【pir】 modify test_Gradname_parse and warprnnt optest bug (PaddlePaddl…

…e#59215) * tmp * modify ci bug * [PIR]Migrate maximum into pir * Polish code * add ir_grad of static_gradient * add test * modify backward * modify * modify segment * modify warprnnt * fix pir error 34 * modofy test_gradname_parse --------- Co-authored-by: 0x45f <wangzhen45@baidu.com> Co-authored-by: xiongkun <xiongkun03@baidu.com>
SecretXV · Nov 28, 2023 · b01910f · b01910f
1 parent f2baea5
commit b01910f
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Showing 5 changed files with 40 additions and 28 deletions.
diff --git a/paddle/fluid/pybind/pir.cc b/paddle/fluid/pybind/pir.cc
@@ -986,7 +986,7 @@ pir::OpResult FakeOpResult() {
 
 bool IsFakeOpResult(const pir::OpResult &result) {
   // create a fake opresults to simplify `ForwardBackwardSplit`.
-  return result.Value::impl() == nullptr;
+  return result.Value::impl() == nullptr || !result.Value::type();
 }
 
 static auto GetNoNeedBufferValue(const ::pir::Block *whole_block,

diff --git a/python/paddle/autograd/ir_backward.py b/python/paddle/autograd/ir_backward.py
@@ -135,25 +135,30 @@ def prepare_grad_outputs(grad_outputs, outputs, state):
                 visited_output.add(opresult)
                 continue
             else:
-                grad_value = paddle.full_like(
-                    opresult,
-                    0.0,
-                    opresult.dtype,
-                )
-                full_likeop = grad_value.get_defining_op()
-                fullop = full_likeop.operand_source(1).get_defining_op()
+                if paddle.pir.is_fake_op_result(opresult):
+                    state.value_to_valuegrad[opresult] = [
+                        [paddle.pir.fake_op_result()]
+                    ]
+                else:
+                    grad_value = paddle.full_like(
+                        opresult,
+                        0.0,
+                        opresult.dtype,
+                    )
+                    full_likeop = grad_value.get_defining_op()
+                    fullop = full_likeop.operand_source(1).get_defining_op()
 
-                update_bwdop_structure(
-                    backward_ops,
-                    state.op_to_opgrad[opresult.get_defining_op()],
-                    [full_likeop, fullop],
-                )
-                state.value_to_valuegrad[opresult] = [[grad_value]]
+                    update_bwdop_structure(
+                        backward_ops,
+                        state.op_to_opgrad[opresult.get_defining_op()],
+                        [full_likeop, fullop],
+                    )
+                    state.value_to_valuegrad[opresult] = [[grad_value]]
 
-                visited_output.add(opresult)
+                    visited_output.add(opresult)
 
-                complete_outputs.append(opresult)
-                complete_gradoutputs.append(grad_value)
+                    complete_outputs.append(opresult)
+                    complete_gradoutputs.append(grad_value)
 
     return complete_outputs, complete_gradoutputs, backward_ops
 

diff --git a/test/dygraph_to_static/test_gradname_parse.py b/test/dygraph_to_static/test_gradname_parse.py
@@ -16,7 +16,11 @@
 import unittest
 
 import numpy as np
-from dygraph_to_static_utils_new import Dy2StTestBase
+from dygraph_to_static_utils_new import (
+    Dy2StTestBase,
+    test_ast_only,
+    test_pir_api_only,
+)
 
 import paddle
 from paddle.nn import BatchNorm, Linear
@@ -82,18 +86,23 @@ def setUp(self):
         self.dy2st_input = (x2,)
         self.dy2st_grad_input = (x2,)
 
+    @test_ast_only
+    @test_pir_api_only
     def test_run(self):
         try:
             dy_out = self.func(*self.dy_input)
-            dy_grad = paddle.grad(dy_out, self.dy_grad_input)
+            dy_grad = paddle.grad(dy_out, self.dy_grad_input, allow_unused=True)
         except:
             dy_grad = [None for i in self.dy_grad_input]
         dy_grad = [
             t.numpy() if isinstance(t, paddle.Tensor) else t for t in dy_grad
         ]
 
-        dy2st_out = paddle.jit.to_static(self.func)(*self.dy2st_input)
-        dy2st_grad = paddle.grad(dy2st_out, self.dy2st_grad_input)
+        tmp_func = paddle.jit.to_static(self.func, full_graph=True)
+        dy2st_out = tmp_func(*self.dy2st_input)
+        dy2st_grad = paddle.grad(
+            dy2st_out, self.dy2st_grad_input, allow_unused=True
+        )
         dy2st_grad = [
             t.numpy() if isinstance(t, paddle.Tensor) else t for t in dy_grad
         ]
@@ -112,8 +121,8 @@ def test_run(self):
 
 def matmul_high_order_grad(x, y):
     z = paddle.matmul(x, y)
-    g = paddle.grad(z, [x, y], create_graph=True)
-    return g[0]
+    g = paddle.grad(z, [x], create_graph=True, allow_unused=True)
+    return g
 
 
 class TestMatMulHighOrderGrad1(TestTanhHighOrderGrad):

diff --git a/test/legacy_test/op_test.py b/test/legacy_test/op_test.py
@@ -3676,7 +3676,7 @@ def construct_output_dict_by_kernel_sig(ret_tuple, output_sig):
                     )
                 fetch_list = list(grad_inputs)
                 # executor run
-                executor = paddle.static.Executor()
+                executor = paddle.static.Executor(place)
                 outs = executor.run(
                     ir_program,
                     feed=feed,

diff --git a/test/legacy_test/test_warprnnt_op.py b/test/legacy_test/test_warprnnt_op.py
@@ -227,7 +227,7 @@ def setUp(self):
         }
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_pir=True)
 
     def test_check_grad(self):
         self.outputs["warprnntgrad"] = self.gradient
@@ -239,9 +239,7 @@ def test_check_grad(self):
             )
         else:
             self.check_grad(
-                ["input"],
-                "loss",
-                numeric_grad_delta=0.009,
+                ["input"], "loss", numeric_grad_delta=0.009, check_pir=True
             )