anijain2305 edited a comment on issue #5362:
URL: https://github.com/apache/incubator-tvm/pull/5362#issuecomment-617279905
@masahi @tqchen The MXNet quantized models has operators that can only work
with MKLDNN. Example is as follows. Note the `"op": "_sg_mkldnn_conv",`
~~~
{
"op": "_sg_mkldnn_conv",
"name": "quantized_sg_mkldnn_conv_bn_act_18",
"attrs": {
"max_calib_range": "2.660447",
"min_calib_range": "0.000000",
"quantized": "true",
"with_act": "true",
"with_bn": "true"
},
"inputs": [[110, 0, 0], [111, 0, 0], [112, 0, 0], [113, 0, 0], [114,
0, 1], [115, 0, 1], [110, 1, 0], [110, 2, 0]],
"subgraphs": [
{
"nodes": [
{
"op": "null",
"name": "sg_mkldnn_conv_bn_add_act_15_output0",
"inputs": []
},
{
"op": "null",
"name": "resnetv10_stage4_conv3_weight0",
"inputs": []
},
{
"op": "Convolution",
"name": "resnetv10_stage4_conv3_fwd",
"attrs": {
"dilate": "(1, 1)",
"kernel": "(3, 3)",
"layout": "NCHW",
"no_bias": "True",
"num_filter": "512",
"num_group": "1",
"pad": "(1, 1)",
"stride": "(1, 1)"
},
"inputs": [[0, 0, 0], [1, 0, 0]]
},
{
"op": "null",
"name": "resnetv10_stage4_batchnorm3_gamma0",
"inputs": []
},
{
"op": "null",
"name": "resnetv10_stage4_batchnorm3_beta0",
"inputs": []
},
{
"op": "null",
"name": "resnetv10_stage4_batchnorm3_running_mean0",
"inputs": []
},
{
"op": "null",
"name": "resnetv10_stage4_batchnorm3_running_var0",
"inputs": []
},
{
"op": "BatchNorm",
"name": "resnetv10_stage4_batchnorm3_fwd",
"attrs": {
"axis": "1",
"eps": "1e-05",
"fix_gamma": "False",
"momentum": "0.9",
"use_global_stats": "False"
},
"inputs": [[2, 0, 0], [3, 0, 0], [4, 0, 0], [5, 0, 0], [6, 0,
0]]
},
{
"op": "Activation",
"name": "resnetv10_stage4_relu1_fwd",
"attrs": {"act_type": "relu"},
"inputs": [[7, 0, 0]]
}
],
"arg_nodes": [0, 1, 3, 4, 5, 6],
"node_row_ptr": [0, 1, 2, 3, 4, 5, 6, 7, 10, 11],
"heads": [[8, 0, 0]]
}
]
},
~~~
Even if I quantize the model outside of this tutorial. I would still need
`mxnet-mkl` to read the MXNet quantized model in the Relay parser.
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