jikechao opened a new issue, #14718:
URL: https://github.com/apache/tvm/issues/14718
### Steps to reproduce
```
import tvm
import tvm.relay as relay
import numpy as np
from tensorflow import keras
from tensorflow.keras import layers, models
input_shape = (2, 3, 4)
input_data = np.random.random(input_shape)
x = layers.Input(shape=input_shape[1:], dtype='float32')
layer = keras.layers.BatchNormalization()
layer.set_weights(layer.get_weights())
y = layer(x)
model = models.Model(x, y)
print(model.summary())
shape_dict = {'input_1': input_shape}
mod, params = relay.frontend.from_keras(model, shape_dict)
with tvm.transform.PassContext(opt_level=3):
model = relay.build_module.create_executor("graph", mod, tvm.cpu(0),
'llvm', params).evaluate()
```
### StackTrace
```
The Relay type checker is unable to show the following types match:
Tensor[(3), float32]
Tensor[(4), float32]
In particular:
dimension 0 conflicts: 3 does not match 4.
The Relay type checker is unable to show the following types match.
In particular `Tensor[(4), float32]` does not match `Tensor[(3), float32]`
The Relay type checker is unable to show the following types match:
Tensor[(3), float32]
Tensor[(4), float32]
In particular:
dimension 0 conflicts: 3 does not match 4.
The Relay type checker is unable to show the following types match.
In particular `Tensor[(4), float32]` does not match `Tensor[(3), float32]`
The Relay type checker is unable to show the following types match:
Tensor[(3), float32]
Tensor[(4), float32]
In particular:
dimension 0 conflicts: 3 does not match 4.
The Relay type checker is unable to show the following types match.
In particular `Tensor[(4), float32]` does not match `Tensor[(3), float32]`
The Relay type checker is unable to show the following types match:
Tensor[(3), float32]
Tensor[(4), float32]
In particular:
dimension 0 conflicts: 3 does not match 4.
The Relay type checker is unable to show the following types match.
In particular `Tensor[(4), float32]` does not match `Tensor[(3), float32]`
Traceback (most recent call last):
File "test.py", line 23, in <module>
model = relay.build_module.create_executor("graph", mod, tvm.cpu(0),
'llvm', params).evaluate()
File
"/workplace/software/tvm/tvm/python/tvm/relay/backend/interpreter.py", line
171, in evaluate
return self._make_executor()
File "/workplace/software/tvm/tvm/python/tvm/relay/build_module.py", line
513, in _make_executor
self.mod = InferType()(self.mod)
File "/workplace/software/tvm/tvm/python/tvm/ir/transform.py", line 160,
in __call__
return _ffi_transform_api.RunPass(self, mod)
File "/workplace/software/tvm/tvm/python/tvm/_ffi/_ctypes/packed_func.py",
line 237, in __call__
raise get_last_ffi_error()
tvm.error.DiagnosticError: Traceback (most recent call last):
7: TVMFuncCall
6:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule
(tvm::transform::Pass,
tvm::IRModule)>::AssignTypedLambda<tvm::transform::$_6>(tvm::transform::$_6,
std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char>
>)::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}>
>::Call(tvm::runtime::PackedFuncObj const*, tvm::runtime::TVMArgs,
tvm::runtime::TVMRetValue*)
5: tvm::transform::Pass::operator()(tvm::IRModule) const
4: tvm::transform::Pass::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
3: tvm::transform::ModulePassNode::operator()(tvm::IRModule,
tvm::transform::PassContext const&) const
2:
tvm::runtime::PackedFuncObj::Extractor<tvm::runtime::PackedFuncSubObj<tvm::runtime::TypedPackedFunc<tvm::IRModule
(tvm::IRModule,
tvm::transform::PassContext)>::AssignTypedLambda<tvm::relay::transform::InferType()::$_2>(tvm::relay::transform::InferType()::$_2)::{lambda(tvm::runtime::TVMArgs
const&, tvm::runtime::TVMRetValue*)#1}> >::Call(tvm::runtime::PackedFuncObj
const*, tvm::runtime::TVMArgs, tvm::runtime::TVMRetValue*)
1: tvm::DiagnosticContext::Render()
0: _ZN3tvm7runtime6detail
File "/workplace/software/tvm/tvm/src/ir/diagnostic.cc", line 131
DiagnosticError: one or more error diagnostics were emitted, please check
diagnostic render for output.
```
### Triage
* flow:relay
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