【complex op】No.6 add complex support for logical_and/or/xor/not (Padd…

…lePaddle#56323)

* 【complex op】No.6 add complex support for logical_and/or/xor/not

* fix dtype check

* modify the docs

* add special condition for not raise when x.dtype is complex

* add random generate for complex dtype

* fix generate for complex

* fix

* fix

* add corner case for complex type

* fix ut

* fix ut

paddle/phi/kernels/cpu/logical_kernel.cc

@@ -77,6 +77,8 @@ void LogicalNotKernel(const Context& dev_ctx,
                      int64_t,                               \
                      int,                                   \
                      int8_t,                                \
+                     phi::dtype::complex<float>,            \
+                     phi::dtype::complex<double>,           \
                      int16_t) {}
 
 REGISTER_LOGICAL_CPU_KERNEL(logical_and, And)

paddle/phi/kernels/kps/logical_kernel.cu

@@ -97,6 +97,8 @@ PD_REGISTER_KERNEL(logical_xor, KPS, ALL_LAYOUT, phi::LogicalXorKernel, int) {
                      int64_t,                                \
                      int,                                    \
                      int8_t,                                 \
+                     phi::dtype::complex<float>,             \
+                     phi::dtype::complex<double>,            \
                      int16_t) {}
 
 REGISTER_LOGICAL_CUDA_KERNEL(logical_and, And)

python/paddle/tensor/logic.py

@@ -53,6 +53,8 @@ def _logical_op(op_name, x, y, out=None, name=None, binary_op=True):
                 "float32",
                 "float64",
                 "uint16",
+                "complex64",
+                "complex128",
             ],
             op_name,
         )
@@ -70,6 +72,8 @@ def _logical_op(op_name, x, y, out=None, name=None, binary_op=True):
                     "float32",
                     "float64",
                     "uint16",
+                    "complex64",
+                    "complex128",
                 ],
                 op_name,
             )
@@ -114,8 +118,8 @@ def logical_and(x, y, out=None, name=None):
         .. _Introduction to Tensor: ../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor
 
     Args:
-        x (Tensor): the input tensor, it's data type should be one of bool, int8, int16, in32, in64, float16, float32, float64.
-        y (Tensor): the input tensor, it's data type should be one of bool, int8, int16, in32, in64, float16, float32, float64.
+        x (Tensor): the input tensor, it's data type should be one of bool, int8, int16, in32, in64, float16, float32, float64, complex64, complex128.
+        y (Tensor): the input tensor, it's data type should be one of bool, int8, int16, in32, in64, float16, float32, float64, complex64, complex128.
         out(Tensor, optional): The ``Tensor`` that specifies the output of the operator, which can be any ``Tensor`` that has been created in the program. The default value is None, and a new ``Tensor`` will be created to save the output.
         name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
@@ -173,8 +177,8 @@ def logical_or(x, y, out=None, name=None):
         .. _Introduction to Tensor: ../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor
 
     Args:
-        x (Tensor): the input tensor, it's data type should be one of bool, int8, int16, in32, in64, float16, float32, float64.
-        y (Tensor): the input tensor, it's data type should be one of bool, int8, int16, in32, in64, float16, float32, float64.
+        x (Tensor): the input tensor, it's data type should be one of bool, int8, int16, in32, in64, float16, float32, float64, complex64, complex128.
+        y (Tensor): the input tensor, it's data type should be one of bool, int8, int16, in32, in64, float16, float32, float64, complex64, complex128.
         out(Tensor): The ``Variable`` that specifies the output of the operator, which can be any ``Tensor`` that has been created in the program. The default value is None, and a new ``Tensor`` will be created to save the output.
         name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
@@ -234,8 +238,8 @@ def logical_xor(x, y, out=None, name=None):
         .. _Introduction to Tensor: ../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor
 
     Args:
-        x (Tensor): the input tensor, it's data type should be one of bool, int8, int16, int32, int64, float16, float32, float64.
-        y (Tensor): the input tensor, it's data type should be one of bool, int8, int16, int32, int64, float16, float32, float64.
+        x (Tensor): the input tensor, it's data type should be one of bool, int8, int16, int32, int64, float16, float32, float64, complex64, complex128.
+        y (Tensor): the input tensor, it's data type should be one of bool, int8, int16, int32, int64, float16, float32, float64, complex64, complex128.
         out(Tensor): The ``Tensor`` that specifies the output of the operator, which can be any ``Tensor`` that has been created in the program. The default value is None, and a new ``Tensor`` will be created to save the output.
         name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
@@ -296,7 +300,7 @@ def logical_not(x, out=None, name=None):
         .. _Introduction to Tensor: ../../guides/beginner/tensor_en.html#chapter5-broadcasting-of-tensor
 
