【PIR API adaptor No.132】 Migrate paddle.Tensor.paddle.Tensor.logcumsumexp (#58695)

Author: xiaoyewww

python/paddle/tensor/math.py

@@ -4203,7 +4203,7 @@ def logcumsumexp(x, axis=None, dtype=None, name=None):
     if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
         x = cast(x, dtype)
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         if axis is None:
             axis = -1
         return _C_ops.logcumsumexp(x, axis, flatten, False, False)

test/legacy_test/test_logcumsumexp_op.py

@@ -22,6 +22,7 @@
 import paddle
 from paddle import base
 from paddle.base import core
+from paddle.pir_utils import test_with_pir_api
 
 
 def np_naive_logcumsumexp(x: np.ndarray, axis: Optional[int] = None):
@@ -145,7 +146,9 @@ def run_imperative(self):
         np.testing.assert_allclose(z, y.numpy(), rtol=1e-05)
 
     def run_static(self, use_gpu=False):
-        with base.program_guard(base.Program()):
+        main = paddle.static.Program()
+        startup = paddle.static.Program()
+        with paddle.static.program_guard(main, startup):
             data_np = np.random.random((5, 4)).astype(np.float32)
             x = paddle.static.data('X', [5, 4])
             y = paddle.logcumsumexp(x)
@@ -156,15 +159,15 @@ def run_static(self, use_gpu=False):
 
             place = base.CUDAPlace(0) if use_gpu else base.CPUPlace()
             exe = base.Executor(place)
-            exe.run(base.default_startup_program())
             out = exe.run(
+                main,
                 feed={'X': data_np},
                 fetch_list=[
-                    y.name,
-                    y2.name,
-                    y3.name,
-                    y4.name,
-                    y5.name,
+                    y,
+                    y2,
+                    y3,
+                    y4,
+                    y5,
                 ],
             )
 
@@ -178,13 +181,15 @@ def run_static(self, use_gpu=False):
             z = np_logcumsumexp(data_np, axis=-2)
             np.testing.assert_allclose(z, out[4], rtol=1e-05)
 
+    @test_with_pir_api
     def test_cpu(self):
         paddle.disable_static(paddle.base.CPUPlace())
         self.run_imperative()
         paddle.enable_static()
 
         self.run_static()
 
+    @test_with_pir_api
     def test_gpu(self):
         if not base.core.is_compiled_with_cuda():
             return
@@ -194,23 +199,26 @@ def test_gpu(self):
 
         self.run_static(use_gpu=True)
 
+    # @test_with_pir_api
     def test_name(self):
         with base.program_guard(base.Program()):
             x = paddle.static.data('x', [3, 4])
             y = paddle.logcumsumexp(x, name='out')
             self.assertTrue('out' in y.name)
 
+    @test_with_pir_api
     def test_type_error(self):
-        with base.program_guard(base.Program()):
+        main = paddle.static.Program()
+        startup = paddle.static.Program()
+        with paddle.static.program_guard(main, startup):
             with self.assertRaises(TypeError):
                 data_np = np.random.random((100, 100), dtype=np.int32)
                 x = paddle.static.data('X', [100, 100], dtype='int32')
                 y = paddle.logcumsumexp(x)
 
                 place = base.CUDAPlace(0)
                 exe = base.Executor(place)
-                exe.run(base.default_startup_program())
-                out = exe.run(feed={'X': data_np}, fetch_list=[y.name])
+                out = exe.run(main, feed={'X': data_np}, fetch_list=[y])
 
 
 def logcumsumexp_wrapper(
@@ -296,6 +304,7 @@ def check_main(self, x_np, dtype, axis=None):
         paddle.enable_static()
         return y_np, x_g_np
 
+    @test_with_pir_api
     def test_main(self):
         if not paddle.is_compiled_with_cuda():
             return