MFreidank

from keras import backend as K
from keras.optimizers import Optimizer


class Padam(Optimizer):
    def __init__(self, lr=1e-1, beta_1=0.9, beta_2=0.999,
                 epsilon=1e-8, decay=0., amsgrad=False, partial=1. / 4., **kwargs):
        """ Partially adaptive momentum estimation optimizer.

        # Arguments

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import tensorflow as tf
import os
os.environ["TF_DETERMINISTIC_OPS"] = "1"

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import tensorflow as tf
from tfdeterminism import patch
patch()

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import torch
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False

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"""
Created on Thu Oct 26 11:23:47 2017

Original Author:
@author: Utku Ozbulak - github.com/utkuozbulak

Changes for ResNet Compatibility:
Moritz Freidank - github.com/MFreidank
"""
import torch

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from collections import defaultdict
import importlib
from importlib.metadata import version
import json
import logging
from pathlib import Path
import sys


def getversion(module):

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from torch.utils.data import DataLoader


class InfiniteDataLoader(DataLoader):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        # Initialize an iterator over the dataset.
        self.dataset_iterator = super().__iter__()

    def __iter__(self):

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from abc import ABC
import json
import logging
import os

import torch
from transformers import AutoModelForSequenceClassification, AutoTokenizer

from ts.torch_handler.base_handler import BaseHandler