From b7bd0ea13e4dcda615bcfd9e7a59723271deddaa Mon Sep 17 00:00:00 2001
From: KetpuntoG <65235481+KetpuntoG@users.noreply.github.com>
Date: Tue, 12 Sep 2023 15:25:57 -0400
Subject: [PATCH] Update tutorial_learning2learn.py

---
 demonstrations/tutorial_learning2learn.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/demonstrations/tutorial_learning2learn.py b/demonstrations/tutorial_learning2learn.py
index 5bb97a1e61..b9e71b9031 100644
--- a/demonstrations/tutorial_learning2learn.py
+++ b/demonstrations/tutorial_learning2learn.py
@@ -248,7 +248,7 @@ def hamiltonian(params, **kwargs):
 
 # Since we use only one layer in QAOA, params have the shape 1 x 2,
 # in the form [[alpha, gamma]].
-x = tf.Variable([[0.5], [0.5]], dtype=tf.float32)
+x = tf.Variable([[0.5], [0.5]], dtype=tf.float64)
 
 # Evaluate th QAOA instance just created with some angles.
 print(cost(x))
@@ -546,7 +546,7 @@ def train_step(graph_cost):
 #
 
 # Parameters are randomly initialized
-x = tf.Variable(np.random.rand(2, 1))
+x = tf.Variable(np.random.rand(2, 1), dtype=tf.float64)
 
 # We set the optimizer to be a Stochastic Gradient Descent
 opt = tf.keras.optimizers.SGD(learning_rate=0.01)