[Relax][Backend] Fix TVM crashes with default relax pipeline when opt_level=1: InternalError: Check failed: (slot->value_computed) is false

[cchung100m]

Hi Commiters,

This PR is trying to fix issues #17876. Any suggestions would be appreciated if you are available.

Root Cause

VMShapeLower crashed when processing ShapeExpr containing composite PrimExpr that weren't computed yet.

Solution

Modified VisitExpr_(const ShapeExprNode* op) in vm_shape_lower.cc to:

1. Mark uncomputed variables as ready for computation
2. Trigger EmitOutstandingPrimExprCompute() to resolve the dependency chain
3. Ensure all expressions are computed before calling MakeSymbolicShapeArg

Added test case: test_composite_shape_expression_fix() to prevent future occurrences.

symbolizing the composite PrimExpr in the pipeline: canonicalization

[tlopex]

Marking arbitrary tir::VarNode instances as value_computed = true in VisitExpr_ is incorrect. In VMShapeLower, only Relax ShapeVars (from function parameters/match_cast) or IntImm constants can be safely marked as computed, because only these have runtime values accessible to the VM.
I think correct way is to fix this earlier in the pipeline (shape inference/canonicalization) by symbolizing composite PrimExpr (introduce Relax ShapeVars) or simplifying them before VMShapeLower.

[cchung100m]

Hi @tlopex

Thanks for the suggestion.
Should we extend ComputePrimValue() to handle ShapeExpr nodes with compound PrimExpr?
https://github.com/apache/tvm/blob/main/src/relax/transform/compute_prim_value.cc#L65

[tlopex]

Well, ComputePrimValue is intended only for evaluating statically evaluable PrimExpr into IntImm (constant folding), so I think extending ComputePrimValue would not address the root issue.
The real problem is that VMShapeLower cannot consume composite PrimExpr directly. The correct solution here should be to canonicalize ShapeExpr earlier by introducing a Relax ShapeVar binding for any non-trivial PrimExpr.

Just like:

# 1. Compute the symbolic value first (Canonicalization)
s1 = R.prim_value(n + 1)

# 2. Pass the computed var to the shape (VMShapeLower is happy now)
lv = R.call_tir(cls.func, (x,), R.shape([s1]), dtype="float32")