[NewIR] No.49 Migrate paddle.tril into pir (PaddlePaddle#57393)

danleifeng · Sep 22, 2023 · a2bc204 · a2bc204
1 parent 0717491
commit a2bc204
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Showing 4 changed files with 18 additions and 6 deletions.
diff --git a/paddle/fluid/pir/dialect/op_generator/vjp_interface_gen_op_list.py b/paddle/fluid/pir/dialect/op_generator/vjp_interface_gen_op_list.py
@@ -58,6 +58,8 @@
     'slice_double',
     'poisson',
     'gumbel_softmax',
+    'tril',
+    'triu',
 ]
 vjp_interface_implementation_gen_op_list = [
     "tanh",
@@ -94,4 +96,6 @@
     'slice_double',
     'poisson',
     'gumbel_softmax',
+    'tril',
+    'triu',
 ]
diff --git a/paddle/fluid/primitive/codegen/gen.py b/paddle/fluid/primitive/codegen/gen.py
@@ -38,6 +38,8 @@
 
 
 VJPS = [
+    'tril_grad',
+    'triu_grad',
     'tanh_grad',
     'mean_grad',
     'add_grad',
@@ -92,6 +94,8 @@
 VJP_COMPS = PRIM_VJP + CUSTOM_VJP
 
 BACKENDS = [
+    'tril_grad',
+    'triu_grad',
     'add_n',
     'mean',
     'sum',

diff --git a/python/paddle/tensor/creation.py b/python/paddle/tensor/creation.py
@@ -1504,7 +1504,7 @@ def tril(x, diagonal=0, name=None):
              [5 , 0 , 0 , 0 ],
              [9 , 10, 0 , 0 ]])
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.tril(x, diagonal)
     else:
         return _tril_triu_op(LayerHelper('tril', **locals()))
@@ -1581,7 +1581,7 @@ def triu(x, diagonal=0, name=None):
              [0 , 10, 11, 12]])
 
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.triu(x, diagonal)
     else:
         return _tril_triu_op(LayerHelper('triu', **locals()))

diff --git a/test/legacy_test/test_tril_triu_op.py b/test/legacy_test/test_tril_triu_op.py
@@ -45,10 +45,10 @@ def setUp(self):
         }
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_new_ir=True)
 
     def test_check_grad_normal(self):
-        self.check_grad(['X'], 'Out')
+        self.check_grad(['X'], 'Out', check_new_ir=True)
 
     def init_dtype(self):
         self.dtype = np.float64
@@ -86,11 +86,15 @@ def initTestCase(self):
         self.X = np.arange(1, 101, dtype="float32").reshape([10, -1])
 
     def test_check_output(self):
-        self.check_output_with_place(core.CUDAPlace(0))
+        self.check_output_with_place(core.CUDAPlace(0), check_new_ir=True)
 
     def test_check_grad_normal(self):
         self.check_grad_with_place(
-            core.CUDAPlace(0), ['X'], 'Out', numeric_grad_delta=0.05
+            core.CUDAPlace(0),
+            ['X'],
+            'Out',
+            numeric_grad_delta=0.05,
+            check_new_ir=True,
         )