【PIR API adaptor No.66、68、110、136】Migrate some ops into pir

python/paddle/nn/initializer/constant.py

@@ -72,10 +72,9 @@ def forward(self, var, block=None):
             if self._force_cpu:
                 place = core.CPUPlace()
             if in_dygraph_mode():
-                _C_ops.full_(
+                return _C_ops.full_(
                     var, var.shape, float(self._value), var.dtype, place
                 )
-                return None
             else:
                 return _C_ops.full(
                     var.shape, float(self._value), var.dtype, place

python/paddle/tensor/attribute.py

@@ -20,11 +20,7 @@
 from paddle import _C_ops
 
 from ..base.data_feeder import check_type, check_variable_and_dtype
-from ..base.framework import (
-    in_dygraph_mode,
-    in_dynamic_or_pir_mode,
-    in_pir_mode,
-)
+from ..base.framework import in_dynamic_or_pir_mode, in_pir_mode
 from ..common_ops_import import Variable
 from ..framework import LayerHelper, core
 from .creation import _complex_to_real_dtype, assign
@@ -300,7 +296,7 @@ def real(x, name=None):
             [[1., 2., 3.],
              [4., 5., 6.]])
     """
-    if in_dygraph_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.real(x)
     else:
         check_variable_and_dtype(x, 'x', ['complex64', 'complex128'], 'real')
@@ -348,7 +344,7 @@ def imag(x, name=None):
             [[6., 5., 4.],
              [3., 2., 1.]])
     """
-    if in_dygraph_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.imag(x)
     else:
         check_variable_and_dtype(x, 'x', ['complex64', 'complex128'], 'imag')

python/paddle/tensor/logic.py

@@ -139,7 +139,7 @@ def logical_and(x, y, out=None, name=None):
             [True , False, True , False])
 
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.logical_and(x, y)
 
     return _logical_op(
@@ -413,7 +413,7 @@ def equal_all(x, y, name=None):
             Tensor(shape=[], dtype=bool, place=Place(cpu), stop_gradient=True,
             False)
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.equal_all(x, y)
     else:
         helper = LayerHelper("equal_all", **locals())

python/paddle/tensor/manipulation.py

@@ -1413,7 +1413,7 @@ def flip(x, axis, name=None):
     if isinstance(axis, int):
         axis = [axis]
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.flip(x, axis)
     else:
         helper = LayerHelper("flip", **locals())
@@ -3430,7 +3430,7 @@ def expand_as(x, y, name=None):
             [[1, 2, 3],
              [1, 2, 3]])
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.expand_as(x, None, y.shape)
     else:
         check_variable_and_dtype(

python/paddle/tensor/math.py

@@ -4437,7 +4437,7 @@ def isnan(x, name=None):
             Tensor(shape=[7], dtype=bool, place=Place(cpu), stop_gradient=True,
             [False, False, False, False, False, True , True ])
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.isnan(x)
     else:
         helper = LayerHelper("isnan_v2", **locals())
@@ -5209,7 +5209,7 @@ def logit(x, eps=None, name=None):
     """
     if eps is None:
         eps = 0.0
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.logit(x, eps)
     else:
         check_variable_and_dtype(

python/paddle/tensor/search.py

@@ -459,7 +459,7 @@ def nonzero(x, as_tuple=False):
     shape = x.shape
     rank = len(shape)
 
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         outs = _C_ops.nonzero(x)
     else:
         check_variable_and_dtype(

test/legacy_test/test_compare_reduce_op.py

@@ -32,7 +32,7 @@ def setUp(self):
             self.op_type = op_type
 
         def test_output(self):
-            self.check_output()
+            self.check_output(check_pir=True)
 
     cls_name = "{}_{}_{}".format(op_type, typename, 'not_equal_all')
     Cls.__name__ = cls_name
@@ -51,7 +51,7 @@ def setUp(self):
             self.op_type = op_type
 
         def test_output(self):
-            self.check_output()
+            self.check_output(check_pir=True)
 
     cls_name = "{}_{}_{}".format(op_type, typename, 'not_shape_equal_all')
     Cls.__name__ = cls_name
@@ -69,7 +69,7 @@ def setUp(self):
             self.op_type = op_type
 
         def test_output(self):
-            self.check_output()
+            self.check_output(check_pir=True)
 
     cls_name = "{}_{}_{}".format(op_type, typename, 'equal_all')
     Cls.__name__ = cls_name
@@ -89,7 +89,7 @@ def setUp(self):
             self.op_type = op_type
 
         def test_output(self):
-            self.check_output()
+            self.check_output(check_pir=True)
 
     cls_name = "{}_{}_{}".format(op_type, typename, 'equal_all')
     Cls.__name__ = cls_name

test/legacy_test/test_expand_as_v2_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 TestExpandAsBasic(OpTest):
@@ -48,10 +49,10 @@ def if_enable_cinn(self):
         pass
 
