fixed an error in test; new way for regularization

keras-team · Jan 3, 2017 · e640e12 · e640e12
1 parent c6d0281
commit e640e12
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Showing 2 changed files with 24 additions and 23 deletions.
diff --git a/keras/layers/crf.py b/keras/layers/crf.py
@@ -119,9 +119,9 @@ def __init__(self, output_dim,
                  weights=None, input_dim=None, input_length=None, unroll=False, **kwargs):
         self.supports_masking = True
         self.output_dim = output_dim
-        self.learn_mode = learn_mode.lower()
-        self.test_mode = test_mode.lower()
+        self.learn_mode = learn_mode
         assert self.learn_mode in ['join', 'marginal']
+        self.test_mode = test_mode
         if self.test_mode is None:
             self.test_mode = 'viterbi' if self.learn_mode == 'join' else 'marginal'
         else:
@@ -150,25 +150,27 @@ def build(self, input_shape):
         if self.input_length is None:
             self.input_length = self.input_spec[0].shape[1]
         input_dim = input_shape[-1]
-        self.W = self.in_init((input_dim, self.output_dim), name='{}_W'.format(self.name))
-        self.U = self.chain_init((self.output_dim, self.output_dim), name='{}_U'.format(self.name))
-        self.b = K.zeros((self.output_dim,), name='{}_b'.format(self.name))
-        self.trainable_weights = [self.W, self.U, self.b]
+
+        self.W = self.add_weight((input_dim, self.output_dim),
+                                 initializer=self.in_init,
+                                 name='{}_W'.format(self.name),
+                                 regularizer=self.W_regularizer)
+        self.U = self.add_weight((self.output_dim, self.output_dim),
+                                 initializer=self.chain_init,
+                                 name='{}_U'.format(self.name),
+                                 regularizer=self.U_regularizer)
+        self.b = self.add_weight((self.output_dim,),
+                                 initializer='zero',
+                                 name='{}_b'.format(self.name),
+                                 regularizer=self.b_regularizer)
+
         if self.boundary_energy:
-            self.a1 = K.zeros((self.output_dim,), name='{}_a1'.format(self.name))
-            self.an = K.zeros((self.output_dim,), name='{}_an'.format(self.name))
-            self.trainable_weights += [self.a1, self.an]
-
-        self.regularizers = []
-        if self.W_regularizer:
-            self.W_regularizer.set_param(self.W)
-            self.regularizers.append(self.W_regularizer)
-        if self.U_regularizer:
-            self.U_regularizer.set_param(self.U)
-            self.regularizers.append(self.U_regularizer)
-        if self.b_regularizer:
-            self.b_regularizer.set_param(self.b)
-            self.regularizers.append(self.b_regularizer)
+            self.a1 = self.add_weight((self.output_dim,),
+                                      initializer='zero',
+                                      name='{}_a1'.format(self.name))
+            self.an = self.add_weight((self.output_dim,),
+                                      initializer='zero',
+                                      name='{}_an'.format(self.name))
 
         if self.initial_weights is not None:
             self.set_weights(self.initial_weights)

diff --git a/tests/keras/layers/test_crf.py b/tests/keras/layers/test_crf.py
@@ -10,7 +10,6 @@
 
 @keras_test
 def test_CRF():
-
     # data
     x = np.random.randint(1, embedding_num, nb_samples * timesteps).reshape((nb_samples, timesteps))
     x[0, -4:] = 0 # right padding
@@ -43,8 +42,8 @@ def test_CRF():
 
     # test `viterbi_acc
     _, v_acc, _ = model.evaluate(x, y)
-    np_acc = (y_pred[x > 0] == y[x > 0]).mean()
-    assert_allclose([v_acc], [np_acc], atol=1e-6)
+    np_acc = (y_pred[x > 0] == y[:, :, 0][x > 0]).astype('float32').mean()
+    assert np.abs(v_acc - np_acc) < 1e-4
 
     # test config
     model.get_config()