[TOPI] Remove cpp upsampling and resize op (#4769)

* remove cpp upsampling

* remove cpp resize

topi/include/topi/detail/tensor_utils.h

@@ -25,6 +25,8 @@
 #define TOPI_DETAIL_TENSOR_UTILS_H_
 
 
+#include <tvm/te/operation.h>
+
 namespace topi {
 namespace detail {
 using namespace tvm;
@@ -50,7 +52,45 @@ inline bool is_empty_shape(const Array<PrimExpr>& x) {
   return is_empty;
 }
 
+/*!
+ * \brief Sample a point in a tensor using bilinear interpolation.
+ *
+ * \param input The input tensor.
+ * \param indices The index of the target point, which can be fractional
+ * \param max_y The maximum of y dimension
+ * \param max_x The maximum of x dimension
+ *
+ * \return The interpolated value in the given index.
+ */
+inline PrimExpr bilinear_sample_nchw(const Tensor& input, const Array<PrimExpr>& indices,
+                                 const PrimExpr max_y, const PrimExpr max_x) {
+  auto in_y = indices[2];
+  auto yf = tvm::floor(in_y);
+  auto yc = tvm::cast(DataType::Int(32), tvm::ceil(in_y));
+
+  auto y0 = tvm::cast(DataType::Int(32), tvm::floor(in_y));
+  auto y1 = tvm::if_then_else((yc > max_y), max_y, yc);
+  auto y_lerp = in_y - yf;
+
+  auto in_x = indices[3];
+  auto xf = tvm::floor(in_x);
+  auto xc = tvm::cast(DataType::Int(32), tvm::ceil(in_x));
+
+  auto x0 = tvm::cast(DataType::Int(32), tvm::floor(in_x));
+  auto x1 = tvm::if_then_else((xc > max_x), max_x, xc);
+  auto x_lerp = in_x - xf;
+
+  auto A = input(indices[0], indices[1], y0, x0);
+  auto B = input(indices[0], indices[1], y0, x1);
+  auto C = input(indices[0], indices[1], y1, x0);
+  auto D = input(indices[0], indices[1], y1, x1);
+
+  return A * ( 1 - x_lerp) * ( 1 - y_lerp) +
+         B * x_lerp * (1 - y_lerp) +
+         C * (1 - x_lerp) * y_lerp +
+         D * x_lerp * y_lerp;
+}
+
 }  // namespace detail
 }  // namespace topi
 #endif  // TOPI_DETAIL_TENSOR_UTILS_H_
-