PaddlePaddle
diff --git a/‎python/paddle/pir/math_op_patch.py
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+3-1Lines changed: 3 additions & 1 deletion b/‎python/paddle/pir/math_op_patch.py
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+3-1Lines changed: 3 additions & 1 deletion
diff --git a/‎python/paddle/tensor/creation.py
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+6-6Lines changed: 6 additions & 6 deletions b/‎python/paddle/tensor/creation.py
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+6-6Lines changed: 6 additions & 6 deletions
diff --git a/‎python/paddle/tensor/linalg.py
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+8-8Lines changed: 8 additions & 8 deletions b/‎python/paddle/tensor/linalg.py
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+8-8Lines changed: 8 additions & 8 deletions
diff --git a/‎python/paddle/tensor/manipulation.py
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+16-2Lines changed: 16 additions & 2 deletions b/‎python/paddle/tensor/manipulation.py
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+16-2Lines changed: 16 additions & 2 deletions
diff --git a/‎python/paddle/tensor/math.py
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+1-1Lines changed: 1 addition & 1 deletion b/‎python/paddle/tensor/math.py
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+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎python/paddle/tensor/stat.py
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+3-3Lines changed: 3 additions & 3 deletions b/‎python/paddle/tensor/stat.py
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+3-3Lines changed: 3 additions & 3 deletions
diff --git a/‎test/legacy_test/test_broadcast_to_op.py
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+5Lines changed: 5 additions & 0 deletions b/‎test/legacy_test/test_broadcast_to_op.py
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+5Lines changed: 5 additions & 0 deletions
diff --git a/‎test/legacy_test/test_determinant_op.py
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+9-4Lines changed: 9 additions & 4 deletions b/‎test/legacy_test/test_determinant_op.py
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+9-4Lines changed: 9 additions & 4 deletions
diff --git a/‎test/legacy_test/test_diag_v2.py
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+4-4Lines changed: 4 additions & 4 deletions b/‎test/legacy_test/test_diag_v2.py
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+4-4Lines changed: 4 additions & 4 deletions
diff --git a/‎test/legacy_test/test_index_add_op.py
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+11-7Lines changed: 11 additions & 7 deletions b/‎test/legacy_test/test_index_add_op.py
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+11-7Lines changed: 11 additions & 7 deletions
@@ -289,7 +289,9 @@ def __impl__(self, other_var):
                 python_api == paddle.divide
             ) and self.dtype in _supported_int_dtype_:
                 self = paddle.cast(self, DataType.FLOAT32)
-                other_var = paddle.cast(other_var_opresult, DataType.FLOAT32)
+                other_var_opresult = paddle.cast(
+                    other_var_opresult, DataType.FLOAT32
+                )
 
             out = python_api(self, other_var_opresult)
             return out
 
@@ -309,20 +309,20 @@ def linspace(start, stop, num, dtype=None, name=None):
     tensor_num = num
     tensor_start = start
     tensor_stop = stop
-    if not isinstance(num, Variable):
+    if not isinstance(num, (Variable, paddle.pir.OpResult)):
         check_type(num, 'num', (int), 'linspace')
     if not isinstance(dtype, core.VarDesc.VarType):
         dtype = convert_np_dtype_to_dtype_(dtype)
-    if not isinstance(start, Variable):
+    if not isinstance(start, (Variable, paddle.pir.OpResult)):
         with device_guard("cpu"):
             tensor_start = fill_constant([1], dtype, start, force_cpu=True)
-    if not isinstance(stop, Variable):
+    if not isinstance(stop, (Variable, paddle.pir.OpResult)):
         with device_guard("cpu"):
             tensor_stop = fill_constant([1], dtype, stop, force_cpu=True)
-    if not isinstance(num, Variable):
+    if not isinstance(num, (Variable, paddle.pir.OpResult)):
         with device_guard("cpu"):
             tensor_num = fill_constant([1], 'int32', num, force_cpu=True)
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.linspace(
             tensor_start,
             tensor_stop,
@@ -2006,7 +2006,7 @@ def diag(x, offset=0, padding_value=0, name=None):
             Tensor(shape=[1], dtype=int64, place=Place(cpu), stop_gradient=True,
             [4])
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.diag(x, offset, padding_value)
     else:
         check_type(x, 'x', (Variable), 'diag_v2')
 
