add index_select(5/5) and index_sample(5/5) (#59040)

python/paddle/tensor/search.py

@@ -358,7 +358,7 @@ def index_select(x, index, axis=0, name=None):
              [ 9. 10. 10.]]
     """
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.index_select(x, index, axis)
     else:
         helper = LayerHelper("index_select", **locals())
@@ -849,7 +849,7 @@ def index_sample(x, index):
              [1200 1100]]
 
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.index_sample(x, index)
     else:
         helper = LayerHelper("index_sample", **locals())

test/legacy_test/test_index_sample_op.py

@@ -20,6 +20,7 @@
 import paddle
 from paddle import base
 from paddle.base import core
+from paddle.pir_utils import test_with_pir_api
 
 
 class TestIndexSampleOp(OpTest):
@@ -46,10 +47,10 @@ def setUp(self):
         self.outputs = {'Out': out}
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_pir=True)
 
     def test_check_grad(self):
-        self.check_grad(['X'], 'Out')
+        self.check_grad(['X'], 'Out', check_pir=True)
 
     def config(self):
         """
@@ -176,10 +177,10 @@ def setUp(self):
         self.place = core.CUDAPlace(0)
 
     def test_check_output(self):
-        self.check_output_with_place(self.place)
+        self.check_output_with_place(self.place, check_pir=True)
 
     def test_check_grad(self):
-        self.check_grad_with_place(self.place, ['X'], 'Out')
+        self.check_grad_with_place(self.place, ['X'], 'Out', check_pir=True)
 
     def config(self):
         """
@@ -193,30 +194,33 @@ def config(self):
 
 
 class TestIndexSampleShape(unittest.TestCase):
+    @test_with_pir_api
     def test_shape(self):
         paddle.enable_static()
-        # create x value
-        x_shape = (2, 5)
-        x_type = "float64"
-        x_np = np.random.random(x_shape).astype(x_type)
-
-        # create index value
-        index_shape = (2, 3)
-        index_type = "int32"
-        index_np = np.random.randint(
-            low=0, high=x_shape[1], size=index_shape
-        ).astype(index_type)
-
-        x = paddle.static.data(name='x', shape=[-1, 5], dtype='float64')
-        index = paddle.static.data(name='index', shape=[-1, 3], dtype='int32')
-        output = paddle.index_sample(x=x, index=index)
-
-        place = base.CPUPlace()
-        exe = base.Executor(place=place)
-        exe.run(base.default_startup_program())
-
-        feed = {'x': x_np, 'index': index_np}
-        res = exe.run(feed=feed, fetch_list=[output])
+        with paddle.static.program_guard(paddle.static.Program()):
+            # create x value
+            x_shape = (2, 5)
+            x_type = "float64"
+            x_np = np.random.random(x_shape).astype(x_type)
+
+            # create index value
+            index_shape = (2, 3)
+            index_type = "int32"
+            index_np = np.random.randint(
+                low=0, high=x_shape[1], size=index_shape
+            ).astype(index_type)
+
+            x = paddle.static.data(name='x', shape=[-1, 5], dtype='float64')
+            index = paddle.static.data(
+                name='index', shape=[-1, 3], dtype='int32'
+            )
+            output = paddle.index_sample(x=x, index=index)
+
+            place = base.CPUPlace()
+            exe = base.Executor(place=place)
+
+            feed = {'x': x_np, 'index': index_np}
+            res = exe.run(feed=feed, fetch_list=[output])
 
 
 class TestIndexSampleDynamic(unittest.TestCase):

test/legacy_test/test_index_select_op.py

@@ -20,6 +20,7 @@
 import paddle
 from paddle import base
 from paddle.base import Program, core, program_guard
+from paddle.pir_utils import test_with_pir_api
 
 np.random.seed(1024)
 
@@ -66,15 +67,15 @@ def init_dtype_type(self):
 
     def test_check_output(self):
         if self.x_type == np.complex64 or self.x_type == np.complex128:
-            self.check_output(check_prim=False)
+            self.check_output(check_prim=False, check_pir=True)
         else:
-            self.check_output(check_prim=True)
+            self.check_output(check_prim=True, check_pir=True)
 
     def test_check_grad_normal(self):
         if self.x_type == np.complex64 or self.x_type == np.complex128:
-            self.check_grad(['X'], 'Out', check_prim=False)
+            self.check_grad(['X'], 'Out', check_prim=False, check_pir=True)
         else:
-            self.check_grad(['X'], 'Out', check_prim=True)
+            self.check_grad(['X'], 'Out', check_prim=True, check_pir=True)
 
 
 class TestIndexSelectOpCase2(TestIndexSelectOp):
@@ -150,11 +151,13 @@ def init_dtype_type(self):
 
     def test_check_output(self):
         place = core.CUDAPlace(0)
-        self.check_output_with_place(place)
+        self.check_output_with_place(place, check_pir=True)
 
     def test_check_grad_normal(self):
         place = core.CUDAPlace(0)
-        self.check_grad_with_place(place, ['X'], 'Out', check_prim=True)
+        self.check_grad_with_place(
+            place, ['X'], 'Out', check_prim=True, check_pir=True
+        )
 
 
 class TestIndexSelectComplex64(TestIndexSelectOp):
@@ -186,6 +189,7 @@ def input_data(self):
         ).astype("float32")
         self.data_index = np.array([0, 1, 1]).astype('int32')
 
+    @test_with_pir_api
     def test_index_select_api(self):
         paddle.enable_static()
         self.input_data()
@@ -198,7 +202,7 @@ def test_index_select_api(self):
             exe = base.Executor(base.CPUPlace())
             (res,) = exe.run(
                 feed={'x': self.data_x, 'index': self.data_index},
-                fetch_list=[z.name],
+                fetch_list=[z],
                 return_numpy=False,
             )
         expect_out = np.array(
@@ -207,14 +211,16 @@ def test_index_select_api(self):
         np.testing.assert_allclose(expect_out, np.array(res), rtol=1e-05)
 
         # case 2:
-        with program_guard(Program(), Program()):
+        with paddle.static.program_guard(
+            paddle.static.Program(), paddle.static.Program()
+        ):
             x = paddle.static.data(name='x', shape=[-1, 4])
             index = paddle.static.data(name='index', shape=[3], dtype='int32')
             z = paddle.index_select(x, index)
             exe = base.Executor(base.CPUPlace())
             (res,) = exe.run(
                 feed={'x': self.data_x, 'index': self.data_index},
-                fetch_list=[z.name],
+                fetch_list=[z],
                 return_numpy=False,
             )
         expect_out = np.array(