multiply supports bool

multiply supports bool  

paddle/fluid/operators/elementwise/elementwise_mul_op.cc

@@ -132,6 +132,7 @@ REGISTER_OP_CPU_KERNEL(
     ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext, double>,
     ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext, int>,
     ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext, int64_t>,
+    ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext, bool>,
     ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext,
                               paddle::platform::complex<float>>,
     ops::ElementwiseMulKernel<paddle::platform::CPUDeviceContext,
@@ -142,6 +143,7 @@ REGISTER_OP_CPU_KERNEL(
     ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext, double>,
     ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext, int>,
     ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext, int64_t>,
+    ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext, bool>,
     ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext,
                                   paddle::platform::complex<float>>,
     ops::ElementwiseMulGradKernel<paddle::platform::CPUDeviceContext,
@@ -156,6 +158,8 @@ REGISTER_OP_CPU_KERNEL(
                                         int>,
     ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
                                         int64_t>,
+    ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
+                                        bool>,
     ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,
                                         paddle::platform::complex<float>>,
     ops::ElementwiseMulDoubleGradKernel<paddle::platform::CPUDeviceContext,

paddle/fluid/operators/elementwise/elementwise_mul_op.cu

@@ -121,6 +121,7 @@ REGISTER_OP_CUDA_KERNEL(
     ops::ElementwiseMulKernel<plat::CUDADeviceContext, double>,
     ops::ElementwiseMulKernel<plat::CUDADeviceContext, int>,
     ops::ElementwiseMulKernel<plat::CUDADeviceContext, int64_t>,
+    ops::ElementwiseMulKernel<plat::CUDADeviceContext, bool>,
     ops::ElementwiseMulKernel<plat::CUDADeviceContext, plat::float16>,
     ops::ElementwiseMulKernel<plat::CUDADeviceContext, plat::complex<float>>,
     ops::ElementwiseMulKernel<plat::CUDADeviceContext, plat::complex<double>>);
@@ -130,6 +131,7 @@ REGISTER_OP_CUDA_KERNEL(
     ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, double>,
     ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, int>,
     ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, int64_t>,
+    ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, bool>,
     ops::ElementwiseMulGradKernel<plat::CUDADeviceContext, plat::float16>,
     ops::ElementwiseMulGradKernel<plat::CUDADeviceContext,
                                   plat::complex<float>>,
@@ -141,6 +143,7 @@ REGISTER_OP_CUDA_KERNEL(
     ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, double>,
     ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, int>,
     ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, int64_t>,
+    ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, bool>,
     ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext, plat::float16>,
     ops::ElementwiseMulDoubleGradKernel<plat::CUDADeviceContext,
                                         plat::complex<float>>,

python/paddle/fluid/tests/unittests/test_multiply.py

@@ -70,6 +70,12 @@ class TestMultiplyApi(unittest.TestCase):
         res = self._run_static_graph_case(x_data, y_data)
         self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))
 
+        # test static computation graph: boolean
+        x_data = np.random.choice([True, False], size=[200])
+        y_data = np.random.choice([True, False], size=[200])
+        res = self._run_static_graph_case(x_data, y_data)
+        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))
+
         # test dynamic computation graph: 1-d array
         x_data = np.random.rand(200)
         y_data = np.random.rand(200)
@@ -88,6 +94,12 @@ class TestMultiplyApi(unittest.TestCase):
         res = self._run_dynamic_graph_case(x_data, y_data)
         self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))
 
+        # test dynamic computation graph: boolean
+        x_data = np.random.choice([True, False], size=[200])
+        y_data = np.random.choice([True, False], size=[200])
+        res = self._run_dynamic_graph_case(x_data, y_data)
+        self.assertTrue(np.allclose(res, np.multiply(x_data, y_data)))
+
 
 class TestMultiplyError(unittest.TestCase):
     def test_errors(self):

python/paddle/tensor/math.py

@@ -196,10 +196,10 @@ def _elementwise_op(helper):
     assert x is not None, 'x cannot be None in {}'.format(original_op_type)
     assert y is not None, 'y cannot be None in {}'.format(original_op_type)
     check_variable_and_dtype(
-        x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'],
+        x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64', 'bool'],
         original_op_type)
     check_variable_and_dtype(
-        y, 'y', ['float16', 'float32', 'float64', 'int32', 'int64'],
+        y, 'y', ['float16', 'float32', 'float64', 'int32', 'int64', 'bool'],
         original_op_type)
 
     axis = helper.kwargs.get('axis', -1)
@@ -473,8 +473,8 @@ def multiply(x, y, name=None):
     ``paddle.multiply`` supports broadcasting. If you would like to know more about broadcasting, please refer to :ref:`user_guide_broadcasting` .
 
     Args:
-        x (Tensor): the input tensor, its data type should be float32, float64, int32, int64.
-        y (Tensor): the input tensor, its data type should be float32, float64, int32, int64.
+        x (Tensor): the input tensor, its data type should be one of float32, float64, int32, int64, bool.
+        y (Tensor): the input tensor, its data type should be one of float32, float64, int32, int64, bool.
         name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`.
 
     Returns: