add get_loss_scaling to fleet

python/paddle/distributed/fleet/base/fleet_base.py

@@ -1041,6 +1041,26 @@ def forward(self, x):
         # imitate target optimizer retrieval
         return self.user_defined_optimizer.clear_grad()
 
+    def _get_amp_optimizer(self):
+        # imitate target optimizer retrieval
+        amp_optimizer = None
+        for optimizer in self.strategy_compiler._get_applied_meta_optimizer():
+            if hasattr(optimizer, 'amp_init'):
+                amp_optimizer = optimizer
+                break
+
+        if amp_optimizer is None:
+            if hasattr(self.user_defined_optimizer, 'amp_init'):
+                amp_optimizer = self.user_defined_optimizer
+
+        assert amp_optimizer is not None, \
+            "amp_init can only be used when the amp(auto mixed precision) strategy is turned on."
+        return amp_optimizer
+
+    def get_loss_scaling(self):
+        amp_optimizer = self._get_amp_optimizer()
+        return amp_optimizer.get_loss_scaling()
+
     def amp_init(self,
                  place,
                  scope=None,
@@ -1101,21 +1121,7 @@ def run_example_code():
                 if paddle.is_compiled_with_cuda() and len(paddle.static.cuda_places()) > 0:
                     run_example_code()       
         """
-
-        # imitate target optimizer retrieval
-        amp_optimizer = None
-        for optimizer in self.strategy_compiler._get_applied_meta_optimizer():
-            if hasattr(optimizer, 'amp_init'):
-                amp_optimizer = optimizer
-                break
-
-        if amp_optimizer is None:
-            if hasattr(self.user_defined_optimizer, 'amp_init'):
-                amp_optimizer = self.user_defined_optimizer
-
-        assert amp_optimizer is not None, \
-            "amp_init can only be used when the amp(auto mixed precision) strategy is turned on."
-
+        amp_optimizer = self._get_amp_optimizer()
         return amp_optimizer.amp_init(place, scope, test_program, use_fp16_test)
 
     def _final_strategy(self):

python/paddle/fluid/contrib/mixed_precision/decorator.py

@@ -98,6 +98,7 @@ def _set_distributed(self, flag):
     def get_loss_scaling(self):
         """Return the real-time loss scaling factor.
         """
+        assert self._loss_scaling is not None, 'Call minimize() before calling get_loss_scaling()'
         return self._loss_scaling
 
     def get_scaled_loss(self):

python/paddle/fluid/tests/unittests/test_fleet_amp_init.py

@@ -70,6 +70,8 @@ def test_fleet_amp_init(self):
             optimizer = fleet.distributed_optimizer(optimizer)
             optimizer.minimize(cost)
 
+        loss_scale = optimizer.get_loss_scaling()
+
         place = paddle.CUDAPlace(0)
 
         exe = paddle.static.Executor(place)