optima2005 commented on a change in pull request #4418: [RUNTIME] Add cudnn 
conv3d
URL: https://github.com/apache/incubator-tvm/pull/4418#discussion_r352125416
 
 

 ##########
 File path: src/runtime/contrib/cudnn/conv_forward.cc
 ##########
 @@ -287,6 +355,91 @@ TVM_REGISTER_GLOBAL("tvm.contrib.cudnn.conv2d.find_algo")
   }
 
   ret[0] = best_algo;
+}
+
+
+TVM_REGISTER_GLOBAL("tvm.contrib.cudnn.conv.forward")
+.set_body([](TVMArgs args, TVMRetValue *ret) {
+  int mode = args[0];
+  int format = args[1];
+  int algo = args[2];
+  int dims = args[3];
+
+  Array<Expr> pads =  args[4];
+  Array<Expr> strides =  args[5];
+  Array<Expr> dilations =  args[6];
+
+  std::vector<int> pad_v(dims), stride_v(dims), dilation_v(dims);
+
+  for (auto &pad : pads) {
+    int i = 0;
+    pad_v[i++] = pad.as<IntImm>()->value;
+  }
+  for (auto &stride : strides) {
+    int i = 0;
+    pad_v[i++] = strides.as<IntImm>()->value;
+  }
+  for (auto &dilation : dilations) {
+    int i = 0;
+    pad_v[i++] = dilations.as<IntImm>()->value;
+  }
+
+  DLTensor* x = args[7];
+  DLTensor* w = args[8];
+  DLTensor* y = args[9];
+  std::string conv_dtype = args[10];
+
+  ConvolutionForward(mode, format, algo, pad_v, stride_v, dilation_v,
+                     x, w, y, conv_dtype);
+});
+
+
+TVM_REGISTER_GLOBAL("tvm.contrib.cudnn.conv.output_shape")
+.set_body([](TVMArgs args, TVMRetValue *ret) {
+  int format = args[0];
+  int dims = args[1];
+  int* pad = static_cast<int*>(static_cast<void*>(args[2]));
+  int* stride = static_cast<int*>(static_cast<void*>(args[3]));
+  int* dilation = static_cast<int*>(static_cast<void*>(args[4]));
+  int* x_dim = static_cast<int*>(static_cast<void*>(args[5]));
+  int* w_dim = static_cast<int*>(static_cast<void*>(args[6]));
+  std::vector<int> pad_v(pad, pad + dims);
+  std::vector<int> stride_v(stride, stride + dims);
+  std::vector<int> dilation_v(dilation, dilation + dims);
+  std::vector<int> x_dim_v(x_dim, x_dim + dims + 2);
+  std::vector<int> w_dim_v(w_dim, w_dim + dims + 2);
+
 
 Review comment:
   Because most need handle the different tuple size, I am wondering whether we 
need keep them.

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