[pir] add unittest for pir test of Dropout (#58106)

* tmp

* modify unsqueeze

* modify part complex bug

* modify

* modify cpu

* [PIR]Migrate maximum into pir

* Polish code

* add ir_grad of static_gradient

* add test

* modify bug

* modify

* test_with_pir

* close one test

* add_math_op_patch

* modify

* modify

* add mean fill_constant test

* modify cpu int32 test

* get_shape_tensor

* delete

* add default place

* add dropout unittest

* Update test/legacy_test/test_elementwise_div_op.py

* modify review comment

* modify add test

---------

Co-authored-by: 0x45f <[email protected]>

python/paddle/nn/functional/common.py

@@ -1196,7 +1196,7 @@ def get_attrs(prog, dropout_prob, is_test, seed):
 
             # get mask shape
             input_shape = x.shape
-            if not in_dynamic_or_pir_mode():
+            if not in_dynamic_mode():
                 input_shape_tensor = paddle.shape(x)
             drop_axes = [axis] if isinstance(axis, int) else list(axis)
             if min(drop_axes) < 0 or max(drop_axes) > len(input_shape) - 1:
@@ -1212,7 +1212,7 @@ def get_attrs(prog, dropout_prob, is_test, seed):
                     )
                 )
             mask_shape = [1] * len(input_shape)
-            if not in_dynamic_or_pir_mode():
+            if not in_dynamic_mode():
                 for i in drop_axes:
                     mask_shape[i] = input_shape_tensor[i]
             else:

python/paddle/pir/math_op_patch.py

@@ -153,6 +153,56 @@ def _item(self):
             )
         return self
 
+    def astype(self, dtype):
+        """
+        **Notes**:
+
+        Cast a OpResult to a specified data type.
+
+        Args:
+
+            self(OpResult): The source OpResult
+
+            dtype: The target data type
+
+        Returns:
+            OpResult: OpResult with new dtype
+
+        Examples:
+            In Static Graph Mode:
+
+            .. code-block:: python
+
+                >>> import paddle
+                >>> paddle.enable_static()
+                >>> startup_prog = paddle.static.Program()
+                >>> main_prog = paddle.static.Program()
+                >>> with paddle.static.program_guard(startup_prog, main_prog):
+                ...     original_value = paddle.static.data(name = "new_value", shape=[2,2], dtype='float32')
+                ...     new_value = original_value.astype('int64')
+                ...     print("new value's dtype is: {}".format(new_value.dtype))
+                ...
+                new OpResult's dtype is: paddle.int64
+
+        """
+        from paddle import _C_ops
+
+        if not isinstance(dtype, DataType):
+            dtype = paddle.pir.core.convert_np_dtype_to_dtype_(dtype)
+        return _C_ops.cast(self, dtype)
+
+    def _scalar_add_(var, value):
+        return paddle.scale(var, 1.0, value)
+
+    def _scalar_sub_(var, value):
+        return paddle.scale(var, 1.0, -value)
+
+    def _scalar_rsub_(var, value):
+        return paddle.scale(var, -1.0, value)
+
+    def _scalar_mul_(var, value):
+        return paddle.scale(var, value, 0.0)
+
     def _scalar_div_(var, value):
         return paddle.scale(var, 1.0 / value, 0.0)
 
@@ -168,7 +218,7 @@ def __impl__(self, other_var):
             if isinstance(other_var, float):
                 # in all cases(+, -, *, /, **, //, %), we need cast tensor.dtype to float
                 if self.dtype in _supported_int_dtype_:
-                    paddle.cast(self, DataType.FLOAT32)
+                    self = astype(self, DataType.FLOAT32)
                 # here use `scale` replace `elementwise` to get better performance
                 # but only +, -, *, / can use this method
                 if scalar_method is not None:
@@ -253,44 +303,6 @@ def __impl__(self, other_var):
         __impl__.__name__ = method_name
         return __impl__
 
