TFA deprecated

philipperemy · Aug 13, 2024 · f8f5750 · f8f5750
1 parent f4409bd
commit f8f5750
Showing 1 changed file with 0 additions and 22 deletions.
diff --git a/tasks/tcn_call_test.py b/tasks/tcn_call_test.py
@@ -3,7 +3,6 @@
 import numpy as np
 from tensorflow.keras import Input
 from tensorflow.keras import Model
-from tensorflow.keras.models import Sequential
 
 from tcn import TCN
 
@@ -100,27 +99,6 @@ def test_non_causal_time_dim_unknown_return_no_sequences(self):
         r = predict_with_tcn(time_steps=None, padding='same', return_sequences=False)
         self.assertListEqual([list(b.shape) for b in r], [[1, NB_FILTERS], [1, NB_FILTERS], [1, NB_FILTERS]])
 
-    def test_norms(self):
-        Sequential(layers=[TCN(input_shape=(20, 2), use_weight_norm=True)]).compile(optimizer='adam', loss='mse')
-        Sequential(layers=[TCN(input_shape=(20, 2), use_weight_norm=False)]).compile(optimizer='adam', loss='mse')
-        Sequential(layers=[TCN(input_shape=(20, 2), use_layer_norm=True)]).compile(optimizer='adam', loss='mse')
-        Sequential(layers=[TCN(input_shape=(20, 2), use_layer_norm=False)]).compile(optimizer='adam', loss='mse')
-        Sequential(layers=[TCN(input_shape=(20, 2), use_batch_norm=True)]).compile(optimizer='adam', loss='mse')
-        Sequential(layers=[TCN(input_shape=(20, 2), use_batch_norm=False)]).compile(optimizer='adam', loss='mse')
-        try:
-            Sequential(layers=[TCN(input_shape=(20, 2), use_batch_norm=True, use_weight_norm=True)]).compile(
-                optimizer='adam', loss='mse')
-            raise AssertionError('test failed.')
-        except ValueError:
-            pass
-        try:
-            Sequential(layers=[TCN(input_shape=(20, 2), use_batch_norm=True,
-                                   use_weight_norm=True, use_layer_norm=True)]).compile(
-                optimizer='adam', loss='mse')
-            raise AssertionError('test failed.')
-        except ValueError:
-            pass
-
     def test_receptive_field(self):
         self.assertEqual(37, TCN(kernel_size=3, dilations=(1, 3, 5), nb_stacks=1).receptive_field)
         self.assertEqual(379, TCN(kernel_size=4, dilations=(1, 2, 4, 8, 16, 32), nb_stacks=1).receptive_field)