[Bug] LegalizeOps failed: InternalError: Check failed: (strides[i] < 0 ? (end_i <= begin_i) : (begin_i <= end_i)) is false

[coffezhou]

Expected behavior

TVM should build the model correctly.

Actual behavior

Traceback (most recent call last):
  File "/home/carla/Documents/test_tvm/0321/test_relax2.py", line 75, in <module>
    tvm_model = relax.transform.LegalizeOps()(tvm_model)
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/carla/Documents/tvm/python/tvm/ir/transform.py", line 238, in __call__
    return _ffi_transform_api.RunPass(self, mod)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "tvm/_ffi/_cython/./packed_func.pxi", line 339, in tvm._ffi._cy3.core.PackedFuncBase.__call__
  File "tvm/_ffi/_cython/./packed_func.pxi", line 270, in tvm._ffi._cy3.core.FuncCall
  File "tvm/_ffi/_cython/./packed_func.pxi", line 259, in tvm._ffi._cy3.core.FuncCall3
  File "tvm/_ffi/_cython/./base.pxi", line 185, in tvm._ffi._cy3.core.CHECK_CALL
  File "/home/carla/Documents/tvm/python/tvm/_ffi/base.py", line 468, in raise_last_ffi_error
    raise py_err
  File "/home/carla/Documents/tvm/src/relax/transform/legalize_ops.cc", line 398, in operator()
    mod = LegalizeMutator(mod, cmap, enable_warning).Transform();
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/carla/Documents/tvm/src/relax/transform/legalize_ops.cc", line 74, in tvm::relax::LegalizeMutator::Transform()
    auto updated_func = Downcast<Function>(this->VisitExpr(func));
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/carla/Documents/tvm/src/relax/transform/legalize_ops.cc", line 343, in tvm::relax::LegalizeMutator::VisitExpr_(tvm::relax::CallNode const*)
    Expr legalized = legalization_func(builder_, visited_call);
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "tvm/_ffi/_cython/./packed_func.pxi", line 56, in tvm._ffi._cy3.core.tvm_callback
  File "/home/carla/Documents/tvm/python/tvm/relax/transform/legalize_ops/index.py", line 62, in _strided_slice
    return bb.call_te(
           ^^^^^^^^^^^
  File "/home/carla/Documents/tvm/python/tvm/relax/block_builder.py", line 356, in call_te
    tir_func, call_args, output_sinfo, tir_vars = gen_call_tir_inputs(func, *args, **kwargs)
                                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/carla/Documents/tvm/python/tvm/relax/utils.py", line 354, in gen_call_tir_inputs
    te_out = func(*te_args, **te_kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/carla/Documents/tvm/python/tvm/topi/transform.py", line 228, in strided_slice
    return cpp.strided_slice(a, begin, end, strides, axes, slice_mode, assume_inbound)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "tvm/_ffi/_cython/./packed_func.pxi", line 339, in tvm._ffi._cy3.core.PackedFuncBase.__call__
  File "tvm/_ffi/_cython/./packed_func.pxi", line 284, in tvm._ffi._cy3.core.FuncCall
  File "tvm/_ffi/_cython/./base.pxi", line 185, in tvm._ffi._cy3.core.CHECK_CALL
  File "/home/carla/Documents/tvm/src/topi/transform.cc", line 195, in operator()
    *rv = strided_slice_with_axes(x, begin_static, end_static, strides_static, axes, slice_mode);
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/carla/Documents/tvm/include/tvm/topi/transform.h", line 899, in tvm::topi::strided_slice_with_axes(tvm::te::Tensor const&, tvm::runtime::Array<tvm::Integer, void> const&, tvm::runtime::Array<tvm::Integer, void> const&, tvm::runtime::Array<tvm::Integer, void> const&, tvm::runtime::Array<tvm::Integer, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)
    slice_mode, begin_expr);
^^^^^^
  File "/home/carla/Documents/tvm/include/tvm/topi/detail/strided_slice.h", line 140, in tvm::topi::detail::StridedSliceOutputShape(tvm::runtime::Array<tvm::PrimExpr, void> const&, std::vector<long, std::allocator<long> > const&, std::vector<long, std::allocator<long> > const&, std::vector<long, std::allocator<long> > const&, tvm::runtime::Array<tvm::Integer, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, tvm::runtime::Array<tvm::PrimExpr, void> const&, bool)
    ICHECK(strides[i] < 0 ? (end_i <= begin_i) : (begin_i <= end_i))
                ^^^^^^^^^^^^^^^^^^^^^^^^^^^
tvm.error.InternalError: Traceback (most recent call last):
  2: operator()
        at /home/carla/Documents/tvm/src/topi/transform.cc:195
  1: tvm::topi::strided_slice_with_axes(tvm::te::Tensor const&, tvm::runtime::Array<tvm::Integer, void> const&, tvm::runtime::Array<tvm::Integer, void> const&, tvm::runtime::Array<tvm::Integer, void> const&, tvm::runtime::Array<tvm::Integer, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)
        at /home/carla/Documents/tvm/include/tvm/topi/transform.h:899
  0: tvm::topi::detail::StridedSliceOutputShape(tvm::runtime::Array<tvm::PrimExpr, void> const&, std::vector<long, std::allocator<long> > const&, std::vector<long, std::allocator<long> > const&, std::vector<long, std::allocator<long> > const&, tvm::runtime::Array<tvm::Integer, void> const&, std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >, tvm::runtime::Array<tvm::PrimExpr, void> const&, bool)
        at /home/carla/Documents/tvm/include/tvm/topi/detail/strided_slice.h:140
  File "/home/carla/Documents/tvm/include/tvm/topi/detail/strided_slice.h", line 140
InternalError: Check failed: (strides[i] < 0 ? (end_i <= begin_i) : (begin_i <= end_i)) is false: : Input [Begin=-1, End=1] is invalid for axis=0

