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Mar 29, 2020 · The upcoming (at the time of writing) release of TensorFlow version 2.2 addsexciting new functionality to the tf.keras API that allows users to easilycustomize the train, test, and predict logic of Keras models.One of the best examples of a deep learning model that requires specializedtraining logic is agenerative adversarial network (GAN),and in this post will use TensorFlow 2.2 release ...

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import tensorflow as tf import numpy as np import datetime import matplotlib.pyplot as plt %matplotlib inline from tensorflow.examples.tutorials.mnist import input_data mnist = input_data.read_data_sets("MNIST_data/") MNIST中每个图像的初始格式是一个784维的向量。可以使用reshape还原成28x28的图像。

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Oct 14, 2020 · import tensorflow_docs.vis.embed as embed embed.embed_file(anim_file) Next steps. This tutorial has shown the complete code necessary to write and train a GAN. As a next step, you might like to experiment with a different dataset, for example the Large-scale Celeb Faces Attributes (CelebA) dataset available on Kaggle.

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Jan 01, 2019 · This blog-post is the subsequent part of my previous article where the fashion MNIST data-set was described. Also, we wrote data loader functions in the blog-post. In this article, we will focus on writing python implementation of fully connected neural network model using tensorflow.

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Jul 23, 2019 · Training an LC-GAN to constrain the generated samples to a region of the latent space. We can see this LC-GAN in practice, using the SketchRNN drawings. The first row of each section below is the prior, and the second row is the LC-GAN output.

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Apr 28, 2019 · The GAN-generated image looks very similar to the original image, but if you look closely at the headband you'll see that the GAN didn't reproduce the starburst pattern from the original. Instead, it made up its own plausible pattern to replace the pattern erased by the down-sampling. For more information, see Ledig et al, 2017. Face Inpainting 07_GAN_MNIST_Digit_Generator ... The workflow builds the generator network using the Keras Layer nodes and then trains and applies it using the TensorFlow 2 integration.

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