Tensorflow渴望没有keras

Question

With NO keras can you do eager execution in tensorflow? I have a non-neural network model in TensorFlow graph code to move to eager. This is a low rank matrix factorization for recommender system.

Python language.

Thank you

Request that answerers please demonstrate working code. If answer includes speculation then please state explicitly.

Answer 1

Yes, you can certainly use eager execution without Keras. Keras is built on top of the lower level operations that support eager execution.

For example:

import tensorflow as tf
import numpy as np
tf.enable_eager_execution()

W = tf.contrib.eager.Variable(tf.random_normal((10, 10)))

def model(x):
  return tf.matmul(x, W)

data = np.random.randn(3, 10).astype(np.float32)
print(model(data))

You can see some more detailed tutorials at https://www.tensorflow.org/tutorials/eager/

That said, there are various corner cases/errors you might hit if trying to run arbitrary code written to construct a graph with eager execution enabled, and slight refactoring may be needed. Those would depend on the details of how the code is structured.

The reverse (ie, writing code that works with eager execution enabled) generally works out well to construct the equivalent graph when eager execution is not enabled.

Hope that helps.