kparzysz-quic edited a comment on pull request #8509:
URL: https://github.com/apache/tvm/pull/8509#issuecomment-1050982328
The first failing testcase is resnet50:
This is the script that reproduces the crash is:
```
import coremltools
import onnx
import onnxmltools
import tvm
import tvm.contrib.hexagon
from tvm import relay
from tvm.relay.transform import InferType, ToMixedPrecision
dtype_dict = {"data": "float32"}
shape_dict = {"data": [1,3,224,224]}
#input name and path for your caffe model
proto_file = './ResNet-50-deploy.prototxt'
input_caffe_path = './ResNet-50-model.caffemodel'
# Convert Caffe model to CoreML
coreml_model = coremltools.converters.caffe.convert((input_caffe_path,
proto_file))
# Convert the Core ML model into ONNX
onnx_model = onnxmltools.convert_coreml(coreml_model)
onnxmltools.utils.save_model(onnx_model, 'resnet-50.onnx')
mod, params = relay.frontend.from_onnx(onnx_model, shape_dict)
mod = InferType()(mod)
mod = ToMixedPrecision("float16")(mod)
target = tvm.target.hexagon("v68", link_params=True)
config = {"relay.FuseOps.link_params":0} # <-- doesn't do
anything
with tvm.transform.PassContext(opt_level=3, config=config):
lib = relay.build(mod, target, target_host=target, params=params,
mod_name="default")
```
At the bottom of the crash dump you should see
```
0: tvm::relay::tec::ScheduleBuilder::VisitExpr_(tvm::relay::ConstantNode
const*)::{lambda(tvm::runtime::Array<tvm::tir::Var, void>
const&)#1}::operator()(tvm::runtime::Array<tvm::tir::Var, void> const&) const
File "/w/src/dmlc/tvm/src/relay/backend/te_compiler_cache.cc", line 242
TVMError: float16 not handled
```
The target string is `hexagon -keys=hexagon -link-params=1
-mattr=+hvxv68,+hvx-length128b -mcpu=hexagonv68 -mtriple=hexagon`.
We don't yet have codegen for `AllocateConst` specific to Hexagon, but if
the LLVM codegen handles it, it will probably work for us as well. Right now
we use the link_params function, which contains all the constants in it, but is
called at runtime to supply them to the model.
Edit: This will crash with the upstream code as well, so if you have the
same resnet50 as we do,
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