     def test_check_output(self):
-        self.check_output(check_prim=True)
+        self.check_output(check_prim=True, check_pir=True)
 
     def test_check_grad(self):
-        self.check_grad(['X'], 'Out', check_prim=True)
+        self.check_grad(['X'], 'Out', check_prim=True, check_pir=True)
 
 
 class TestExpandAs_ZeroDim1(TestExpandAsBasic):
@@ -104,11 +105,11 @@ def if_enable_cinn(self):
         self.enable_cinn = False
 
     def test_check_output(self):
-        self.check_output_with_place(place=paddle.CUDAPlace(0))
+        self.check_output_with_place(place=paddle.CUDAPlace(0), check_pir=True)
 
     def test_check_grad(self):
         self.check_grad_with_place(
-            paddle.CUDAPlace(0), ['X'], 'Out', check_prim=True
+            paddle.CUDAPlace(0), ['X'], 'Out', check_prim=True, check_pir=True
         )
 
 
@@ -242,7 +243,7 @@ def setUp(self):
         self.outputs = {'Out': convert_float_to_uint16(output)}
 
     def test_check_output(self):
-        self.check_output_with_place(place=paddle.CUDAPlace(0))
+        self.check_output_with_place(place=paddle.CUDAPlace(0), check_pir=True)
 
     def test_check_grad(self):
         pass
@@ -261,26 +262,28 @@ def test_errors(self):
 
 # Test python API
 class TestExpandAsV2API(unittest.TestCase):
+    @test_with_pir_api
     def test_api(self):
-        input1 = np.random.random([12, 14]).astype("float32")
-        input2 = np.random.random([2, 12, 14]).astype("float32")
-        x = paddle.static.data(name='x', shape=[12, 14], dtype="float32")
-
-        y = paddle.static.data(
-            name='target_tensor',
-            shape=[2, 12, 14],
-            dtype="float32",
-        )
-
-        out_1 = paddle.expand_as(x, y=y)
-
-        exe = base.Executor(place=base.CPUPlace())
-        res_1 = exe.run(
-            base.default_main_program(),
-            feed={"x": input1, "target_tensor": input2},
-            fetch_list=[out_1],
-        )
-        np.testing.assert_array_equal(res_1[0], np.tile(input1, (2, 1, 1)))
+        with paddle.static.program_guard(paddle.static.Program()):
+            input1 = np.random.random([12, 14]).astype("float32")
+            input2 = np.random.random([2, 12, 14]).astype("float32")
+            x = paddle.static.data(name='x', shape=[12, 14], dtype="float32")
+
+            y = paddle.static.data(
+                name='target_tensor',
+                shape=[2, 12, 14],
+                dtype="float32",
+            )
+
+            out_1 = paddle.expand_as(x, y=y)
+
+            exe = base.Executor(place=base.CPUPlace())
+            res_1 = exe.run(
+                paddle.static.default_main_program(),
+                feed={"x": input1, "target_tensor": input2},
+                fetch_list=[out_1],
+            )
+            np.testing.assert_array_equal(res_1[0], np.tile(input1, (2, 1, 1)))
 
 
 if __name__ == "__main__":

test/legacy_test/test_flip.py

@@ -100,10 +100,10 @@ def init_attrs(self):
         self.attrs = {"axis": self.axis}
 
     def test_check_output(self):
-        self.check_output(check_cinn=True)
+        self.check_output(check_cinn=True, check_pir=True)
 
     def test_check_grad(self):
-        self.check_grad(["X"], "Out", check_cinn=True)
+        self.check_grad(["X"], "Out", check_cinn=True, check_pir=True)
 
     def init_test_case(self):
         self.in_shape = (6, 4, 2, 3)
@@ -167,12 +167,16 @@ def test_check_output(self):
             if core.is_compiled_with_cuda():
                 place = core.CUDAPlace(0)
                 if core.is_float16_supported(place):
-                    self.check_output_with_place(place, check_cinn=True)
+                    self.check_output_with_place(
+                        place, check_cinn=True, check_pir=True
+                    )
 
         def test_check_grad(self):
             place = core.CUDAPlace(0)
             if core.is_float16_supported(place):
-                self.check_grad_with_place(place, ["X"], "Out", check_cinn=True)
+                self.check_grad_with_place(
+                    place, ["X"], "Out", check_cinn=True, check_pir=True
+                )
 
     cls_name = "{}_{}".format(parent.__name__, "FP16OP")
     TestFlipFP16.__name__ = cls_name
@@ -202,12 +206,12 @@ def init_dtype(self):
         def test_check_output(self):
             place = core.CUDAPlace(0)
             if core.is_bfloat16_supported(place):
-                self.check_output_with_place(place)
+                self.check_output_with_place(place, check_pir=True)
 
         def test_check_grad(self):
             place = core.CUDAPlace(0)
             if core.is_bfloat16_supported(place):
-                self.check_grad_with_place(place, ["X"], "Out")
+                self.check_grad_with_place(place, ["X"], "Out", check_pir=True)
 
     cls_name = "{}_{}".format(parent.__name__, "BF16OP")
     TestFlipBF16.__name__ = cls_name

test/legacy_test/test_full_op.py

@@ -19,60 +19,63 @@
 import paddle
 from paddle import base
 from paddle.base import Program, program_guard
+from paddle.pir_utils import test_with_pir_api
 
