OP:strided_slice_op supports bool type inputs (#33373) (#33393)

* Fix two english api documents, transpose and strided_slice

* OP:strided_slice_op supports bool type inputs

Author: TeslaZhao

paddle/fluid/operators/strided_slice_op.cc

@@ -324,6 +324,7 @@ REGISTER_OPERATOR(strided_slice_grad, ops::StridedSliceOpGrad,
 
 REGISTER_OP_CPU_KERNEL(
     strided_slice,
+    ops::StridedSliceKernel<paddle::platform::CPUDeviceContext, bool>,
     ops::StridedSliceKernel<paddle::platform::CPUDeviceContext, int>,
     ops::StridedSliceKernel<paddle::platform::CPUDeviceContext, int64_t>,
     ops::StridedSliceKernel<paddle::platform::CPUDeviceContext, float>,
@@ -335,6 +336,7 @@ REGISTER_OP_CPU_KERNEL(
 
 REGISTER_OP_CPU_KERNEL(
     strided_slice_grad,
+    ops::StridedSliceGradKernel<paddle::platform::CPUDeviceContext, bool>,
     ops::StridedSliceGradKernel<paddle::platform::CPUDeviceContext, int>,
     ops::StridedSliceGradKernel<paddle::platform::CPUDeviceContext, int64_t>,
     ops::StridedSliceGradKernel<paddle::platform::CPUDeviceContext, float>,

paddle/fluid/operators/strided_slice_op.cu

@@ -19,6 +19,7 @@ limitations under the License. */
 namespace ops = paddle::operators;
 REGISTER_OP_CUDA_KERNEL(
     strided_slice,
+    ops::StridedSliceKernel<paddle::platform::CUDADeviceContext, bool>,
     ops::StridedSliceKernel<paddle::platform::CUDADeviceContext, int>,
     ops::StridedSliceKernel<paddle::platform::CUDADeviceContext, int64_t>,
     ops::StridedSliceKernel<paddle::platform::CUDADeviceContext, float>,
@@ -30,7 +31,8 @@ REGISTER_OP_CUDA_KERNEL(
 
 REGISTER_OP_CUDA_KERNEL(
     strided_slice_grad,
-    ops::StridedSliceGradKernel<paddle::platform::CPUDeviceContext, int>,
+    ops::StridedSliceGradKernel<paddle::platform::CUDADeviceContext, bool>,
+    ops::StridedSliceGradKernel<paddle::platform::CUDADeviceContext, int>,
     ops::StridedSliceGradKernel<paddle::platform::CUDADeviceContext, int64_t>,
     ops::StridedSliceGradKernel<paddle::platform::CUDADeviceContext, float>,
     ops::StridedSliceGradKernel<paddle::platform::CUDADeviceContext, double>,

python/paddle/fluid/layers/nn.py

@@ -11075,7 +11075,7 @@ def strided_slice(input, axes, starts, ends, strides):
             Then:
                 result = [ [2], ]
     Args:
-        input (Variable): An N-D ``Tensor`` or ``LoDTensor`` . The data type is ``float32``, ``float64``, ``int32`` or ``int64``.
+        input (Variable): An N-D ``Tensor`` or ``LoDTensor`` . The data type is ``bool``, ``float32``, ``float64``, ``int32`` or ``int64``.
         axes (list|tuple): The data type is ``int32`` . Axes that `starts` and `ends` apply to.
                             It's optional. If it is not provides, it will be treated as :math:`[0,1,...,len(starts)-1]`.
         starts (list|tuple|Variable): The data type is ``int32`` . If ``starts`` is a list or tuple, the elements of
@@ -11126,7 +11126,7 @@ def strided_slice(input, axes, starts, ends, strides):
     helper = LayerHelper('strided_slice', **locals())
 
     check_variable_and_dtype(input, 'input',
-                             ['float32', 'float64', 'int32', 'int64'],
+                             ['bool', 'float32', 'float64', 'int32', 'int64'],
                              'strided_slice')
     check_type(axes, 'axes', (list, tuple), 'strided_slice')
     check_type(starts, 'starts', (list, tuple, Variable), 'strided_slice')

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

@@ -216,6 +216,71 @@ def initTestCase(self):
         self.infer_flags = [1, 1, 1, 1, 1]
 
 
+class TestStrideSliceOpBool(TestStrideSliceOp):
+    def test_check_grad(self):
+        pass
+
+
+class TestStrideSliceOpBool1D(TestStrideSliceOpBool):
+    def initTestCase(self):
+        self.input = np.random.rand(100).astype("bool")
+        self.axes = [0]
+        self.starts = [3]
+        self.ends = [8]
+        self.strides = [1]
+        self.infer_flags = [1]
+
+
+class TestStrideSliceOpBool2D(TestStrideSliceOpBool):
+    def initTestCase(self):
+        self.input = np.random.rand(10, 10).astype("bool")
+        self.axes = [0, 1]
+        self.starts = [1, 0]
+        self.ends = [2, 2]
+        self.strides = [1, 1]
+        self.infer_flags = [1, 1]
+
+
+class TestStrideSliceOpBool3D(TestStrideSliceOpBool):
+    def initTestCase(self):
+        self.input = np.random.rand(3, 4, 10).astype("bool")
+        self.axes = [0, 1, 2]
+        self.starts = [0, -1, 0]
+        self.ends = [2, -3, 5]
+        self.strides = [1, -1, 1]
+        self.infer_flags = [1, 1, 1]
+
+
+class TestStrideSliceOpBool4D(TestStrideSliceOpBool):
+    def initTestCase(self):
+        self.input = np.random.rand(3, 3, 3, 4).astype("bool")
+        self.axes = [0, 1, 2, 3]
+        self.starts = [1, 0, 0, 0]
+        self.ends = [2, 2, 3, 4]
+        self.strides = [1, 1, 1, 2]
+        self.infer_flags = [1, 1, 1, 1]
+
+
+class TestStrideSliceOpBool5D(TestStrideSliceOpBool):
+    def initTestCase(self):
+        self.input = np.random.rand(3, 3, 3, 4, 5).astype("bool")
+        self.axes = [0, 1, 2, 3, 4]
+        self.starts = [1, 0, 0, 0, 0]
+        self.ends = [2, 2, 3, 4, 4]
+        self.strides = [1, 1, 1, 1, 1]
+        self.infer_flags = [1, 1, 1, 1]
+
+
+class TestStrideSliceOpBool6D(TestStrideSliceOpBool):
+    def initTestCase(self):
+        self.input = np.random.rand(3, 3, 3, 6, 7, 8).astype("bool")
+        self.axes = [0, 1, 2, 3, 4, 5]
+        self.starts = [1, 0, 0, 0, 1, 2]
+        self.ends = [2, 2, 3, 1, 2, 8]
+        self.strides = [1, 1, 1, 1, 1, 2]
+        self.infer_flags = [1, 1, 1, 1, 1]
+
+
 class TestStridedSliceOp_starts_ListTensor(OpTest):
     def setUp(self):
         self.op_type = "strided_slice"