Now, I want to use BYOC to run SSD-ResNet34 model and I met some problems.
About the "concatenate" operator, if it is a subgraph, the partitioned graph is:
def @ssdnn_0(%ssdnn_0_i0: (Tensor[(64, 4, 5776), float32], Tensor[(64, 4,
2166), float32], Tensor[(64, 4, 600), float32], Tensor[(64, 4, 150), float32],
Tensor[(64, 4, 36), float32], Tensor[(64, 4, 4), float32]), Compiler="ssdnn",
Inline=1, Primitive=1, global_symbol="ssdnn_0") -> Tensor[(64, 4, 8732),
float32] {
concatenate(%ssdnn_0_i0, axis=2) /* ty=Tensor[(64, 4, 8732), float32] */
}
After codegen, the cSource code is generated:
extern "C" int ssdnn_0_wrapper_(DLTensor* arg0,
DLTensor* arg1) {
ssdnn_0_(static_cast<float*>(arg0->data),
static_cast<float*>(arg1->data));
return 0;
}
extern "C" void ssdnn_0_(float* ssdnn_0_i0, float* out) {
...
ssdnn_concat(1, buf_0, 0, 2, 3, 64, 4, 8732, 1, ssdnn_0_i0);
std::memcpy(out, buf_0->data(), 4 * 2235392);
...
}
The parameter of "ssdnn_0_i0" is a tupleTypeNode,
But I need to know each field's data after codegen.
I wonder if there is any idear to get the each element of TupeTypeNode after
codegen, or after graph partition, not input the TupleTypeNode but give each
element of the TupleTypeNode?
@comaniac @manupa-arm
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