warning when user save a inference model which contains auc op test=develop (#19838)

python/paddle/fluid/io.py

@@ -1031,6 +1031,15 @@ def save_inference_model(dirname,
 
     main_program = _get_valid_program(main_program)
 
+    # remind user to set auc_states to zeros if the program contains auc op 
+    all_ops = main_program.global_block().ops
+    for op in all_ops:
+        if op.type == 'auc':
+            warnings.warn(
+                "please ensure that you have set the auc states to zeros before saving inference model"
+            )
+            break
+
     # fix the bug that the activation op's output as target will be pruned.
     # will affect the inference performance.
     # TODO(Superjomn) add an IR pass to remove 1-scale op.

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

@@ -19,6 +19,8 @@ import unittest
 import six
 import numpy as np
 import paddle.fluid.core as core
+import paddle.fluid as fluid
+import warnings
 
 import paddle.fluid.executor as executor
 import paddle.fluid.layers as layers
@@ -111,6 +113,33 @@ class TestSaveInferenceModel(unittest.TestCase):
 
         save_inference_model(MODEL_DIR, ["x", "y"], [avg_cost], exe, program)
 
+    def test_save_inference_model_with_auc(self):
+        MODEL_DIR = "./tmp/inference_model4"
+        init_program = Program()
+        program = Program()
+
+        # fake program without feed/fetch
+        with program_guard(program, init_program):
+            x = layers.data(name='x', shape=[2], dtype='float32')
+            y = layers.data(name='y', shape=[1], dtype='float32')
+            predict = fluid.layers.fc(input=x, size=2, act='softmax')
+            acc = fluid.layers.accuracy(input=predict, label=y)
+            auc_var, batch_auc_var, auc_states = fluid.layers.auc(input=predict,
+                                                                  label=y)
+            cost = fluid.layers.cross_entropy(input=predict, label=y)
+            avg_cost = fluid.layers.mean(x=cost)
+
+        place = core.CPUPlace()
+        exe = executor.Executor(place)
+        exe.run(init_program, feed={}, fetch_list=[])
+        with warnings.catch_warnings(record=True) as w:
+            warnings.simplefilter("always")
+            save_inference_model(MODEL_DIR, ["x", "y"], [avg_cost], exe,
+                                 program)
+            expected_warn = "please ensure that you have set the auc states to zeros before saving inference model"
+            self.assertTrue(len(w) > 0)
+            self.assertTrue(expected_warn == str(w[0].message))
+
 
 class TestInstance(unittest.TestCase):
     def test_save_inference_model(self):