Keras: Simplify recurrent state updates

tensorflow/python/keras/layers/convolutional_recurrent.py

@@ -392,9 +392,9 @@ def step(inputs, states):
                                          mask=mask,
                                          input_length=timesteps)
     if self.stateful:
-      updates = []
-      for i in range(len(states)):
-        updates.append(K.update(self.states[i], states[i]))
+      updates = [
+          K.update(self_state, state)
+          for self_state, state in zip(self.states, states)]
       self.add_update(updates)
 
     if self.return_sequences:

tensorflow/python/keras/layers/cudnn_recurrent.py

@@ -110,9 +110,9 @@ def call(self, inputs, mask=None, training=None, initial_state=None):
     output, states = self._process_batch(inputs, initial_state)
 
     if self.stateful:
-      updates = []
-      for i in range(len(states)):
-        updates.append(state_ops.assign(self.states[i], states[i]))
+      updates = [
+          state_ops.assign(self_state, state)
+          for self_state, state in zip(self.states, states)]
       self.add_update(updates)
 
     if self.return_state:

tensorflow/python/keras/layers/recurrent.py

@@ -601,16 +601,17 @@ def _validate_state_spec(cell_state_sizes, init_state_specs):
         '`cell.state_size`. Received `state_spec`={}; '
         'however `cell.state_size` is '
         '{}'.format(init_state_specs, cell_state_sizes))
-    flat_cell_state_size = nest.flatten(cell_state_sizes)
-    flat_state_spec = nest.flatten(init_state_specs)
+    flat_cell_state_sizes = nest.flatten(cell_state_sizes)
+    flat_state_specs = nest.flatten(init_state_specs)
 
-    if len(flat_cell_state_size) != len(flat_state_spec):
+    if len(flat_cell_state_sizes) != len(flat_state_specs):
       raise validation_error
-    for i in range(len(flat_cell_state_size)):
+    for cell_state_spec, cell_state_size in zip(
+        flat_state_specs, flat_cell_state_sizes):
       if not tensor_shape.TensorShape(
           # Ignore the first axis for init_state which is for batch
-          flat_state_spec[i].shape[1:]).is_compatible_with(
-              tensor_shape.TensorShape(flat_cell_state_size[i])):
+          cell_state_spec.shape[1:]).is_compatible_with(
+              tensor_shape.TensorShape(cell_state_size)):
         raise validation_error
 
   @doc_controls.do_not_doc_inheritable
@@ -785,9 +786,10 @@ def step(inputs, states):
         zero_output_for_mask=self.zero_output_for_mask)
 
     if self.stateful:
-      updates = []
-      for state_, state in zip(nest.flatten(self.states), nest.flatten(states)):
-        updates.append(state_ops.assign(state_, state))
+      updates = [
+          state_ops.assign(self_state, state)
+          for self_state, state in zip(
+              nest.flatten(self.states), nest.flatten(states))]
       self.add_update(updates)
 
     if self.return_sequences:

tensorflow/python/keras/layers/recurrent_v2.py

@@ -1152,9 +1152,9 @@ def step(inputs, states):
       states = [new_h, new_c]
 
     if self.stateful:
-      updates = []
-      for i in range(len(states)):
-        updates.append(state_ops.assign(self.states[i], states[i]))
+      updates = [
+          state_ops.assign(self_state, state)
+          for self_state, state in zip(self.states, states)]
       self.add_update(updates)
 
     if self.return_sequences: