op:transpose_op supports bool type (#35886)

* Pass compat of conv_transpose_bias_mkldnn_fuse_pass

* Fix a bug of strided_slice op, about the axes parameter access memory out of bounds

* Fix a bug of transpose op, about accessing memory out of bounds of the perm param

* op:transpose_op supports bool type

paddle/fluid/operators/math/math_function.cu

@@ -44,6 +44,7 @@ template struct SetConstant<platform::CUDADeviceContext,
                             platform::complex<double>>;
 
 #define DEFINE_GPU_TRANS(RANK)                                            \
+  template struct Transpose<platform::CUDADeviceContext, bool, RANK>;     \
   template struct Transpose<platform::CUDADeviceContext, float, RANK>;    \
   template struct Transpose<platform::CUDADeviceContext, double, RANK>;   \
   template struct Transpose<platform::CUDADeviceContext, float16, RANK>;  \

paddle/fluid/operators/transpose_op.cc

@@ -350,7 +350,8 @@ REGISTER_OPERATOR(
 REGISTER_OPERATOR(transpose_grad, ops::TransposeOpGrad);
 
 REGISTER_OP_CPU_KERNEL(
-    transpose, ops::TransposeKernel<paddle::platform::CPUDeviceContext, float>,
+    transpose, ops::TransposeKernel<paddle::platform::CPUDeviceContext, bool>,
+    ops::TransposeKernel<paddle::platform::CPUDeviceContext, float>,
     ops::TransposeKernel<paddle::platform::CPUDeviceContext, double>,
     ops::TransposeKernel<paddle::platform::CPUDeviceContext,
                          paddle::platform::complex<float>>,
@@ -358,6 +359,7 @@ REGISTER_OP_CPU_KERNEL(
                          paddle::platform::complex<double>>);
 REGISTER_OP_CPU_KERNEL(
     transpose_grad,
+    ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, bool>,
     ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, float>,
     ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, double>,
     ops::TransposeGradKernel<paddle::platform::CPUDeviceContext,
@@ -373,7 +375,8 @@ REGISTER_OPERATOR(transpose2_grad, ops::Transpose2OpGrad,
                   ops::Transpose2DoubleGradMaker<paddle::imperative::OpBase>);
 
 REGISTER_OP_CPU_KERNEL(
-    transpose2, ops::TransposeKernel<paddle::platform::CPUDeviceContext, float>,
+    transpose2, ops::TransposeKernel<paddle::platform::CPUDeviceContext, bool>,
+    ops::TransposeKernel<paddle::platform::CPUDeviceContext, float>,
     ops::TransposeKernel<paddle::platform::CPUDeviceContext, int32_t>,
     ops::TransposeKernel<paddle::platform::CPUDeviceContext, int64_t>,
     ops::TransposeKernel<paddle::platform::CPUDeviceContext, double>,
@@ -383,6 +386,7 @@ REGISTER_OP_CPU_KERNEL(
                          paddle::platform::complex<double>>);
 REGISTER_OP_CPU_KERNEL(
     transpose2_grad,
+    ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, bool>,
     ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, int32_t>,
     ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, int64_t>,
     ops::TransposeGradKernel<paddle::platform::CPUDeviceContext, float>,

paddle/fluid/operators/transpose_op.cu

@@ -83,6 +83,7 @@ namespace plat = paddle::platform;
 
 REGISTER_OP_CUDA_KERNEL(
     transpose,
+    ops::TransposeGPUKernel<paddle::platform::CUDADeviceContext, bool>,
     ops::TransposeGPUKernel<paddle::platform::CUDADeviceContext, float>,
     ops::TransposeGPUKernel<paddle::platform::CUDADeviceContext, double>,
     ops::TransposeGPUKernel<paddle::platform::CUDADeviceContext, plat::float16>,
@@ -92,6 +93,7 @@ REGISTER_OP_CUDA_KERNEL(
                             paddle::platform::complex<double>>);
 REGISTER_OP_CUDA_KERNEL(
     transpose_grad,
+    ops::TransposeGradGPUKernel<paddle::platform::CUDADeviceContext, bool>,
     ops::TransposeGradGPUKernel<paddle::platform::CUDADeviceContext, float>,
     ops::TransposeGradGPUKernel<paddle::platform::CUDADeviceContext, double>,
     ops::TransposeGradGPUKernel<paddle::platform::CUDADeviceContext,
@@ -103,6 +105,7 @@ REGISTER_OP_CUDA_KERNEL(
 
 REGISTER_OP_CUDA_KERNEL(
     transpose2,
+    ops::TransposeGPUKernel<paddle::platform::CUDADeviceContext, bool>,
     ops::TransposeGPUKernel<paddle::platform::CUDADeviceContext, int32_t>,
     ops::TransposeGPUKernel<paddle::platform::CUDADeviceContext, int64_t>,
     ops::TransposeGPUKernel<paddle::platform::CUDADeviceContext, float>,
@@ -114,6 +117,7 @@ REGISTER_OP_CUDA_KERNEL(
                             paddle::platform::complex<double>>);
 REGISTER_OP_CUDA_KERNEL(
     transpose2_grad,
+    ops::TransposeGradGPUKernel<paddle::platform::CUDADeviceContext, bool>,
     ops::TransposeGradGPUKernel<paddle::platform::CUDADeviceContext, int32_t>,
     ops::TransposeGradGPUKernel<paddle::platform::CUDADeviceContext, int64_t>,
     ops::TransposeGradGPUKernel<paddle::platform::CUDADeviceContext, float>,

python/paddle/fluid/layers/nn.py

@@ -5499,12 +5499,12 @@ def transpose(x, perm, name=None):
     perm[i]-th dimension of `input`.
 