-    def astype(self, dtype):
-        """
-        **Notes**:
-
-        Cast a OpResult to a specified data type.
-
-        Args:
-
-            self(OpResult): The source OpResult
-
-            dtype: The target data type
-
-        Returns:
-            OpResult: OpResult with new dtype
-
-        Examples:
-            In Static Graph Mode:
-
-            .. code-block:: python
-
-                >>> import paddle
-                >>> paddle.enable_static()
-                >>> startup_prog = paddle.static.Program()
-                >>> main_prog = paddle.static.Program()
-                >>> with paddle.static.program_guard(startup_prog, main_prog):
-                ...     original_value = paddle.static.data(name = "new_value", shape=[2,2], dtype='float32')
-                ...     new_value = original_value.astype('int64')
-                ...     print("new value's dtype is: {}".format(new_value.dtype))
-                ...
-                new OpResult's dtype is: paddle.int64
-
-        """
-        from paddle import _C_ops
-
-        if not isinstance(dtype, DataType):
-            dtype = paddle.pir.core.convert_np_dtype_to_dtype_(dtype)
-        return _C_ops.cast(self, dtype)
-
     import paddle
 
     opresult_methods = [
@@ -300,6 +312,42 @@ def astype(self, dtype):
         ('ndimension', ndimension),
         ('ndim', _ndim),
         ('astype', astype),
+        (
+            '__add__',
+            _binary_creator_('__add__', paddle.tensor.add, False, _scalar_add_),
+        ),
+        #  a+b == b+a. Do not need to reverse explicitly
+        (
+            '__radd__',
+            _binary_creator_(
+                '__radd__', paddle.tensor.add, False, _scalar_add_
+            ),
+        ),
+        (
+            '__sub__',
+            _binary_creator_(
+                '__sub__', paddle.tensor.subtract, False, _scalar_sub_
+            ),
+        ),
+        (
+            '__rsub__',
+            _binary_creator_(
+                '__rsub__', paddle.tensor.subtract, True, _scalar_rsub_
+            ),
+        ),
+        (
+            '__mul__',
+            _binary_creator_(
+                '__mul__', paddle.tensor.multiply, False, _scalar_mul_
+            ),
+        ),
+        #  a*b == b*a. Do not need to reverse explicitly
+        (
+            '__rmul__',
+            _binary_creator_(
+                '__rmul__', paddle.tensor.multiply, False, _scalar_mul_
+            ),
+        ),
         (
             '__div__',
             _binary_creator_(

python/paddle/tensor/random.py

@@ -796,6 +796,10 @@ def uniform(shape, dtype=None, min=-1.0, max=1.0, seed=0, name=None):
 
     if in_dynamic_or_pir_mode():
         shape = paddle.utils.convert_shape_to_list(shape)
+        if in_pir_mode() and paddle.utils._contain_var(shape):
+            shape = paddle.utils.get_pir_shape_tensor(
+                shape, _current_expected_place()
+            )
         return _C_ops.uniform(
             shape,
             dtype,

python/paddle/utils/layers_utils.py

@@ -393,6 +393,8 @@ def get_pir_shape_tensor(list_shape, place=_current_expected_place()):
             dim.stop_gradient = True
             if convert_dtype(dim.dtype) != 'int32':
                 dim = paddle.cast(x=dim, dtype='int32')
+            if dim.shape == []:
+                dim = paddle.reshape(dim, [-1])
             shape_tensor_list.append(dim)
         else:
             temp_out = paddle.full([1], dim, core.DataType.INT32, place)

test/legacy_test/test_activation_op.py

@@ -2672,6 +2672,7 @@ def setUp(self):
         self.rev_comp_rtol = 1e-8
         self.rev_comp_atol = 1e-8
 
+    @test_with_pir_api
     def test_static_api(self):
         with static_guard():
             with paddle.static.program_guard(paddle.static.Program()):