@@ -857,7 +857,7 @@ def mat_norm(input, porder=1.0, axis=None):
             Calculate the matrix norm of a square matrix or batches of square matrices,
             when porder is in (1, -1, inf, -inf)
         """
-        if in_dynamic_mode():
+        if in_dynamic_or_pir_mode():
             abs_out = _C_ops.abs(input)
             sum_out = _C_ops.sum(abs_out, axis, None, False)
 
@@ -920,7 +920,7 @@ def fro_norm(input, porder=2, axis=[-1]):
         NOTE:
             Calculate the frobenius norm of a square matrix or batches of square matrices.
         """
-        if in_dynamic_mode():
+        if in_dynamic_or_pir_mode():
             pow_out = _C_ops.pow(input, porder)
             sum_out_1 = _C_ops.sum(pow_out, axis, None, False)
             sum_out_2 = _C_ops.sum(sum_out_1, axis, None, False)
@@ -983,7 +983,7 @@ def svd_norm(input, porder, axis=[-1]):
         """
         u, s, vh = svd(input, full_matrices=False)
 
-        if in_dynamic_mode():
+        if in_dynamic_or_pir_mode():
             if porder == "nuc":
                 return _C_ops.sum(s, axis, None, False)
             max_out = _C_ops.max(s, axis, False)
@@ -1054,7 +1054,7 @@ def svd_norm(input, porder, axis=[-1]):
                 return out
 
     def empty_tensor(input, shape):
-        if in_dynamic_mode():
+        if in_dynamic_or_pir_mode():
             return input.reshape(shape)
         raise ValueError(
             "only support x is nonempty tensor in static graph mode"
@@ -1905,7 +1905,7 @@ def det(x, name=None):
 
 
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.det(x)
     else:
         check_dtype(x.dtype, 'Input', ['float16', 'float32', 'float64'], 'det')
@@ -1964,7 +1964,7 @@ def slogdet(x, name=None):
              [ 0.25681755, -0.25061053, -0.10809582]])
 
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.slogdet(x)
     else:
         check_dtype(x.dtype, 'Input', ['float32', 'float64'], 'slogdet')
@@ -3143,7 +3143,7 @@ def solve(x, y, name=None):
             Tensor(shape=[2], dtype=float64, place=Place(cpu), stop_gradient=True,
             [2., 3.])
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.solve(x, y)
     else:
         inputs = {"X": [x], "Y": [y]}
@@ -3215,7 +3215,7 @@ def triangular_solve(
              [-2.],
              [-5.]])
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.triangular_solve(x, y, upper, transpose, unitriangular)
     else:
         inputs = {"X": [x], "Y": [y]}
 
@@ -30,6 +30,7 @@
 from ..base.framework import Variable
 from ..framework import (
     LayerHelper,
+    _current_expected_place,
     convert_np_dtype_to_dtype_,
     core,
     dygraph_only,
@@ -3517,8 +3518,19 @@ def broadcast_to(x, shape, name=None):
             [[1, 2, 3],
              [1, 2, 3]])
     """
+
     if in_dynamic_mode():
         return _C_ops.expand(x, shape)
+    elif in_pir_mode():
+        place = _current_expected_place()
+        if isinstance(shape, (list, tuple)):
+            if paddle.utils._contain_var(shape):
+                shape = paddle.utils.get_int_tensor_list(shape, place)
+        elif isinstance(shape, paddle.pir.OpResult):
+            shape.stop_gradient = True
+        else:
+            TypeError("Shape only supports OpReslut, or list, or tuple.")
+        return _C_ops.expand(x, shape)
     else:
         if isinstance(shape, Variable):
             assert len(shape.shape) == 1, 'shape must be an 1-D Tensor.'
@@ -3636,6 +3648,8 @@ def expand(x, shape, name=None):
         elif isinstance(shape, (list, tuple)):
             if paddle.utils._contain_var(shape):
                 shape = paddle.utils._convert_to_tensor_list(shape)
+        else:
+            TypeError("Shape only supports OpReslut, or list, or tuple.")
         return _C_ops.expand(x, shape)
     else:
         if isinstance(shape, Variable):
@@ -5080,7 +5094,7 @@ def index_add(x, index, axis, value, name=None):
              [1., 1., 1.],
              [2., 2., 2.]])
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.index_add(x, index, value, axis)
 