     Args:
-        x (Tensor): The input Tensor. It is a N-D Tensor of data types float32, float64, int32.
+        x (Tensor): The input Tensor. It is a N-D Tensor of data types bool, float32, float64, int32.
         perm (list|tuple): Permute the input according to the data of perm.
         name (str): The name of this layer. It is optional.
 
     Returns:
-        Tensor: A transposed n-D Tensor, with data type being float32, float64, int32, int64.
+        Tensor: A transposed n-D Tensor, with data type being bool, float32, float64, int32, int64.
 
     For Example:
 
@@ -5546,7 +5546,7 @@ def transpose(x, perm, name=None):
         return out
 
     check_variable_and_dtype(
-        x, 'x', ['float16', 'float32', 'float64', 'int32', 'int64'],
+        x, 'x', ['bool', 'float16', 'float32', 'float64', 'int32', 'int64'],
         'transpose')
     check_type(perm, 'perm', (list, tuple), 'transpose')
     if isinstance(perm, tuple):

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

@@ -113,6 +113,99 @@ class TestCase9(TestTransposeOp):
         self.axis = (6, 1, 3, 5, 0, 2, 4, 7)
 
 
+class TestTransposeOpBool(TestTransposeOp):
+    def test_check_grad(self):
+        pass
+
+
+class TestTransposeOpBool1D(TestTransposeOpBool):
+    def initTestCase(self):
+        self.shape = (100, )
+        self.axis = (0, )
+        self.inputs = {'X': np.random.random(self.shape).astype("bool")}
+        self.outputs = {
+            'XShape': np.random.random(self.shape).astype("bool"),
+            'Out': self.inputs['X'].transpose(self.axis)
+        }
+
+
+class TestTransposeOpBool2D(TestTransposeOpBool):
+    def initTestCase(self):
+        self.shape = (3, 40)
+        self.axis = (1, 0)
+        self.inputs = {'X': np.random.random(self.shape).astype("bool")}
+        self.outputs = {
+            'XShape': np.random.random(self.shape).astype("bool"),
+            'Out': self.inputs['X'].transpose(self.axis)
+        }
+
+
+class TestTransposeOpBool3D(TestTransposeOpBool):
+    def initTestCase(self):
+        self.shape = (3, 4, 10)
+        self.axis = (0, 2, 1)
+        self.inputs = {'X': np.random.random(self.shape).astype("bool")}
+        self.outputs = {
+            'XShape': np.random.random(self.shape).astype("bool"),
+            'Out': self.inputs['X'].transpose(self.axis)
+        }
+
+
+class TestTransposeOpBool4D(TestTransposeOpBool):
+    def initTestCase(self):
+        self.shape = (2, 3, 4, 5)
+        self.axis = (0, 2, 3, 1)
+        self.inputs = {'X': np.random.random(self.shape).astype("bool")}
+        self.outputs = {
+            'XShape': np.random.random(self.shape).astype("bool"),
+            'Out': self.inputs['X'].transpose(self.axis)
+        }
+
+
+class TestTransposeOpBool5D(TestTransposeOpBool):
+    def initTestCase(self):
+        self.shape = (2, 3, 4, 5, 6)
+        self.axis = (4, 2, 3, 1, 0)
+        self.inputs = {'X': np.random.random(self.shape).astype("bool")}
+        self.outputs = {
+            'XShape': np.random.random(self.shape).astype("bool"),
+            'Out': self.inputs['X'].transpose(self.axis)
+        }
+
+
+class TestTransposeOpBool6D(TestTransposeOpBool):
+    def initTestCase(self):
+        self.shape = (2, 3, 4, 5, 6, 1)
+        self.axis = (4, 2, 3, 1, 0, 5)
+        self.inputs = {'X': np.random.random(self.shape).astype("bool")}
+        self.outputs = {
+            'XShape': np.random.random(self.shape).astype("bool"),
+            'Out': self.inputs['X'].transpose(self.axis)
+        }
+
+
+class TestTransposeOpBool7D(TestTransposeOpBool):
+    def initTestCase(self):
+        self.shape = (2, 3, 2, 3, 2, 4, 3)
+        self.axis = (0, 1, 3, 2, 4, 5, 6)
+        self.inputs = {'X': np.random.random(self.shape).astype("bool")}
+        self.outputs = {
+            'XShape': np.random.random(self.shape).astype("bool"),
+            'Out': self.inputs['X'].transpose(self.axis)
+        }
+
+
+class TestTransposeOpBool8D(TestTransposeOpBool):
+    def initTestCase(self):
+        self.shape = (2, 3, 2, 3, 2, 4, 3, 3)
+        self.axis = (6, 1, 3, 5, 0, 2, 4, 7)
+        self.inputs = {'X': np.random.random(self.shape).astype("bool")}
+        self.outputs = {
+            'XShape': np.random.random(self.shape).astype("bool"),
+            'Out': self.inputs['X'].transpose(self.axis)
+        }
+
+
 class TestTransposeOpError(unittest.TestCase):
     def test_errors(self):
         paddle.enable_static()
@@ -126,9 +219,9 @@ class TestTransposeOpError(unittest.TestCase):
             self.assertRaises(TypeError, test_x_Variable_check)
 
             def test_x_dtype_check():
-                # the Input(x)'s dtype must be one of [float16, float32, float64, int32, int64]
+                # the Input(x)'s dtype must be one of [bool, float16, float32, float64, int32, int64]
                 x1 = fluid.layers.data(
-                    name='x1', shape=[10, 5, 3], dtype='bool')
+                    name='x1', shape=[10, 5, 3], dtype='int8')
                 fluid.layers.transpose(x1, perm=[1, 0, 2])
 
             self.assertRaises(TypeError, test_x_dtype_check)