File "tf_tvm_interpreter.py", line 171, in run_test_person_detection
tvm_output = run_tvm_graph(tflite_model_buf, img_data, 'input')
File "tf_tvm_interpreter.py", line 63, in run_tvm_graph
graph, lib, params = relay.build(mod, target, params=params)
File "/home/siju/workspace/tvm/python/tvm/relay/build_module.py", line 251, in build
graph_json, mod, params = bld_mod.build(mod, target, target_host, params)
File "/home/siju/workspace/tvm/python/tvm/relay/build_module.py", line 120, in build
self._build(mod, target, target_host)
File "/home/siju/workspace/tvm/python/tvm/_ffi/_ctypes/packed_func.py", line 219, in __call__
raise get_last_ffi_error()
tvm._ffi.base.TVMError: Traceback (most recent call last):
[bt] (8) /home/siju/workspace/tvm/build/libtvm.so(tvm::relay::IndexedForwardGraph::Create(tvm::support::Arena*, tvm::RelayExpr const&)+0xfe) [0x7eff4c25f17e]
[bt] (7) /home/siju/workspace/tvm/build/libtvm.so(tvm::relay::ExprVisitor::VisitExpr(tvm::RelayExpr const&)+0x7b) [0x7eff4c38dd7b]
[bt] (6) /home/siju/workspace/tvm/build/libtvm.so(tvm::relay::ExprFunctor<void (tvm::RelayExpr const&)>::VisitExpr(tvm::RelayExpr const&)+0x92) [0x7eff4c17b242]
[bt] (5) /home/siju/workspace/tvm/build/libtvm.so(tvm::relay::IndexedForwardGraph::Creator::VisitExpr_(tvm::relay::FunctionNode const*)+0x2bf) [0x7eff4c265c6f]
[bt] (4) /home/siju/workspace/tvm/build/libtvm.so(tvm::relay::ExprVisitor::VisitExpr_(tvm::relay::FunctionNode const*)+0xe3) [0x7eff4c38a303]
[bt] (3) /home/siju/workspace/tvm/build/libtvm.so(tvm::relay::ExprVisitor::VisitExpr(tvm::RelayExpr const&)+0x7b) [0x7eff4c38dd7b]
[bt] (2) /home/siju/workspace/tvm/build/libtvm.so(tvm::relay::ExprFunctor<void (tvm::RelayExpr const&)>::VisitExpr(tvm::RelayExpr const&)+0x92) [0x7eff4c17b242]
[bt] (1) /home/siju/workspace/tvm/build/libtvm.so(tvm::relay::IndexedForwardGraph::Creator::VisitExpr_(tvm::relay::CallNode const*)+0x461) [0x7eff4c262fe1]
[bt] (0) /home/siju/workspace/tvm/build/libtvm.so(dmlc::LogMessageFatal::~LogMessageFatal()+0x7c) [0x7eff4bae5abc]
File "/home/siju/workspace/tvm/include/tvm/ir/op.h", line 574
TVMError: Check failed: idx < data_.size() && data_[idx].second != 0: Attribute TOpPattern has not been registered for Operator qnn.requantize
@anijain2305 Can you please help me with this issue? I want to keep opt_level=0 because the tflite conv weights are int8 and bias is int32, But most of tvm param weights are int16 and int32 after op fusion. So because of this the param size is high in tvm compared to tflite.
I want to load the model in arduino with limited RAM and flash memory. TFlite is able to run and for tvm im getting memory issues.