(2 , _lowercase ):
factorials.append(factorials[-1] * i )
ass... | 371 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def a_ ( _lowercase ):
return choice(_lowercase )
def a_ ( _lowercase , _lowercase ):
_UpperCamelCase : Optional[int] = ... | 128 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attention... | 248 |
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
class A__(a_ ):
"""sim... | 248 | 1 |
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
__A = {
"linear": PIL.Image.Resampling.BILINEAR,
"bilinear": PIL.Image.Resampling.BILINEAR,
... | 348 |
import sys
from collections import defaultdict
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> Union[str, Any]:
'''simple docstring'''
__lowerCamelCase = []
def lowercase_ ( self ... | 348 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCAmelCase_ : Tuple = {"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTCo... | 200 |
# Copyright 2022 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
#
# Unless required by applica... | 336 | 0 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowercase :
def __init__( self , snake_case , snake_case , snake_case ):
if dst_width < 0 or dst_height < 0:
raise ValueError('Destination width/height shoul... | 200 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase : str = logging.get_logger(__name__)
_UpperCAmelCase : int = {
"""google/canine-s""": """https://huggingface.co/google/canine-s/resolve/main/config.json""",
# See all CANINE mode... | 200 | 1 |
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 228 |
from __future__ import annotations
def __A ( __lowerCamelCase , __lowerCamelCase ) -> float:
a = sorted(numsa + numsa )
a , a = divmod(len(__lowerCamelCase ) , 2 )
if mod == 1:
return all_numbers[div]
else:
ret... | 228 | 1 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def A_ ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Tuple:
# Initialis... | 361 |
class A__ : # Public class to implement a graph
def __init__( self , A_ , A_ , A_ ):
'''simple docstring'''
UpperCamelCase : Optional[int] = row
UpperCamelCase : Any = col
UpperCamelCase : Optional[Any] ... | 140 | 0 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
_A : Dict =6_378_137.0
_A : str =6_356_752.314_245
_A : Union[str, Any] =6_378_137
def SCREAMING_SNAKE_CASE_ (Upper... | 41 |
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
UpperCAmelCase : Tuple ... | 128 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperC... | 350 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase = {"""configu... | 234 | 0 |
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
__snake_case = {
'''linear''': PIL.Image.Resampling.BILINEAR,
'''bilinear''': PIL.Image.Resampling.BILINEA... | 348 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''OPTConfig''']}
... | 348 | 1 |
from math import factorial, radians
def __UpperCamelCase (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = 18 , _SCREAMING_SNAKE_CASE = 10 ) -> float:
lowercase__ = angle_in_degrees - ((angle_in_degrees // 3_6_0.0) * 3_6_0.0)
# Converting from degrees ... | 269 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase )
class SCREAMING_SNAKE_CASE (UpperCAmelCase ):
_UpperCamelCase : str = field(default='language-m... | 269 | 1 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto i... | 221 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class A ( nn.Module ):
UpperCamelCase__ : int
UpperCamelCase__ : int
UpperCamelCase__ : fl... | 199 | 0 |
import os
import sys
import unittest
_snake_case = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_test... | 300 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from... | 300 | 1 |
'''simple docstring'''
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
... | 198 | import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
_UpperCAmelCase = """scheduler_config.json"""
class UpperCAmelCase ( __A ):
'''simple docstring'... | 140 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, ... | 102 |
def _a ( SCREAMING_SNAKE_CASE_ : List[Any] ):
__lowerCAmelCase , __lowerCAmelCase = [], []
while len(SCREAMING_SNAKE_CASE_ ) > 1:
__lowerCAmelCase , __lowerCAmelCase = min(SCREAMING_SNAKE_CASE_ ), max(SCREAMING_SNAKE_... | 102 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from tra... | 254 |
'''simple docstring'''
def __lowerCAmelCase (__lowerCAmelCase = 50 ):
