Remove some data type conversion warnings

apache · Nov 10, 2020 · a649634 · a649634
1 parent 137663f
commit a649634
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Showing 3 changed files with 11 additions and 10 deletions.
diff --git a/src/operator/linalg_impl.h b/src/operator/linalg_impl.h
@@ -1572,7 +1572,7 @@ lapack_index_t linalg_getri_workspace_query<cpu, DType>(const Tensor<cpu, 2, DTy
   DType lwork(0); \
   MXNET_LAPACK_##func(MXNET_LAPACK_COL_MAJOR, A.size(0), A.dptr_, \
                       A.stride_, nullptr, &lwork, -1); \
-  return lwork; \
+  return static_cast<lapack_index_t>(lwork); \
 }
 
 LINALG_CPU_GETRI_WORKSPACE_QUERY(sgetri, float)

diff --git a/src/operator/numpy/linalg/np_lstsq-inl.h b/src/operator/numpy/linalg/np_lstsq-inl.h
@@ -168,7 +168,7 @@ linalg_gelsd_workspace_query<cpu, DType, IndexT>(const IndexT nrow, \
                                  &temp_work, -1, &temp_iwork); \
   CHECK_GE(info, 0) << "MXNET_LAPACK_" << #func << ": " \
     << "the " << -info << "-th argument had an illegal value"; \
-  *lwork = temp_work; \
+  *lwork = static_cast<IndexT>(temp_work); \
   *liwork = temp_iwork; \
   return; \
 }
@@ -260,10 +260,10 @@ inline bool GetOutputShapes(const mxnet::TShape& a_shape,
   }
   const int a_ndim = a_shape.ndim();
   const int b_ndim = b_shape.ndim();
-  const int a_nrow = a_shape[0];
-  const int a_ncol = a_shape[1];
-  const int b_nrow = b_shape[0];
-  const int b_nrhs = b_ndim == 2 ? b_shape[1] : 1;
+  const dim_t a_nrow = a_shape[0];
+  const dim_t a_ncol = a_shape[1];
+  const dim_t b_nrow = b_shape[0];
+  const dim_t b_nrhs = b_ndim == 2 ? b_shape[1] : 1;
   CHECK_EQ(a_ndim, 2) << a_ndim
     << "-dimensional array given. Array must be two-dimensional";
   CHECK(b_ndim == 1 || b_ndim == 2) << b_ndim
@@ -272,20 +272,21 @@ inline bool GetOutputShapes(const mxnet::TShape& a_shape,
     << "Incompatible dimensions of inputs";
   // x_shape
   if (b_ndim == 2) {
-    std::vector<int> x_shape_vec({a_ncol, b_nrhs});
+    std::vector<dim_t> x_shape_vec({a_ncol, b_nrhs});
     SHAPE_ASSIGN_CHECK(*out_attrs, 0, mxnet::TShape(x_shape_vec.begin(), x_shape_vec.end()));
   } else {
     SHAPE_ASSIGN_CHECK(*out_attrs, 0, mxnet::TShape(1, a_ncol));
   }
   // temp_residuals_shape
-  SHAPE_ASSIGN_CHECK(*out_attrs, 1, mxnet::TShape(1, static_cast<dim_t>(std::max(1, b_nrhs))));
+  SHAPE_ASSIGN_CHECK(*out_attrs, 1, mxnet::TShape(1, std::max(dim_t(1), b_nrhs)));
   // rank_shape
   SHAPE_ASSIGN_CHECK(*out_attrs, 2, mxnet::TShape(0, 0));
   // s_shape
   if (a_nrow == 0 || a_ncol == 0) {
     SHAPE_ASSIGN_CHECK(*out_attrs, 3, mxnet::TShape(1, 0));
   } else {
-    SHAPE_ASSIGN_CHECK(*out_attrs, 3, mxnet::TShape(1, std::max(1, std::min(a_nrow, a_ncol))));
+    SHAPE_ASSIGN_CHECK(*out_attrs, 3, mxnet::TShape(1, std::max(dim_t(1),
+                                                                std::min(a_nrow, a_ncol))));
   }
   return shape_is_known(*out_attrs);
 }

diff --git a/src/operator/numpy/linalg/np_solve-inl.h b/src/operator/numpy/linalg/np_solve-inl.h
@@ -433,7 +433,7 @@ void LaOpBackwardSolve(const nnvm::NodeAttrs& attrs,
         0 == b_shape[ndim - 1] || 0 == b_shape[ndim - 2]) { return; }
 
     const Tensor<xpu, idim + 1, OType> A = a_tblob.FlatToKD<xpu, idim + 1, OType>(s);
-    int work_space_size = sizeof(OType) * a_shape.Size();  // for inverse(A)
+    size_t work_space_size = sizeof(OType) * a_shape.Size();  // for inverse(A)
     work_space_size += sizeof(OType) * a_shape.Size();  // for getri work space
     work_space_size += 2 * sizeof(OType) * b_shape.Size();  // for B and X
     work_space_size += sizeof(IndexT) * A.size(0) * N;  // for pivot work space