Tensorflow: Error when calling optimizer to minimize loss

I am trying to get tensorflow to minimize a loss function with respect to a variable, however, I keep getting an error and I am unsure of the cause. I have created a minimal example:

import tensorflow as tf

def loss_func(x, target):
    return tf.pow(x - target, 2) 

x = tf.Variable(initial_value=1., name='x', dtype=tf.float32)
target = tf.constant(value=10., dtype=tf.float32)
adam = tf.train.AdamOptimizer()
loss = lambda: loss_func(x, target)
adam_op = adam.minimize(loss, var_list=tf.trainable_variables)

When running this piece of code I get the error

AttributeError: 'function' object has no attribute '_id'

The above exception was the direct cause of the following exception:
Traceback (most recent call last):
  File "test.py", line 19, in <module>
    adam_op = adam.minimize(loss, var_list=tf.trainable_variables)
  File "C:...\optimizer.py", line 403, in minimize
    grad_loss=grad_loss)
  File "C:...\optimizer.py", line 461, in compute_gradients
    tape.watch(var_list)
  File "C:...\backprop.py", line 808, in watch
    tape.watch(self._tape, t)
  File "C:...\tape.py", line 59, in watch
    pywrap_tensorflow.TFE_Py_TapeWatch(tape._tape, tensor)  # pylint: disable=protected-access
SystemError: <built-in function TFE_Py_TapeWatch> returned a result with an error set

Does anyone know what it is I am doing wrong? Thank you. I am using tensorflow version 1.13.1