When I auto-tune my own onnx model, it finished:
```
[Task 20/22] Current/Best: 3.86/ 14.62 GFLOPS | Progress: (5/5) | 4.90 s
Done.
[Task 21/22] Current/Best: 7.47/ 12.78 GFLOPS | Progress: (5/5) | 2.42 s
Done.
[Task 22/22] Current/Best: 2.07/ 2.07 GFLOPS | Progress: (5/5) | 2.55 s
Done.
Auto-tvm on
Compile...
```
But, build error occurs after going into `relay.build_config`
```
with autotvm.apply_history_best(log_file):
print("Compile...")
with relay.build_config(opt_level=3):
graph, lib, params = relay.build(
mod, target=target, params=params)
```
With the error log:
```
tvm._ffi.base.TVMError: Traceback (most recent call last):
[bt] (8) 9 libtvm.dylib 0x0000000110a576f0
tvm::transform::SequentialNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const + 992
[bt] (7) 8 libtvm.dylib 0x0000000110a57b03
tvm::transform::Pass::operator()(tvm::IRModule, tvm::transform::PassContext
const&) const + 179
[bt] (6) 7 libtvm.dylib 0x000000011123fee8
tvm::relay::transform::FunctionPassNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const + 1624
[bt] (5) 6 libtvm.dylib 0x0000000110a36e30
tvm::IRModuleNode::Add(tvm::GlobalVar const&, tvm::BaseFunc const&, bool) + 320
[bt] (4) 5 libtvm.dylib 0x0000000110a362c7
tvm::RunTypeCheck(tvm::IRModule const&, tvm::GlobalVar const&,
tvm::relay::Function) + 1431
[bt] (3) 4 libtvm.dylib 0x0000000111189535
tvm::relay::InferType(tvm::relay::Function const&, tvm::IRModule const&,
tvm::GlobalVar const&) + 565
[bt] (2) 3 libtvm.dylib 0x00000001111886d8
tvm::relay::TypeInferencer::Infer(tvm::RelayExpr) + 136
[bt] (1) 2 libtvm.dylib 0x0000000110a2a8db
tvm::ErrorReporter::RenderErrors(tvm::IRModule const&, bool) + 5499
[bt] (0) 1 libtvm.dylib 0x000000011091e899
dmlc::LogMessageFatal::~LogMessageFatal() + 57
[bt] (8) 9 libtvm.dylib 0x0000000110a362c7
tvm::RunTypeCheck(tvm::IRModule const&, tvm::GlobalVar const&,
tvm::relay::Function) + 1431
[bt] (7) 8 libtvm.dylib 0x0000000111189535
tvm::relay::InferType(tvm::relay::Function const&, tvm::IRModule const&,
tvm::GlobalVar const&) + 565
[bt] (6) 7 libtvm.dylib 0x00000001111886bc
tvm::relay::TypeInferencer::Infer(tvm::RelayExpr) + 108
[bt] (5) 6 libtvm.dylib 0x0000000111063548
tvm::relay::TypeSolver::Solve() + 1064
[bt] (4) 5 libtvm.dylib 0x0000000111063be5
tvm::TypedEnvFunc<bool (tvm::Array<tvm::Type, void> const&, int, tvm::Attrs
const&, tvm::TypeReporter const&)>::operator()(tvm::Array<tvm::Type, void>
const&, int, tvm::Attrs const&, tvm::TypeReporter const&) const + 325
[bt] (3) 4 libtvm.dylib 0x0000000110d7d83b
std::__1::__function::__func<void tvm::runtime::TypedPackedFunc<bool
(tvm::Array<tvm::Type, void> const&, int, tvm::Attrs const&, tvm::TypeReporter
const&)>::AssignTypedLambda<bool (*)(tvm::Array<tvm::Type, void> const&, int,
tvm::Attrs const&, tvm::TypeReporter const&)>(bool (*)(tvm::Array<tvm::Type,
void> const&, int, tvm::Attrs const&, tvm::TypeReporter
const&))::'lambda'(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*),
std::__1::allocator<void tvm::runtime::TypedPackedFunc<bool
(tvm::Array<tvm::Type, void> const&, int, tvm::Attrs const&, tvm::TypeReporter
const&)>::AssignTypedLambda<bool (*)(tvm::Array<tvm::Type, void> const&, int,
tvm::Attrs const&, tvm::TypeReporter const&)>(bool (*)(tvm::Array<tvm::Type,
void> const&, int, tvm::Attrs const&, tvm::TypeReporter
const&))::'lambda'(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)>,
void (tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*)>::operator()(tvm::runtime::TVMArgs&&,
