Fix type parse error about AdaptiveMaxPool

[jikechao]

This PR is similar to the pr-14837

This pr fixed a type parse bug when the out_size attribute of the AdaptiveMaxPool2d or AdaptiveMaxPool3d contains None, which means has the same size as the input. But the op can't be parsed by Relay and throws an error message:
"Check failed: (!checked_type.defined()) is false: Expected Array[PrimExpr], but got Array[index 1: relay.Constant]"

The op introduction in the PyTorch documentation

Bug triggering Script

import torch
from tvm import relay

m = torch.nn.AdaptiveMaxPool3d((3, None, None),)   
input_data=[torch.randn([1, 1, 3, 5, 6], dtype=torch.float32)]
trace = torch.jit.trace(m, input_data)
input_shapes = [('input0', torch.Size([1, 1, 3, 5, 6]))]

mod, params = relay.frontend.from_pytorch(trace, input_shapes)

Traceback

Traceback (most recent call last):
  File "test.py", line 13, in <module>
    mod, params = relay.frontend.from_pytorch(trace, input_shapes)
  File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/pytorch.py", line 4970, in from_pytorch
    outputs = converter.convert_operators(operator_nodes, outputs, ret_name)
  File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/pytorch.py", line 4240, in convert_operators
    _get_input_types(op_node, outputs, default_dtype=self.default_dtype),
  File "/workplace/software/tvm/tvm/python/tvm/relay/frontend/pytorch.py", line 1127, in adaptive_max_pool
    return op(data, output_size=output_size), None
  File "/workplace/software/tvm/tvm/python/tvm/relay/op/nn/nn.py", line 3435, in adaptive_max_pool3d
    return _make.adaptive_max_pool3d(data, output_size, layout, out_layout)
  File "/workplace/software/tvm/tvm/python/tvm/_ffi/_ctypes/packed_func.py", line 238, in __call__
    raise get_last_ffi_error()
tvm._ffi.base.TVMError: Traceback (most recent call last):
  4: TVMFuncCall
  3: _ZN3tvm7runtime13Pac
  2: tvm::runtime::TypedPackedFunc<tvm::RelayExpr (tvm::RelayExpr, tvm::runtime::Array<tvm::PrimExpr, void>, tvm::runtime::String, tvm::runtime::String)>::AssignTypedLambda<tvm::RelayExpr (*)(tvm::RelayExpr, tvm::runtime::Array<tvm::PrimExpr, void>, tvm::runtime::String, tvm::runtime::String)>(tvm::RelayExpr (*)(tvm::RelayExpr, tvm::runtime::Array<tvm::PrimExpr, void>, tvm::runtime::String, tvm::runtime::String), std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*) const
  1: tvm::runtime::TVMMovableArgValueWithContext_::operator tvm::runtime::Array<tvm::PrimExpr, void><tvm::runtime::Array<tvm::PrimExpr, void> >() const
  0: _ZN3tvm7runtime6detail
  6: TVMFuncCall
  5: _ZN3tvm7runtime13Pac
  4: tvm::runtime::TypedPackedFunc<tvm::RelayExpr (tvm::RelayExpr, tvm::runtime::Array<tvm::PrimExpr, void>, tvm::runtime::String, tvm::runtime::String)>::AssignTypedLambda<tvm::RelayExpr (*)(tvm::RelayExpr, tvm::runtime::Array<tvm::PrimExpr, void>, tvm::runtime::String, tvm::runtime::String)>(tvm::RelayExpr (*)(tvm::RelayExpr, tvm::runtime::Array<tvm::PrimExpr, void>, tvm::runtime::String, tvm::runtime::String), std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*) const
  3: tvm::runtime::TVMMovableArgValueWithContext_::operator tvm::runtime::Array<tvm::PrimExpr, void><tvm::runtime::Array<tvm::PrimExpr, void> >() const
  2: tvm::runtime::TVMMovableArgValue_::operator tvm::runtime::Array<tvm::PrimExpr, void><tvm::runtime::Array<tvm::PrimExpr, void>, void>() const
  1: tvm::runtime::Array<tvm::PrimExpr, void> tvm::runtime::TVMPODValue_::AsObjectRef<tvm::runtime::Array<tvm::PrimExpr, void> >() const
  0: _ZN3tvm7runtime6detail
  File "/workplace/software/tvm/tvm/include/tvm/runtime/packed_func.h", line 777
TVMError: In function relay.op.nn._make.adaptive_max_pool3d(0: RelayExpr, 1: Array<PrimExpr>, 2: runtime.String, 3: runtime.String) -> RelayExpr: error while converting argument 1: [07:33:53] /workplace/software/tvm/tvm/include/tvm/runtime/packed_func.h:1866: 
---------------------------------------------------------------
An error occurred during the execution of TVM.
For more information, please see: https://tvm.apache.org/docs/errors.html
---------------------------------------------------------------
  Check failed: (!checked_type.defined()) is false: Expected Array[PrimExpr], but got Array[index 1: relay.Constant]

cc @Hzfengsy @echuraev

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