 
 # Test python API
 class TestFullAPI(unittest.TestCase):
+    @test_with_pir_api
     def test_api(self):
-        positive_2_int32 = paddle.tensor.fill_constant([1], "int32", 2)
+        with paddle.static.program_guard(paddle.static.Program()):
+            positive_2_int32 = paddle.tensor.fill_constant([1], "int32", 2)
 
-        positive_2_int64 = paddle.tensor.fill_constant([1], "int64", 2)
-        shape_tensor_int32 = paddle.static.data(
-            name="shape_tensor_int32", shape=[2], dtype="int32"
-        )
+            positive_2_int64 = paddle.tensor.fill_constant([1], "int64", 2)
+            shape_tensor_int32 = paddle.static.data(
+                name="shape_tensor_int32", shape=[2], dtype="int32"
+            )
 
-        shape_tensor_int64 = paddle.static.data(
-            name="shape_tensor_int64", shape=[2], dtype="int64"
-        )
+            shape_tensor_int64 = paddle.static.data(
+                name="shape_tensor_int64", shape=[2], dtype="int64"
+            )
 
-        out_1 = paddle.full(shape=[1, 2], dtype="float32", fill_value=1.1)
+            out_1 = paddle.full(shape=[1, 2], dtype="float32", fill_value=1.1)
 
-        out_2 = paddle.full(
-            shape=[1, positive_2_int32], dtype="float32", fill_value=1.1
-        )
+            out_2 = paddle.full(
+                shape=[1, positive_2_int32], dtype="float32", fill_value=1.1
+            )
 
-        out_3 = paddle.full(
-            shape=[1, positive_2_int64], dtype="float32", fill_value=1.1
-        )
+            out_3 = paddle.full(
+                shape=[1, positive_2_int64], dtype="float32", fill_value=1.1
+            )
 
-        out_4 = paddle.full(
-            shape=shape_tensor_int32, dtype="float32", fill_value=1.2
-        )
+            out_4 = paddle.full(
+                shape=shape_tensor_int32, dtype="float32", fill_value=1.2
+            )
 
-        out_5 = paddle.full(
-            shape=shape_tensor_int64, dtype="float32", fill_value=1.1
-        )
+            out_5 = paddle.full(
+                shape=shape_tensor_int64, dtype="float32", fill_value=1.1
+            )
 
-        out_6 = paddle.full(
-            shape=shape_tensor_int64, dtype=np.float32, fill_value=1.1
-        )
+            out_6 = paddle.full(
+                shape=shape_tensor_int64, dtype=np.float32, fill_value=1.1
+            )
 
-        val = paddle.tensor.fill_constant(
-            shape=[1], dtype=np.float32, value=1.1
-        )
-        out_7 = paddle.full(
-            shape=shape_tensor_int64, dtype=np.float32, fill_value=val
-        )
+            val = paddle.tensor.fill_constant(
+                shape=[1], dtype=np.float32, value=1.1
+            )
+            out_7 = paddle.full(
+                shape=shape_tensor_int64, dtype=np.float32, fill_value=val
+            )
 
-        exe = base.Executor(place=base.CPUPlace())
-        res_1, res_2, res_3, res_4, res_5, res_6, res_7 = exe.run(
-            base.default_main_program(),
-            feed={
-                "shape_tensor_int32": np.array([1, 2]).astype("int32"),
-                "shape_tensor_int64": np.array([1, 2]).astype("int64"),
-            },
-            fetch_list=[out_1, out_2, out_3, out_4, out_5, out_6, out_7],
-        )
+            exe = base.Executor(place=base.CPUPlace())
+            res_1, res_2, res_3, res_4, res_5, res_6, res_7 = exe.run(
+                paddle.static.default_main_program(),
+                feed={
+                    "shape_tensor_int32": np.array([1, 2]).astype("int32"),
+                    "shape_tensor_int64": np.array([1, 2]).astype("int64"),
+                },
+                fetch_list=[out_1, out_2, out_3, out_4, out_5, out_6, out_7],
+            )
 
         np.testing.assert_array_equal(
             res_1, np.full([1, 2], 1.1, dtype="float32")

test/legacy_test/test_logical_op.py

@@ -67,6 +67,7 @@
 }
 
 
+# @test_with_pir_api
 def run_static(x_np, y_np, op_str, use_gpu=False, binary_op=True):
     paddle.enable_static()
     startup_program = Program()