[AutoParallel] fix amp o1 (#46391) (#46481)

python/paddle/distributed/passes/auto_parallel_amp.py

@@ -38,14 +38,18 @@ class AMPState(object):
         self._op_fp16_dict = {
         }  # op_id --> True/False. 'True' means that the current op is in fp16 mode.
         self._var_name_dict = {}  # fwd_op_id --> {old_name: cast_name}
+        self.is_train = False
 
     def _is_fp16_op(self, op_id):
         return self._op_fp16_dict.get(op_id, None)
 
-    def _build_stats(self, amp_lists, dist_context):
+    def _build_state(self, amp_lists, dist_context):
         ops = self._block.ops
         dist_op_context = dist_context.dist_op_context
         for op in ops:
+            if int(op.attr('op_role')) == 257:
+                self.is_train = True
+
             if int(op.attr('op_role')) == int(OpRole.Forward):
                 self._mark_black_white_ops(amp_lists)
             elif int(op.attr('op_role')) == int(OpRole.Backward):
@@ -59,6 +63,8 @@ class AMPState(object):
             elif int(op.attr('op_role')) == int(OpRole.Optimize):
                 break
 
+        return self.is_train
+
     def _mark_black_white_ops(self, amp_lists):
         """
         this function is modified from paddle.fluid.contrib.mixed_precision
@@ -546,13 +552,15 @@ class AMPPass(PassBase):
             set(self.get_attr("custom_black_list")),
             set(self.get_attr("custom_black_varnames")))
 
+        with paddle.static.program_guard(main_program, startup_program):
             amp_state = AMPState(main_program.global_block())
-        amp_state._build_stats(amp_lists, self.dist_context)
+            is_train = amp_state._build_state(amp_lists, self.dist_context)
 
-        with paddle.static.program_guard(main_program, startup_program):
             amp_state.cast_forward_program(self.dist_context)
+
+        if is_train:
+            with paddle.static.program_guard(main_program, startup_program):
                 amp_state.cast_backward_program(params_grads, self.dist_context)
-            # TODO (JZ-LIANG)support cast forward program only when inference
                 self._init_amp_var()
                 self._scale_loss()
 

python/paddle/fluid/tests/unittests/auto_parallel/amp_pass_unittest.py

@@ -97,6 +97,7 @@ class TestAMPPass(unittest.TestCase):
                                           3,
                                           batch_size=self.batch_size)
         amp_o1_losses = np.array(amp_o1_losses["loss"])
+        amp_o1_engine.evaluate(self.dataset, 3, batch_size=self.batch_size)
         # self.check_results(mp_losses, amp_o1_losses)
 
         # mp2 amp-o2 training
@@ -105,6 +106,7 @@ class TestAMPPass(unittest.TestCase):
                                           3,
                                           batch_size=self.batch_size)
         amp_o2_losses = np.array(amp_o2_losses["loss"])
+        amp_o2_engine.evaluate(self.dataset, 3, batch_size=self.batch_size)
         # self.check_results(mp_losses, amp_o2_losses)
 
         # mp2 amp-o3 training
@@ -113,6 +115,7 @@ class TestAMPPass(unittest.TestCase):
                                           3,
                                           batch_size=self.batch_size)
         amp_o3_losses = np.array(amp_o3_losses["loss"])
+        amp_o3_engine.evaluate(self.dataset, 3, batch_size=self.batch_size)
         # self.check_results(mp_losses, amp_o3_losses)