Environment

OS: Ubuntu 20.04 TVM: 0.20.dev0 (f6236ce41)

Steps to reproduce

This bug can be reproduced by the following code with the model in the attachment. For the model, it can be correctly ran by onnxruntime. However, an InternalError occurs when TVM builds this model.

from typing import Dict, List, Literal, Optional
import sys

import numpy as np
import onnx
import onnxruntime
from onnx import ModelProto, TensorProto, helper, mapping

import tvm
from tvm import relax
from tvm.relax.frontend.onnx import from_onnx

import argparse

bg = np.random.MT19937(0)
rg = np.random.Generator(bg)

def generate_random_inputs(
    model: ModelProto, inputs: Optional[Dict[str, np.ndarray]] = None
) -> Dict[str, np.ndarray]:
    input_values = {}
    # Iterate through model inputs and extract their shape.
    for i in model.graph.input:
        if inputs is not None and i.name in inputs and inputs[i.name] is not None:
            input_values[i.name] = inputs[i.name]
            continue
        shape = []
        for dim in i.type.tensor_type.shape.dim:
            shape.append(dim.dim_value)

        input_values[i.name] = generate_random_value(shape, i.type.tensor_type.elem_type)

    return input_values


def generate_random_value(shape, elem_type) -> np.ndarray:

    # Extract datatype for the input.
    if elem_type:
        dtype = str(helper.tensor_dtype_to_np_dtype(elem_type))
    else:
        dtype = "float32"

    # Generate random inputs for each input.
    if dtype == "bool":
        # random_value = np.random.choice(a=[False, True], size=shape)
        random_value = rg.choice(a=[False, True], size=shape)
    elif dtype.startswith("int"):
        # Keep non-zero values
        random_value = rg.integers(low=-63, high=63, size=shape).astype(dtype)
        random_value[random_value <= 0] -= 1
    else:
        random_value = rg.standard_normal(size=shape).astype(dtype)

    return random_value
    
model_path = "model.onnx"
model = onnx.load(model_path)

inputs: Optional[Dict[str, np.ndarray]] = None
inputs = generate_random_inputs(model, inputs)

try:
    ort_session = onnxruntime.InferenceSession(
        model.SerializeToString(), providers=["CPUExecutionProvider"]
    )
    ort_output = ort_session.run([], inputs)
except:
    print("This model cannot be executed by onnxruntime!")
    sys.exit(1)

    
tvm_model = from_onnx(model, keep_params_in_input=True)
tvm_model = relax.transform.DecomposeOpsForInference()(tvm_model)
tvm_model = relax.transform.LegalizeOps()(tvm_model)

tvm_model, params = relax.frontend.detach_params(tvm_model)

with tvm.transform.PassContext(opt_level=4):
    ex = relax.build(tvm_model, target="llvm")
    vm = relax.VirtualMachine(ex, tvm.cpu())

model.zip