From b37f675396668c0f76524fed4f75994b535ad9d4 Mon Sep 17 00:00:00 2001 From: elad-c Date: Sun, 22 Sep 2024 09:24:29 +0300 Subject: [PATCH] fix test --- .../feature_networks/const_representation_test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/tests/keras_tests/feature_networks_tests/feature_networks/const_representation_test.py b/tests/keras_tests/feature_networks_tests/feature_networks/const_representation_test.py index a597a4a76..11754f504 100644 --- a/tests/keras_tests/feature_networks_tests/feature_networks/const_representation_test.py +++ b/tests/keras_tests/feature_networks_tests/feature_networks/const_representation_test.py @@ -156,7 +156,7 @@ def create_networks(self): as_const = lambda v: np.random.random(v.shape.as_list()).astype(np.float32) inputs = layers.Input(shape=self.get_input_shapes()[0][1:]) inds = tf.reshape(tf.argmax(tf.reshape(inputs, (-1, 32 * 32, 16)), axis=1), (-1, 1, 1, 16)) - b = tf.gather(np.random.random((100,)).astype(np.float32), inds) + b = tf.gather(np.random.random((2000,)).astype(np.float32), inds) x = tf.add(inputs, b) x = layers.Concatenate()([x, np.random.random((1, 32, 32, 3)), x, np.random.random((1, 32, 32, 3))]) x1 = layers.Add()([np.random.random((1, x.shape[-1])), x, np.random.random((1, x.shape[-1]))])