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TensorFlow 2.0中的tf.contrib.layers.recompute_grad在哪里？

[英]Where is tf.contrib.layers.recompute_grad in TensorFlow 2.0?

原文 2019-04-03 22:41:19 1 1 python/ tensorflow

Does TensorFlow 2.0 have any support for making a computation as "recompute during the gradient pass" to save memory? TensorFlow 2.0是否支持将计算作为“渐变过程中的重新计算”以节省内存？ TensorFlow 1.x has tf.contrib.layers.recompute_grad , but contrib is gone in TF 2.0 and it doesn't look like anyone moved recompute_grad . TensorFlow 1.x具有tf.contrib.layers.recompute_grad ，但是contrib在TF 2.0中已经消失了，看起来好像没有人搬过 recompute_grad 。

1 个解决方案

Ya, they didn't move it. 是的，他们没有移动它。 This is a big error on Google's part. 这是Google的重大错误。 I won't move to Tensorflow 2 for this reason. 因此，我不会移至Tensorflow 2。 Recomputing gradients and creating memory efficient graphs is EXTREMELY helpful, if not vital. 重新计算梯度并创建内存有效的图形非常有用，即使不是很重要。

将 tf.contrib.layers.batch_norm 迁移到 Tensorflow 2.0 - Migrate tf.contrib.layers.batch_norm to Tensorflow 2.0

重写 Tensorflow 2.0 中的 tf.contrib.layers.batch_norm - Rewrite tf.contrib.layers.batch_norm in Tensorflow 2.0

TensorFlow - tf.layers vs tf.contrib.layers - TensorFlow - tf.layers vs tf.contrib.layers

Tensorflow：tf.contrib.layers.embed_sequence - Tensorflow: tf.contrib.layers.embed_sequence

Tensorflow 2 中的 tf.contrib.layers.fully_connected()？ - tf.contrib.layers.fully_connected() in Tensorflow 2?

Tensorflow2.0：`tf.contrib.layers.fully_connected` 的替代品是什么？ - Tensorflow2.0: What is the replacement of `tf.contrib.layers.fully_connected`?

如何将 tf.contrib 转换为 Tensorflow 2.0 - How to convert tf.contrib to Tensorflow 2.0

Tensorflow：将手动构建图层转换为tf.contrib.layers - Tensorflow: Transforming manually build layers to tf.contrib.layers

Tensorflow 2.x - tf.contrib.layers.variance_scaling_initializer() - Tensorflow 2.x - tf.contrib.layers.variance_scaling_initializer()

Tensorflow tf.layers，tf.contrib.layers不适用于可变范围 - Tensorflow tf.layers, tf.contrib.layers not working with variable scope

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