fix the bug in generated api code, tests are passed now

PaddlePaddle · Apr 4, 2022 · a7f3410 · a7f3410
1 parent 26f4662
commit a7f3410
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Showing 5 changed files with 45 additions and 12 deletions.
diff --git a/paddle/phi/api/lib/api_gen_utils.cc b/paddle/phi/api/lib/api_gen_utils.cc
@@ -144,7 +144,7 @@ phi::TensorBase* SetSparseKernelOutput(Tensor* out, TensorType type) {
           std::make_shared<phi::SparseCsrTensor>(phi::DenseTensor(),
                                                  phi::DenseTensor(),
                                                  phi::DenseTensor(),
-                                                 phi::DDim{-1});
+                                                 phi::DDim{-1, -1});
       out->set_impl(sparse_tensor);
       return sparse_tensor.get();
     } else {

diff --git a/paddle/phi/core/sparse_csr_tensor.cc b/paddle/phi/core/sparse_csr_tensor.cc
@@ -27,9 +27,11 @@ SparseCsrTensor::SparseCsrTensor() {
 inline void check_shape(const DDim& dims) {
   bool valid = dims.size() == 2 || dims.size() == 3;
 
-  PADDLE_ENFORCE(valid,
-                 phi::errors::InvalidArgument(
-                     "the SparseCsrTensor only support 2-D Tensor."));
+  PADDLE_ENFORCE(
+      valid,
+      phi::errors::InvalidArgument("the SparseCsrTensor only support 2-D or "
+                                   "3-D Tensor, but get %d-D Tensor",
+                                   dims.size()));
 }
 #define Check(non_zero_crows, non_zero_cols, non_zero_elements, dims)          \
   {                                                                            \

diff --git a/paddle/phi/kernels/sparse/activation_grad_kernel.cc b/paddle/phi/kernels/sparse/activation_grad_kernel.cc
@@ -17,5 +17,21 @@ limitations under the License. */
 #include "paddle/phi/kernels/activation_grad_kernel.h"
 #include "paddle/phi/kernels/sparse/utils.h"
 
-DEFINE_AND_REGISTER_SPARSE_UNARY_GRAD_KERNEL(sparse_relu_grad, ReluGradKernel)
-DEFINE_AND_REGISTER_SPARSE_UNARY_GRAD_KERNEL(sparse_sqrt_grad, SqrtGradKernel)
+DEFINE_AND_REGISTER_SPARSE_UNARY_GRAD_KERNEL(relu_grad, ReluGradKernel)
+DEFINE_AND_REGISTER_SPARSE_UNARY_GRAD_KERNEL(sqrt_grad, SqrtGradKernel)
+
+namespace phi {
+namespace sparse {
+
+template <typename T, typename Context>
+void SparseCooXXGrad(const Context& dev_ctx,
+                 const SparseCooTensor& x,
+                 SparseCooTensor* out) {
+}
+}  // namespace sparse
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    sparse_coo_xx_grad, CPU, ALL_LAYOUT, phi::sparse::SparseCooXXGrad, float, double) {
+  kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
+}
diff --git a/paddle/phi/kernels/sparse/activation_kernel.cc b/paddle/phi/kernels/sparse/activation_kernel.cc
@@ -16,5 +16,21 @@ limitations under the License. */
 
 #include "paddle/phi/kernels/sparse/utils.h"
 
-DEFINE_AND_REGISTER_SPARSE_UNARY_KERNEL(sparse_relu, ReluKernel)
-DEFINE_AND_REGISTER_SPARSE_UNARY_KERNEL(sparse_sqrt, SqrtKernel)
+DEFINE_AND_REGISTER_SPARSE_UNARY_KERNEL(relu, ReluKernel)
+DEFINE_AND_REGISTER_SPARSE_UNARY_KERNEL(sqrt, SqrtKernel)
+
+namespace phi {
+namespace sparse {
+
+template <typename T, typename Context>
+void SparseCooXX(const Context& dev_ctx,
+                 const SparseCooTensor& x,
+                 SparseCooTensor* out) {
+}
+}  // namespace sparse
+}  // namespace phi
+
+PD_REGISTER_KERNEL(
+    sparse_coo_xx, CPU, ALL_LAYOUT, phi::sparse::SparseCooXX, float, double) {
+  kernel->InputAt(0).SetDataLayout(phi::DataLayout::SPARSE_COO);
+}
diff --git a/python/paddle/fluid/tests/unittests/test_sparse_activation_op.py b/python/paddle/fluid/tests/unittests/test_sparse_activation_op.py
@@ -44,18 +44,17 @@ def test_sparse_coo_sqrt(self):
             sparse_act_out = _C_ops.final_state_sparse_coo_sqrt(sparse_coo_x)
             correct_result = [2, np.sqrt(2), 4]
             actual_result = sparse_act_out.non_zero_elements().numpy()
-            assert np.array_equal(correct_result, actual_result)
+            assert np.allclose(correct_result, actual_result)
 
     def test_sparse_csr_sqrt(self):
         with _test_eager_guard():
             x = [[0, 4, 0, 2], [0, 0, 0, 0], [0, 0, 16, 0]]
             dense_x = paddle.to_tensor(x, dtype='float32')
-            sparse_dim = 2
-            sparse_coo_x = dense_x.to_sparse_csr(sparse_dim)
+            sparse_coo_x = dense_x.to_sparse_csr()
             sparse_act_out = _C_ops.final_state_sparse_csr_sqrt(sparse_coo_x)
             correct_result = [2, np.sqrt(2), 4]
             actual_result = sparse_act_out.non_zero_elements().numpy()
-            assert np.array_equal(correct_result, actual_result)
+            assert np.allclose(correct_result, actual_result)
 
 
 if __name__ == "__main__":