tvm::runtime::TVMRetValue*&&) + 107
[bt] (2) 3 libtvm.dylib 0x0000000110d7d9c3 void
tvm::runtime::detail::unpack_call_dispatcher<bool, 0, 4, bool
(*)(tvm::Array<tvm::Type, void> const&, int, tvm::Attrs const&,
tvm::TypeReporter const&)>::run<tvm::runtime::TVMMovableArgValue_,
tvm::runtime::TVMMovableArgValue_, tvm::runtime::TVMMovableArgValue_,
tvm::runtime::TVMMovableArgValue_>(bool (* const&)(tvm::Array<tvm::Type, void>
const&, int, tvm::Attrs const&, tvm::TypeReporter const&),
tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*,
tvm::runtime::TVMMovableArgValue_&&, tvm::runtime::TVMMovableArgValue_&&,
tvm::runtime::TVMMovableArgValue_&&, tvm::runtime::TVMMovableArgValue_&&) + 323
[bt] (1) 2 libtvm.dylib 0x0000000110de508c bool
tvm::relay::Conv2DWinogradRel<tvm::relay::Conv2DWinogradAttrs>(tvm::Array<tvm::Type,
void> const&, int, tvm::Attrs const&, tvm::TypeReporter const&) + 1756
[bt] (0) 1 libtvm.dylib 0x000000011091e899
dmlc::LogMessageFatal::~LogMessageFatal() + 57
File "/Users/kindlehe/Project/tvm/tvm/src/ir/error.cc", line 133
TVMError:
Error(s) have occurred. The program has been annotated with them:
In `main`:
v0.0.4
fn (%input: Tensor[(1, 3, 112, 112), float32]) -> Tensor[(1, 2), float32] {
%0 = reshape(%input, newshape=[-1, 3, 112, 112]);
%1 = layout_transform(meta[relay.Constant][0], src_layout="OIHW",
dst_layout="OIHW2o");
%2 = nn.conv2d(%0, %1, strides=[2, 2], padding=[0, 0, 0, 0], kernel_size=[3,
3], kernel_layout="OIHW2o");
%3 = expand_dims(meta[relay.Constant][1], axis=1, num_newaxis=2);
%4 = expand_dims(%3, axis=0);
%5 = add(%2, %4);
%6 = nn.relu(%5);
%7 = nn.max_pool2d(%6, pool_size=[3, 3], strides=[2, 2], padding=[0, 0, 0,
0], ceil_mode=True);
%8 = layout_transform(meta[relay.Constant][2], src_layout="OIHW",
dst_layout="OIHW2o");
%9 = nn.conv2d(%7, %8, padding=[0, 0, 0, 0], kernel_size=[1, 1],
kernel_layout="OIHW2o");
%10 = expand_dims(meta[relay.Constant][3], axis=1, num_newaxis=2);
%11 = expand_dims(%10, axis=0);
%12 = add(%9, %11);
%13 = nn.relu(%12);
%14 = layout_transform(meta[relay.Constant][4], src_layout="OIHW",
dst_layout="OIHW8o");
%15 = nn.conv2d(%13, %14, padding=[0, 0, 0, 0], kernel_size=[1, 1],
kernel_layout="OIHW8o");
%16 = expand_dims(meta[relay.Constant][5], axis=1, num_newaxis=2);
%17 = expand_dims(%16, axis=0);
%18 = add(%15, %17);
%19 = nn.relu(%18);
%20 = nn.contrib_conv2d_winograd_weight_transform(meta[relay.Constant][6],
tile_size=4);
%21 = reshape(%20, newshape=[6, 6, 16, 4, 16]);
%22 = transpose(%21, axes=[0, 1, 2, 4, 3]);
%23 = nn.contrib_conv2d_winograd_without_weight_transform(%13, %22,
tile_size=4, padding=[1, 1, 1, 1], kernel_size=[3, 3]) an internal invariant
was violated while typechecking your program [14:45:38]
/Users/kindlehe/Project/tvm/tvm/src/relay/op/nn/convolution.h:489: Check
failed: param->kernel_size.defined() && param->channels.defined(): The kernel
size and channels of a Conv must be set or inferred by previous pass
; ;
%24 = expand_dims(meta[relay.Constant][7], axis=1, num_newaxis=2);
```
main error line:
```
an internal invariant was violated while typechecking your program [14:45:38]
/Users/kindlehe/Project/tvm/tvm/src/relay/op/nn/convolution.h:489: Check
failed: param->kernel_size.defined() && param->channels.defined(): The kernel
size and channels of a Conv must be set or inferred by previous pass
; ;
```
---
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