AlexanderSerov opened a new issue #7849:
URL: https://github.com/apache/tvm/issues/7849
We have a network which contained nms layer. I can build a module from this
using relay.build and run inference using
graph_runtime.GraphModule(lib["default"](ctx)) on host using python tvm
interface flawlessly. But inference stuck with an error during inference when
run inference of wasm file on node.js.
**Steps to reproduce:**
1) Compile wasm file using following code:
```python
target = "llvm -mtriple=wasm32-unknown-unknown-wasm -system-lib"
if not tvm.runtime.enabled(target):
raise RuntimeError("Target %s is not enbaled" % target)
mod, params = relay.frontend.from_mxnet(sym, shape=shape_dict,
arg_params=arg_params, aux_params=aux_params)
func = mod["main"]
func = relay.Function(func.params,
func.body, None,
func.type_params, func.attrs)
with tvm.transform.PassContext(opt_level=3):
graph_json, mod, params = relay.build(func, target=target, params=params)
```
2) Run wasm module using folowing node.js code:
```node
const path = require("path");
const fs = require("fs");
const assert = require("assert");
const tvmjs = require("./dist");
const basePath = "/tvm_master/web/tvm_master";
const wasmPath = tvmjs.wasmPath();
const EmccWASI = require(path.join(wasmPath, "tvmjs_runtime.wasi.js"));
const wasmSource = fs.readFileSync(path.join(basePath, "bld210.wasm"));
const graphJson =
fs.readFileSync(path.join(basePath,"builder210_relay.json"), "utf-8");
const paramsBinary =
fs.readFileSync(path.join(basePath,"builder210_relay.params"));
let tvm = new tvmjs.Instance(new WebAssembly.Module(wasmSource), new
EmccWASI());
// console.log(tvm.listGlobalFuncNames());
// console.log(tvm.getGlobalFunc('tvm.graph_runtime.create'));
ctx = tvm.cpu(0);
const syslib = tvm.systemLib();
// syslib.getFunction("fused_subtract_multiply_layout_transform");
const executor = tvm.createGraphExecutor(graphJson, syslib, ctx);
executor.loadParams(paramsBinary);
const inputData = tvm.empty([1, 3, 128, 128]);
const outputData = tvm.empty([1, 676, 16]);
const output = executor.getOutput(0);
executor.run();
ctx.sync();
function randomArray(length, max) {
return Array.apply(null, Array(length)).map(function () {
return Math.random() * max;
});
}
// inputData.copyFrom(randomArray(49152, 255));
inputData.copyFrom(Array(49152).fill(125));
executor.setInput("data", inputData);
executor.run();
outputData.copyFrom(output);
```
3) Get an error:
**Environment:**
TVM : main branch or v0.7
Environment: ubuntu 18.04, [tlcpack docker
image](https://hub.docker.com/u/tlcpack)
**Notes:**
- Only reproduced with wasm module. Not reproduced on host
- All operators resolved successfully during tvm.createGraphExecutor in
above node.js code. Means fused_vision_non_max_suppression successfully
resolved in syslib. As i can understand nms rely on additional operators, i.e
argsort_nms, which he can't resolve
- The error iccurs when executor.run(); , means runtime.
- Similar issues:
> - [Meet an error when deploy nms on
target](https://discuss.tvm.apache.org/t/meet-an-error-when-deploy-nms-on-target/5956)
> - [[VTA] A Workaround for Deploying Faster R-CNN on Target ext_dev(VTA and
ARM
CPU)](https://discuss.tvm.apache.org/t/vta-a-workaround-for-deploying-faster-r-cnn-on-target-ext-dev-vta-and-arm-cpu/6516)
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