fix auto backward bug

python/paddle/autograd/backward_utils.py

@@ -444,6 +444,14 @@ def all_stop_gradient_true(block):
     return True
 
 
+def all_input_stop_gradient_true(list_of_list):
+    for list_ in list_of_list:
+        for stop_gradient in list_:
+            if stop_gradient is False:
+                return False
+    return True
+
+
 def all_output_grad_none(list_of_list):
     for list_ in list_of_list:
         for value in list_:

python/paddle/autograd/ir_backward.py

@@ -22,6 +22,7 @@
     ValueDict,
     ValueSet,
     _as_list,
+    all_input_stop_gradient_true,
     all_output_grad_none,
     all_stop_gradient_true,
     argument_to_value,
@@ -649,6 +650,14 @@ def append_yield(
                     ]:
                         continue
 
+                    if all_input_stop_gradient_true(
+                        input_grad_stopgradients
+                    ) and op.name() not in [
+                        "pd_op.array_read",
+                        "pd_op.array_write_",
+                        "pd_op.increment_",
+                    ]:
+                        continue
                     if op.name() == "pd_op.if":
                         origin_inputs = get_real_op_inputs(op)
                         for sub_block in op.blocks():

test/auto_parallel/pir/test_to_static_pir_program.py

@@ -139,8 +139,6 @@ def test_to_static_program(self):
         backward_op_list = [
             "pd_op.sgd_",
             "pd_op.sgd_",
-            "pd_op.relu_grad",
-            "pd_op.c_allreduce_sum_",
             "pd_op.matmul_grad",
             "pd_op.relu_grad",
             "pd_op.matmul_grad",

test/ir/pir/test_ir_backward.py

@@ -292,6 +292,31 @@ def false_func():
             self.assertEqual((grad_x == res).all(), True)
 
 
+class TestBackward_5(unittest.TestCase):
+    def tearDown(self) -> None:
+        paddle.framework.set_flags({"FLAGS_enable_pir_api": False})
+
+    def test_skip_vjp(self):
+        if not paddle.framework.in_pir_mode():
+            return
+        program = paddle.static.Program()
+        with paddle.static.program_guard(program):
+            x = paddle.static.data('x', [4, 4], 'float32')
+            x.stop_gradient = True
+            y = paddle.nn.functional.relu(x)
+            y.stop_gradient = False
+            z = paddle.nn.functional.relu(y)
+            loss = paddle.mean(z)
+
+        paddle.autograd.ir_backward.append_backward(loss)
+        relu_grad_number = 0
+        for op in program.global_block().ops:
+            if op.name() == "pd_op.relu_grad":
+                relu_grad_number += 1
+
+        self.assertEqual(relu_grad_number, 1)
+
+
 class TestValueSet(unittest.TestCase):
     def setUp(self) -> None:
         with paddle.pir_utils.IrGuard():