From 26fd0e30791e956a135fce6f1ea71d3c02ccbd05 Mon Sep 17 00:00:00 2001
From: Franck Mamalet <49721198+franckma31@users.noreply.github.com>
Date: Thu, 7 Nov 2024 17:54:24 +0100
Subject: [PATCH] clean test_condense

---
 tests/test_condense.py | 42 ------------------------------------------
 1 file changed, 42 deletions(-)

diff --git a/tests/test_condense.py b/tests/test_condense.py
index 64c5443..0c6cb7c 100644
--- a/tests/test_condense.py
+++ b/tests/test_condense.py
@@ -236,23 +236,11 @@ def test_model(layer_type, layer_params, k_coef_lip, input_shape):
         steps_per_epoch=steps_per_epoch,
         callbacks=callback_list,
     )
-    # model.__getattribute__(FIT)(
-    #     linear_generator(batch_size, input_shape, kernel),
-    #     steps_per_epoch=steps_per_epoch,
-    #     epochs=epochs,
-    #     verbose=0,
-    #     callbacks=callback_list,
-    # )
     # the seed is set to compare all models with the same data
     np.random.seed(42)
     # get original results
     test_dl = linear_generator(batch_size, input_shape, kernel)
     loss, mse = uft.run_test(model, test_dl, loss_fn, metrics, steps=10)
-    # loss, mse = model.__getattribute__(EVALUATE)(
-    #     linear_generator(batch_size, input_shape, kernel),
-    #     steps=10,
-    #     verbose=0,
-    # )
     # generate vanilla
     if vanilla_require_a_copy():
         model2 = get_model(layer_type, layer_params, input_shape, k_coef_lip)
@@ -267,29 +255,16 @@ def test_model(layer_type, layer_params, k_coef_lip, input_shape):
         loss=uft.MeanSquaredError(),
         metrics=[uft.metric_mse()],
     )
-    # vanilla_model.compile(
-    #     optimizer=optimizer, loss="mean_squared_error", metrics=[metrics.mse]
-    # )
     np.random.seed(42)
     # evaluate vanilla
     test_dl = linear_generator(batch_size, input_shape, kernel)
     loss2, mse2 = uft.run_test(model, test_dl, loss_fn, metrics, steps=10)
-    # loss2, mse2 = model.__getattribute__(EVALUATE)(
-    #     linear_generator(batch_size, input_shape, kernel),
-    #     steps=10,
-    #     verbose=0,
-    # )
     np.random.seed(42)
     # check if original has changed
     test_dl = linear_generator(batch_size, input_shape, kernel)
     vanilla_loss, vanilla_mse = uft.run_test(
         vanilla_model, test_dl, loss_fn, metrics, steps=10
     )
-    # vanilla_loss, vanilla_mse = vanilla_model.__getattribute__(EVALUATE)(
-    #     linear_generator(batch_size, input_shape, kernel),
-    #     steps=10,
-    #     verbose=0,
-    # )
     model.summary()
     vanilla_model.summary()
 
@@ -314,32 +289,15 @@ def test_model(layer_type, layer_params, k_coef_lip, input_shape):
         steps_per_epoch=steps_per_epoch,
         callbacks=callback_list,
     )
-    # model.__getattribute__(FIT)(
-    #     linear_generator(batch_size, input_shape, kernel),
-    #     steps_per_epoch=steps_per_epoch,
-    #     epochs=1,
-    #     verbose=0,
-    #     callbacks=callback_list,
-    # )
     np.random.seed(42)
     test_dl = linear_generator(batch_size, input_shape, kernel)
     loss3, mse3 = uft.run_test(model, test_dl, loss_fn, metrics, steps=10)
-    # loss3, mse3 = model.__getattribute__(EVALUATE)(
-    #     linear_generator(batch_size, input_shape, kernel),
-    #     steps=10,
-    #     verbose=0,
-    # )
     # check if vanilla has changed
     np.random.seed(42)
     test_dl = linear_generator(batch_size, input_shape, kernel)
     vanilla_loss2, vanilla_mse2 = uft.run_test(
         vanilla_model, test_dl, loss_fn, metrics, steps=10
     )
-    # vanilla_loss2, vanilla_mse2 = vanilla_model.__getattribute__(EVALUATE)(
-    #     linear_generator(batch_size, input_shape, kernel),
-    #     steps=10,
-    #     verbose=0,
-    # )
     np.testing.assert_equal(
         vanilla_mse,
         vanilla_mse2,