_UpperCAmelCase : Tuple = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(... | 234 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def SCREAMING_SNAKE_CASE_ () -> Union[str, Any]:
lowerCamelCase__ : Union[str, Any] = {
... | 129 |
'''simple docstring'''
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
_A : str ={
'''sample_size''': 32,
'''in_channels''': 3,
'''out_channels'... | 129 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def _lowercase ( ) -> Generator[int, None, None]:
__lowerCAmelCase : dict[int, int] = {}
__lowerCAmelCase : List[Any] = 2
w... | 269 |
"""simple docstring"""
import os
from math import logaa
def _lowercase ( __snake_case = "base_exp.txt" ) -> int:
__lowerCAmelCase : float = 0
__lowerCAmelCase : Any = 0
for i, line in enumerate(open(os.path.join(os.path.d... | 269 | 1 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
UpperCamelCase_ = logging.getLogger(__name__)
if __name__ == "__main__":
Up... | 359 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNetYaa... | 59 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
fro... | 300 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion import Stabl... | 300 | 1 |
"""simple docstring"""
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import (
BackboneOutput,
BaseModelOutputWithNoAttention... | 303 |
"""simple docstring"""
import unittest
from transformers import BertGenerationConfig, 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_modelin... | 303 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
SCREAMING_SNA... | 102 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_di... | 102 | 1 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@datacla... | 348 |
import requests
__A = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def lowerCamelCase_ ( UpperCamelCase__ : str ) -> None:
"""simple docstring"""
__lowerCamelCase = requests.get(_NEWS_API + bbc_news_api_key ).jso... | 348 | 1 |
# Copyright 2022 The HuggingFace Team and The OpenBMB 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
#
# Unl... | 129 |
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
__snake_case : Dict =logging.get_logger(__name__)
... | 129 | 1 |
"""simple docstring"""
from torch import nn
class lowercase( nn.Module ):
'''simple docstring'''
def __init__( self: List[Any], a_: Optional[int], a_: Union[str, Any] ):
'''simple docstring'''
super().__init__()
_snake_cas... | 369 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCAmelCase__ (snake_case__ : int = 3 ):
"""simple docstring"""
if isinstance(snake_case__ , snake_case__ ):
... | 132 | 0 |
def lowercase__ ( __snake_case : int ):
'''simple docstring'''
UpperCAmelCase_ : list[list[int]] = [[0 for _ in range(__snake_case )] for _ in range(m + 1 )]
for i in range(m + 1 ):
UpperCAmelCase_ : Optional[A... | 29 |
__lowerCamelCase = {
"joule": 1.0,
"kilojoule": 10_00,
"megajoule": 1_00_00_00,
"gigajoule": 10_00_00_00_00,
"wattsecond": 1.0,
"watthour": 36_00,
"kilowatthour": 3_60_00_00,
"newtonmeter": 1.0,
"calorie_nutr": 41_86.8,
"kilocalorie_nutr": 4_18_68_00.00,
... | 59 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ ={'processing_layoutxlm': ['LayoutXLMProcessor']}
try:
if... | 353 |
import os
import unicodedata
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
UpperCamelCase__ =logging.get_logger(__name__)
UpperCamelCase__ ... | 325 | 0 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
lowercase_ = logging.getLogger(__name__)
class __UpperCamelCase ( lowerCAmelCase__ ):
"""simple... | 303 |
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_collator... | 303 | 1 |
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 lowercase( UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ ) -> ... | 363 | from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interle... | 165 | 0 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffusers.... | 348 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case = {
'''configuration_bloom''': ['''BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BloomConfig''', '''BloomOnnxConfig'''],
}
try:
if not is_tokenizers... | 348 | 1 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> str:
return "".join(sorted(__UpperCAmelCase ) )
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> ... | 359 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
lowerCamelCase__ : List[Any] = logging.get_logger(__name__) # pylint: disable=invalid-name
class lowerCa... | 210 | 0 |
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