'Run keras.Models.fit() in graph
How to run keras.model.fit() in graph not with eager execution...??
I tried to run my model in graph by using tf.compat.v1.disable_eager_execution(), but the code return error: numpy must be run with eager execution
The error appear after checkpoint model
I’m using tensorflow GpU 2.1.0 and keras 2.3.1
Solution 1:[1]
In tensorflow2.x, model.fit() runs in graph mode by default, you can control this behavior by using the run_eagerly argument in the model.compile(...) method, which defaults to False.
Solution 2:[2]
Even though eager mode is by default in TF2.x, under the hood keras.model.fit() run in graph mode for faster computation. If you want to use some advanced functionality of TF2.x and want to use graph mode as in TF1.x, then import tensorflow as follows
import tensorflow.compat.v1 as tf
Mixing functionality of TF1.x and TF2.x by using tf.compat.v1.disable_eager_execution() is not suggested. It could result in lot of issues down the line. Thanks!
Sources
This article follows the attribution requirements of Stack Overflow and is licensed under CC BY-SA 3.0.
Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Parham |
| Solution 2 | Vishnuvardhan Janapati |