fix bugs of paddle.linalg.lstsq (#44280)

paddle/fluid/operators/lstsq_op.cu

@@ -100,7 +100,7 @@ class LstsqCUDAKernel : public framework::OpKernel<T> {
                                      true,
                                      batch_count,
                                      m,
-                                     n,
+                                     nrhs,
                                      k,
                                      x_data,
                                      x_stride,
@@ -137,14 +137,17 @@ class LstsqCUDAKernel : public framework::OpKernel<T> {
 
       // Step 2, solve R^H Z = Y
       Tensor trans_r = dito.Transpose(new_x);
+      Tensor slice_r = dito.Slice(trans_r, {-2}, {0}, {min_mn});
+      Tensor res_r = dito.TrilTriu(slice_r, 0, false);
+
       phi::TriangularSolveKernel<T, Context>(
-          phi_dev_ctx, trans_r, new_y, true, true, false, solution);
+          phi_dev_ctx, res_r, new_y, true, true, false, solution);
 
       // Step 3, X <- Q Z
       BatchedOrgqr<DeviceContext, T>(dev_ctx,
                                      batch_count,
                                      n,
-                                     n,
+                                     m,
                                      min_mn,
                                      x_data,
                                      n,
@@ -183,8 +186,6 @@ void BatchedOrmqr<platform::CUDADeviceContext, float>(
   auto handle = dev_ctx.cusolver_dn_handle();
   PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::cusolverDnSormqr_bufferSize(
       handle, side, trans, m, n, k, a, lda, tau, other, ldc, &lwork));
-  auto workspace = memory::Alloc(dev_ctx, lwork * sizeof(float));
-  float* workspace_ptr = reinterpret_cast<float*>(workspace->ptr());
   auto info = memory::Alloc(dev_ctx, sizeof(int));
   int* info_d = reinterpret_cast<int*>(info->ptr());
 
@@ -192,6 +193,11 @@ void BatchedOrmqr<platform::CUDADeviceContext, float>(
     float* a_working_ptr = &a[i * a_stride];
     float* tau_working_ptr = &tau[i * tau_stride];
     float* other_working_ptr = &other[i * other_stride];
+
+    handle = dev_ctx.cusolver_dn_handle();
+    auto workspace = memory::Alloc(dev_ctx, lwork * sizeof(float));
+    float* workspace_ptr = reinterpret_cast<float*>(workspace->ptr());
+
     // compute ormgr
     PADDLE_ENFORCE_GPU_SUCCESS(
         platform::dynload::cusolverDnSormqr(handle,
@@ -249,8 +255,6 @@ void BatchedOrmqr<platform::CUDADeviceContext, double>(
   auto handle = dev_ctx.cusolver_dn_handle();
   PADDLE_ENFORCE_GPU_SUCCESS(platform::dynload::cusolverDnDormqr_bufferSize(
       handle, side, trans, m, n, k, a, lda, tau, other, ldc, &lwork));
-  auto workspace = memory::Alloc(dev_ctx, lwork * sizeof(double));
-  double* workspace_ptr = reinterpret_cast<double*>(workspace->ptr());
   auto info = memory::Alloc(dev_ctx, sizeof(int));
   int* info_d = reinterpret_cast<int*>(info->ptr());
 
@@ -258,6 +262,11 @@ void BatchedOrmqr<platform::CUDADeviceContext, double>(
     double* a_working_ptr = &a[i * a_stride];
     double* tau_working_ptr = &tau[i * tau_stride];
     double* other_working_ptr = &other[i * other_stride];
+
+    handle = dev_ctx.cusolver_dn_handle();
+    auto workspace = memory::Alloc(dev_ctx, lwork * sizeof(double));
+    double* workspace_ptr = reinterpret_cast<double*>(workspace->ptr());
+
     // compute ormgr
     PADDLE_ENFORCE_GPU_SUCCESS(
         platform::dynload::cusolverDnDormqr(handle,

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

@@ -175,6 +175,16 @@ class LinalgLstsqTestCase2(LinalgLstsqTestCase):
         self._input_shape_2 = (5, 8)
 
 
+class LinalgLstsqTestCase3(LinalgLstsqTestCase):
+
+    def init_config(self):
+        self.dtype = 'float64'
+        self.rcond = 1e-15
+        self.driver = "gels"
+        self._input_shape_1 = (10, 7, 3)
+        self._input_shape_2 = (10, 7, 6)
+
+
 class LinalgLstsqTestCaseRcond(LinalgLstsqTestCase):
 
     def init_config(self):
@@ -192,7 +202,17 @@ class LinalgLstsqTestCaseGelsFloat32(LinalgLstsqTestCase):
         self.rcond = None
         self.driver = "gels"
         self._input_shape_1 = (10, 5)
-        self._input_shape_2 = (10, 2)
+        self._input_shape_2 = (10, 8)
+
+
+class LinalgLstsqTestCaseGelsFloat64(LinalgLstsqTestCase):
+
+    def init_config(self):
+        self.dtype = 'float32'
+        self.rcond = None
+        self.driver = "gels"
+        self._input_shape_1 = (3, 2, 8)
+        self._input_shape_2 = (3, 2, 15)
 
 
 class LinalgLstsqTestCaseGelssFloat64(LinalgLstsqTestCase):
@@ -230,9 +250,9 @@ class LinalgLstsqTestCaseBatch2(LinalgLstsqTestCase):
     def init_config(self):
         self.dtype = 'float64'
         self.rcond = 1e-15
-        self.driver = "gelss"
+        self.driver = "gels"
         self._input_shape_1 = (10, 8, 6)
-        self._input_shape_2 = (10, 8, 2)
+        self._input_shape_2 = (10, 8, 10)
 
 
 class LinalgLstsqTestCaseLarge1(LinalgLstsqTestCase):