Seems like a tf version error in week 3 assignment.

My code:

```
# GRADED FUNCTION: sigmoid
def sigmoid(z):
"""
Computes the sigmoid of z
Arguments:
z -- input value, scalar or vector
Returns:
a -- (tf.float32) the sigmoid of z
"""
# tf.keras.activations.sigmoid requires float16, float32, float64, complex64, or complex128.
# (approx. 2 lines)
# z = ...
# a = ...
# YOUR CODE STARTS HERE
# Create a placeholder for x. Name it 'x'.
# tf.disable_eager_execution()
x = tf.placeholder(tf.float32, name="x")
# compute sigmoid(x)
sigmoid = tf.sigmoid(x)
# Create a session, and run it. Please use the method 2 explained above.
# You should use a feed_dict to pass z's value to x.
with tf.Session() as sess:
# Run session and call the output "result"
result = result = sess.run(sigmoid, feed_dict = {x: z})
# tf.convert_to_tensor(result, dtype=tf.float32)
# YOUR CODE ENDS HERE
return result
```

I keep getting this error. I tried `tf.disable_eager_execution()`

but then my result type is numpy.float

How do I fix this?