     Args:
-        x(Tensor):  Operand of logical_not operator. Must be a Tensor of type bool, int8, int16, in32, in64, float16, float32, or float64.
+        x(Tensor):  Operand of logical_not operator. Must be a Tensor of type bool, int8, int16, in32, in64, float16, float32, or float64, complex64, complex128.
         out(Tensor): The ``Tensor`` that specifies the output of the operator, which can be any ``Tensor`` that has been created in the program. The default value is None, and a new ``Tensor` will be created to save the output.
         name(str|None): The default value is None. Normally there is no need for users to set this property. For more information, please refer to :ref:`api_guide_Name`.
 

test/legacy_test/test_logical_op.py

@@ -31,6 +31,8 @@
     np.float16,
     np.float32,
     np.float64,
+    np.complex64,
+    np.complex128,
 ]
 
 TEST_META_OP_DATA = [
@@ -124,6 +126,10 @@ def np_data_generator(np_shape, dtype, *args, **kwargs):
     elif dtype == np.uint16:
         x = np.random.uniform(0.0, 1.0, np_shape).astype(np.float32)
         return convert_float_to_uint16(x)
+    elif dtype == np.complex64 or dtype == np.complex128:
+        return np.random.normal(0, 1, np_shape).astype(dtype) + (
+            1.0j * np.random.normal(0, 1, np_shape)
+        ).astype(dtype)
     else:
         return np.random.normal(0, 1, np_shape).astype(dtype)
 
@@ -169,6 +175,41 @@ def test(unit_test, use_gpu=False, test_error=False):
                     (dygraph_result.numpy() == np_result).all()
                 )
                 unit_test.assertTrue((eager_result.numpy() == np_result).all())
+            # add some corner case for complex datatype
+            for complex_data_type in [np.complex64, np.complex128]:
+                for x_data in (0 + 0j, 0 + 1j, 1 + 0j, 1 + 1j):
+                    for y_data in (0 + 0j, 0 + 1j, 1 + 0j, 1 + 1j):
+                        meta_data['x_np'] = (
+                            x_data * np.ones(shape_data['x_shape'])
+                        ).astype(complex_data_type)
+                        meta_data['y_np'] = (
+                            y_data * np.ones(shape_data['y_shape'])
+                        ).astype(complex_data_type)
+                        if meta_data['binary_op'] and test_error:
+                            # catch C++ Exception
+                            unit_test.assertRaises(
+                                BaseException, run_static, **meta_data
+                            )
+                            unit_test.assertRaises(
+                                BaseException, run_dygraph, **meta_data
+                            )
+                            continue
+                        static_result = run_static(**meta_data)
+                        dygraph_result = run_dygraph(**meta_data)
+                        eager_result = run_eager(**meta_data)
+                        if meta_data['binary_op']:
+                            np_result = np_op(
+                                meta_data['x_np'], meta_data['y_np']
+                            )
+                        else:
+                            np_result = np_op(meta_data['x_np'])
+                        unit_test.assertTrue((static_result == np_result).all())
+                        unit_test.assertTrue(
+                            (dygraph_result.numpy() == np_result).all()
+                        )
+                        unit_test.assertTrue(
+                            (eager_result.numpy() == np_result).all()
+                        )
 
 
 def test_type_error(unit_test, use_gpu, type_str_map):
@@ -180,7 +221,9 @@ def check_type(op_str, x, y, binary_op):
             y = paddle.to_tensor(y)
             error_type = BaseException
         if binary_op:
-            if type_str_map['x'] != type_str_map['y']:
+            if type_str_map['x'] != type_str_map['y'] and type_str_map[
+                'x'
+            ] not in [np.complex64, np.complex128]:
                 unit_test.assertRaises(error_type, op, x=x, y=y)
             if not in_dynamic_mode():
                 error_type = TypeError