MeioJane opened a new issue #5446:
URL: https://github.com/apache/incubator-tvm/issues/5446
Hi: I create a network using relay.build. Now I need to add the
nms(relya.vision.non_max_suppression) after the network, and then get a new
network, But I find only the nms operation cost about 30ms time. It is too
strange to cost so much time. I want to know if there is any wrong with nms
using or add the nms layer. There are part code as follows:
```
relay_mod, relay_params = relay.frontend.from_mxnet(
mx_sym,
shape=input_shapes,
dtype={'data': 'float32'},
arg_params=arg_params,
aux_params=aux_params
)
func = relay_mod["main"]
valid_count = relay.var('valid_count', relay.TensorType((1,), 'int32'),)
out = relay.vision.non_max_suppression(func.body, valid_count,
max_output_size=100, top_k=400, iou_threshold=0.45, return_indices=False)
func = relay.Function(func.params, out, None, func.type_params, func.attrs)
target = tvm.target.create('cuda')
with autotvm.apply_history_best(log_file):
print('Compile with relay ...')
with relay.build_config(opt_level=3):
graph, lib, params = relay.build(
func,
# relay_mod,
target,
params=relay_params
)
```
----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
For queries about this service, please contact Infrastructure at:
[email protected]