     helper = LayerHelper("index_add", **locals())
@@ -5216,7 +5230,7 @@ def index_put(x, indices, value, accumulate=False, name=None):
              [0., 0., 1.],
              [0., 1., 0.]])
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.index_put(x, indices, value, accumulate)
 
     helper = LayerHelper("index_put", **locals())
 
@@ -2672,7 +2672,7 @@ def inverse(x, name=None):
              [0.        , 0.50000000]])
 
     """
-    if in_dynamic_mode():
+    if in_dynamic_or_pir_mode():
         return _C_ops.inverse(x)
     else:
 
 
@@ -159,8 +159,8 @@ def var(x, axis=None, unbiased=True, keepdim=False, name=None):
     out = paddle.sum(paddle.pow((x - u), 2), axis, keepdim=keepdim, name=name)
 
     dtype = x.dtype
-    n = paddle.cast(paddle.numel(x), paddle.int64) / paddle.cast(
-        paddle.numel(out), paddle.int64
+    n = paddle.cast(paddle.numel(x), "int64") / paddle.cast(
+        paddle.numel(out), "int64"
     )
     n = n.astype(dtype)
     if unbiased:
@@ -221,7 +221,7 @@ def std(x, axis=None, unbiased=True, keepdim=False, name=None):
             [1.       2.081666]
 
     """
-    if not in_dynamic_mode():
+    if not in_dynamic_or_pir_mode():
         check_variable_and_dtype(
             x, 'x', ['float16', 'float32', 'float64'], 'std'
         )
 
@@ -19,6 +19,7 @@
 import paddle
 from paddle import base
 from paddle.base import Program, program_guard
+from paddle.pir_utils import test_with_pir_api
 
 paddle.enable_static()
 
@@ -40,6 +41,9 @@ def test_errors(self):
 
 # Test python API
 class TestBroadcastToAPI(unittest.TestCase):
+    # TODO: add test_with_pir_api
+    # base.backward.calc_gradient maybe not support pir
+    # AttributeError: 'paddle.base.libpaddle.pir.Program' object has no attribute '_appending_grad_times'
     def test_api(self):
         input = np.random.random([12, 14]).astype("float32")
         x = paddle.static.data(name='x', shape=[12, 14], dtype="float32")
@@ -70,6 +74,7 @@ def test_api(self):
         np.testing.assert_array_equal(res_2, np.tile(input, (1, 1)))
         np.testing.assert_array_equal(res_3, np.tile(input, (1, 1)))
 
+    @test_with_pir_api
     def test_api_fp16_gpu(self):
         if paddle.base.core.is_compiled_with_cuda():
             place = paddle.CUDAPlace(0)
 
@@ -18,6 +18,7 @@
 from op_test import OpTest
 
 import paddle
+from paddle.pir_utils import test_with_pir_api
 
 paddle.enable_static()
 
@@ -30,10 +31,10 @@ def setUp(self):
         self.outputs = {'Out': self.target}
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_pir=True)
 
     def test_check_grad(self):
-        self.check_grad(['Input'], ['Out'])
+        self.check_grad(['Input'], ['Out'], check_pir=True)
 
     def init_data(self):
         np.random.seed(0)
@@ -85,6 +86,7 @@ def setUp(self):
         self.x = np.random.random(self.shape).astype(np.float32)
         self.place = paddle.CPUPlace()
 
