[BUG] tensorflow autograph with finite diff and M1 Mac kills the kernel about pennylane HOT 4 CLOSED

I've managed to track down the problem to this line:

Why that would be causing a problem, I have no idea.

from pennylane.

And it seems to be fixed by switching np.linalg.solve with scipy.linalg.solve. 😕

from pennylane.

And an minimal example of the issue:

import tensorflow as tf

@tf.py_function(Tout=tf.float32)
def py_log_huber(x, m):
    print('Running with eager execution.')
    import numpy as np
    A = np.array([[1.0, 1.0], [0.0, 1.0]])
    b = np.array([0.0, 1.0])
    print(np.linalg.solve(A, b))
    return m**2 

x = tf.constant(1.0)
m = tf.constant(2.0)

print(py_log_huber(x,m).numpy())

@tf.function
def tf_wrapper(x):
  print('Tracing.')
  m = tf.constant(2.0)
  return py_log_huber(x,m)

print(tf_wrapper(x).numpy())

from pennylane.

It seems to me that tensorflow/python/eager/imperative_grad.py uses a pywrap_tfe.TFE_Py_TapeGradient, which access a memory address it isn't supposed to. Guess that the next step is to create a MRE and raise to TensorFlow team?

If you are fine with that then I would be happy to take the issue, otherwise let's discuss more.

from pennylane.