add test for BCE loss function #381

costar_google_brainrobotdata/test_grasp_loss.py

@@ -0,0 +1,37 @@
+import tensorflow as tf
+import numpy as np
+from keras.losses import binary_crossentropy
+import grasp_loss
+
+
+class grasp_loss_function_test(tf.test.TestCase):
+    """ Unit test for functions in grasp_loss.py
+    """
+    def test_single_pixel_measurement_index(self):
+        with self.test_session() as sess:
+            test_shape_width = 20
+            test_shape_height = 30
+            random_x_true = np.random.randint(0, test_shape_width)
+            random_y_true = np.random.randint(0, test_shape_height)
+            random_x_false = np.random.randint(0, test_shape_width)
+            random_y_false = np.random.randint(0, test_shape_height)
+            test_true_np = np.array([[1, random_y_true, random_x_true],
+                                     [0, random_y_false, random_x_false]],
+                                    dtype=np.float32)
+            test_pred_np = np.zeros((2, test_shape_height, test_shape_width, 1), dtype=np.float32)
+            test_pred_np[0, random_y_true, random_x_true, 0] = 1.0
+            test_pred_np[0, random_y_false, random_x_false, 0] = 0.0
+            test_pred_tf = tf.convert_to_tensor(test_pred_np, tf.float32)
+            test_true_tf = tf.convert_to_tensor(test_true_np, tf.float32)
+
+            measure_tf_true = grasp_loss.segmentation_single_pixel_binary_crossentropy(test_true_tf, test_pred_np)
+            measure_tf_true = sess.run(measure_tf_true)
+
+            direct_call_result = binary_crossentropy(test_true_tf[:, :1], tf.constant([[1.0], [0.0]], tf.float32))
+            direct_call_result = sess.run(direct_call_result)
+
+            assert np.allclose(measure_tf_true, np.array([0.0], dtype=np.float32), atol=1e-06)
+            assert np.allclose(direct_call_result, measure_tf_true)
+
+if __name__ == '__main__':
+    tf.test.main()