How could I get the pool_size and pool_stride information from built graph_json?

[WeberChen]

Hi all,
I have run the test example in test_pass_partition_graph.py.
It's OK to export the graph_jason, lib.so and the parameters.
However, when I try to insert the nn.maxpool2d operator, the information of pool_size and pool_stride is missing in graph_json file.
Could someone tell me how to get the above information in graph_json file?
What files should I modify?
Thank you.

---

The following code is the inserted nn.maxpool2d in test_dnnl_fuse() in test_pass_partition_graph.py.
def get_net(include_bn=True, include_sigmoid=False):
data = relay.var("data", relay.TensorType((1, 3, 224, 224), "float32"))
block1 = get_blocks("block1_", data, 3, 8, include_bn, include_sigmoid)
block2 = get_blocks("block2_", block1, 8, 8, False, include_sigmoid)
block3 = relay.nn.avg_pool2d(block2, pool_size=(2, 2), strides=(2, 2), padding=(0, 0), layout='NCHW', ceil_mode=False, count_include_pad=False)
return relay.Function(relay.analysis.free_vars(block3), block3)

The following code is the part of graph_json about the maxpool2d:
{
"op": "tvm_op",
"name": "fused_nn_avg_pool2d_1",
"attrs": {
"num_outputs": "1",
"num_inputs": "1",
"func_name": "fused_nn_avg_pool2d_1",
"flatten_data": "0"
},
"inputs": [
[
2,
0,
0
]
]
}

AND the picture is the graph_json and it can get the correct result.

[tqchen]

Thanks for asking the question. Please open threads on https://discuss.tvm.apache.org/ for related questions. The generated json already inlines the pooling configuration into the library so the pooling size configuration is no longer available

[WeberChen]

Hi @tqchen tqchen,
Thank you for your kindly reply.
It's pretty that I can not get the pool configuration from graph_json file.
However, because I want to combine TVM with the NVDLA through BYOC method, could you suggest some TVM trace code that liking the DLA to TVM?
Thanks a lot.