Merge pull request #249 from ranqiu92/mt_with_external_memory2

fix a bug of external_memory.

mt_with_external_memory/external_memory.py

@@ -35,6 +35,8 @@ class ExternalMemory(object):
                        sequence layer has sequence length indicating the number
                        of memory slots, and size as memory slot size.
     :type boot_layer: LayerOutput
+    :param initial_weight: Initializer for addressing weights.
+    :type initial_weight: LayerOutput
     :param readonly: If true, the memory is read-only, and write function cannot
                      be called. Default is false.
     :type readonly: bool
@@ -49,6 +51,7 @@ class ExternalMemory(object):
                  name,
                  mem_slot_size,
                  boot_layer,
+                 initial_weight,
                  readonly=False,
                  enable_interpolation=True):
         self.name = name
@@ -57,11 +60,7 @@ class ExternalMemory(object):
         self.enable_interpolation = enable_interpolation
         self.external_memory = paddle.layer.memory(
             name=self.name, size=self.mem_slot_size, boot_layer=boot_layer)
-        # prepare a constant (zero) intializer for addressing weights 
-        self.zero_addressing_init = paddle.layer.slope_intercept(
-            input=paddle.layer.fc(input=boot_layer, size=1),
-            slope=0.0,
-            intercept=0.0)
+        self.initial_weight = initial_weight
         # set memory to constant when readonly=True
         if self.readonly:
             self.updated_external_memory = paddle.layer.mixed(
@@ -111,7 +110,7 @@ class ExternalMemory(object):
         last_addressing_weight = paddle.layer.memory(
             name=self.name + "_addressing_weight_" + head_name,
             size=1,
-            boot_layer=self.zero_addressing_init)
+            boot_layer=self.initial_weight)
         interpolated_weight = paddle.layer.interpolation(
             name=self.name + "_addressing_weight_" + head_name,
             input=[addressing_weight, addressing_weight],

mt_with_external_memory/model.py

@@ -125,7 +125,15 @@ def memory_enhanced_decoder(input, target, initial_state, source_context, size,
             bounded_memory_perturbation
         ],
         act=paddle.activation.Linear())
+    bounded_memory_weight_init = paddle.layer.slope_intercept(
+        input=paddle.layer.fc(input=bounded_memory_init, size=1),
+        slope=0.0,
+        intercept=0.0)
     unbounded_memory_init = source_context
+    unbounded_memory_weight_init = paddle.layer.slope_intercept(
+        input=paddle.layer.fc(input=unbounded_memory_init, size=1),
+        slope=0.0,
+        intercept=0.0)
 
     # prepare step function for reccurent group
     def recurrent_decoder_step(cur_embedding):
@@ -136,12 +144,14 @@ def memory_enhanced_decoder(input, target, initial_state, source_context, size,
             name="bounded_memory",
             mem_slot_size=size,
             boot_layer=bounded_memory_init,
+            initial_weight=bounded_memory_weight_init,
             readonly=False,
             enable_interpolation=True)
         unbounded_memory = ExternalMemory(
             name="unbounded_memory",
             mem_slot_size=size * 2,
             boot_layer=unbounded_memory_init,
+            initial_weight=unbounded_memory_weight_init,
             readonly=True,
             enable_interpolation=False)
         # write bounded memory
@@ -154,7 +164,7 @@ def memory_enhanced_decoder(input, target, initial_state, source_context, size,
             size=size,
             act=paddle.activation.Tanh(),
             bias_attr=False)
-        # read unbounded memory (i.e. attention mechanism) 
+        # read unbounded memory (i.e. attention mechanism)
         context = unbounded_memory.read(key_for_unbounded_memory)
         # gated recurrent unit
         gru_inputs = paddle.layer.fc(