+    @test_with_pir_api
     def test_api_static(self):
         paddle.enable_static()
         with paddle.static.program_guard(paddle.static.Program()):
@@ -114,11 +116,13 @@ def setUp(self):
         self.outputs = {'Out': self.target}
 
     def test_check_output(self):
-        self.check_output()
+        self.check_output(check_pir=True)
 
     def test_check_grad(self):
         # the slog det's grad value is always huge
-        self.check_grad(['Input'], ['Out'], max_relative_error=0.1)
+        self.check_grad(
+            ['Input'], ['Out'], max_relative_error=0.1, check_pir=True
+        )
 
     def init_data(self):
         np.random.seed(0)
@@ -142,6 +146,7 @@ def setUp(self):
         self.x = np.random.random(self.shape).astype(np.float32)
         self.place = paddle.CPUPlace()
 
+    @test_with_pir_api
     def test_api_static(self):
         paddle.enable_static()
         with paddle.static.program_guard(paddle.static.Program()):
 
@@ -51,11 +51,11 @@ def init_input_output(self):
 
     def test_check_output(self):
         paddle.enable_static()
-        self.check_output()
+        self.check_output(check_pir=True)
 
     def test_check_grad(self):
         paddle.enable_static()
-        self.check_grad(['X'], 'Out')
+        self.check_grad(['X'], 'Out', check_pir=True)
 
 
 class TestDiagV2OpCase1(TestDiagV2Op):
@@ -335,12 +335,12 @@ def setUp(self):
     def test_check_output(self):
         paddle.enable_static()
         place = core.CUDAPlace(0)
-        self.check_output_with_place(place)
+        self.check_output_with_place(place, check_pir=True)
 
     def test_check_grad(self):
         paddle.enable_static()
         place = core.CUDAPlace(0)
-        self.check_grad_with_place(place, ['X'], 'Out')
+        self.check_grad_with_place(place, ['X'], 'Out', check_pir=True)
 
 
 if __name__ == "__main__":
 
@@ -18,7 +18,8 @@
 from op_test import OpTest, convert_float_to_uint16
 
 import paddle
-from paddle.base import Program, core
+from paddle.base import core
+from paddle.pir_utils import test_with_pir_api
 
 
 def compute_index_add_ref(
@@ -93,10 +94,10 @@ def init_dtype_type(self):
         self.add_value_shape = (3, 3)
 
     def test_check_output(self):
-        self.check_output(atol=1e-2)
+        self.check_output(atol=1e-2, check_pir=True)
 
     def test_check_grad_normal(self):
-        self.check_grad(['X', 'AddValue'], 'Out')
+        self.check_grad(['X', 'AddValue'], 'Out', check_pir=True)
 
 
 class TestIndexAddFP16Op(TestIndexAddOp):
@@ -156,10 +157,12 @@ def init_dtype_type(self):
         self.dtype = np.uint16
 
     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_normal(self):
-        self.check_grad_with_place(self.place, ['X', 'AddValue'], 'Out')
+        self.check_grad_with_place(
+            self.place, ['X', 'AddValue'], 'Out', check_pir=True
+        )
 
 
 class TestIndexAddAPI(unittest.TestCase):
@@ -290,15 +293,16 @@ def run_static(self, device):
                 "Index": self.index_np,
                 "AddValue": self.add_value_np,
             },
-            fetch_list=[out.name],
+            fetch_list=[out],
             return_numpy=False,
         )
         return res
 
+    @test_with_pir_api
     def test_static(self):
         paddle.enable_static()
         for device in self.place:
-            with paddle.static.program_guard(Program()):
+            with paddle.static.program_guard(paddle.static.Program()):
                 out = self.run_static(device)
             ref_out = compute_index_add_ref(
                 self.axis,