NOTE: commands and UI are deprecated
- Negative Engineering
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- Introduction to Prefect 2.0
- First Prefect flow and Basics
| # Author: Ygor Rebouças | |
| # | |
| ### The Training Loop | |
| # | |
| # 0) Imports | |
| import tensorflow as tf | |
| import numpy as np |
| import numpy as np | |
| import tensorflow as tf | |
| from PIL import Image | |
| from tensorflow import keras | |
| import coremltools | |
| import tfcoreml as tf_converter | |
| import tensorflow.keras.backend as K | |
| import datetime | |
| import os | |
| from tensorflow.python.framework import graph_io |
| // | |
| // RecordAudio.swift | |
| // | |
| // This is a Swift class (updated for Swift 5) | |
| // that uses the iOS RemoteIO Audio Unit | |
| // to record audio input samples, | |
| // (should be instantiated as a singleton object.) | |
| // | |
| // Created by Ronald Nicholson on 10/21/16. | |
| // Copyright © 2017,2019 HotPaw Productions. All rights reserved. |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| import tensorflow as tf | |
| import tensorflow.keras.layers as layers | |
| import tensorflow.keras.losses as loss | |
| import tensorflow_datasets.public_api as tfds | |
| from sys import argv | |
| from random import Random | |
| from os import walk |
| from collections import defaultdict | |
| from keras.callbacks import Callback | |
| class WRWDScheduler(Callback): | |
| """Warm restart scheduler for optimizers with decoupled weight decay | |
| This Keras callback should be used with TensorFlow optimizers | |
| with decoupled weight decay, such as tf.contrib.opt.AdamWOptimizer | |
| or tf.contrib.opt.MomentumWOptimizer. Warm restarts include | |
| cosine annealing with periodic restarts for both learning rate |
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