[Relax] Use optional dtype for absent Relax dtype fields

[tqchen]

This PR replaces Relax uses of void dtype sentinels for semantically absent dtypes with explicit optional/null representations.

Summary:

• Make unknown TensorType dtype optional instead of represented as void.
• Convert optional Relax dtype attrs to optional values and update inference paths to check presence directly.
• Represent R.memory.view(..., dtype=None) with R.null_value() at the expression boundary, and lower to a concrete runtime dtype when required.
• Reject R.memory.view(..., dtype=R.dtype("void")) in inference instead of treating the legacy void spelling as absence.
• Handle review feedback around unknown optional dtype propagation in utility, qdq, and mixed-precision paths.

[gemini-code-assist]

Code Review

This pull request refactors TVM Relax's TensorTypeNode to represent unknown data types using ffi::Optionaltvm::PrimType initialized to std::nullopt instead of an opaque DLDataType placeholder. This change is propagated across various operators, type inference helpers, and transformations. The code review identified several critical issues where calling .value() on the newly introduced dtype optionals could cause crashes when the data type is unknown, specifically in utils.cc, qdq.cc (quantize/dequantize), and to_mixed_precision.cc. Additionally, a minor improvement was suggested in op_common.h to print a cleaner concrete dtype in error messages.

Important

The consumer version of Gemini Code Assist on GitHub is being sunset. Starting June 18, 2026, new organization installations will be blocked, and all code review activity will officially cease on July 17, 2026.
For more details on the timeline and next steps, please review the Help Documentation.

[gemini-code-assist]

When permit_unknown_dtype is true and tensor->IsUnknownDtype() is true, calling tensor->dtype.value() will throw an exception or crash due to accessing an empty optional. We should safely handle the unknown dtype case when permit_unknown_dtype is enabled.

  if (const auto* tensor = ty.as<TensorTypeNode>()) {
    if (tensor->IsUnknownDtype()) {
      if (!permit_unknown_dtype) {
        return false;
      }
      dtype = DLDataType{kDLOpaqueHandle, 0, 0};
    } else {
      dtype = tensor->dtype.value()->dtype;
    }
    ndim = tensor->ndim;

[gemini-code-assist]

If any of the input tensors (input_ty, scale_ty, or zp_ty) has an unknown dtype, calling .value() directly on their dtype fields will crash. Since type inference can be run on expressions with unknown dtypes, we should check IsUnknownDtype() and return a TensorType with an unknown dtype instead of crashing.

Suggested change

	PrimType input_dtype = input_ty->dtype.value();
	PrimType scale_dtype = scale_ty->dtype.value();
	PrimType zp_dtype = zp_ty->dtype.value();
	if (input_ty->IsUnknownDtype() || scale_ty->IsUnknownDtype() || zp_ty->IsUnknownDtype()) {
	if (input_ty->shape.defined()) {
	return TensorType(input_ty->shape.value(), std::nullopt, input_ty->vdevice);
	} else {
	return TensorType(std::nullopt, input_ty->ndim, input_ty->vdevice);
	}
	}
	PrimType input_dtype = input_ty->dtype.value();
	PrimType scale_dtype = scale_ty->dtype.value();
	PrimType zp_dtype = zp_ty->dtype.value();

[gemini-code-assist]

If any of the input tensors (input_ty, scale_ty, or zp_ty) has an unknown dtype, calling .value() directly on their dtype fields will crash. Since type inference can be run on expressions with unknown dtypes, we should check IsUnknownDtype() and return a TensorType with an unknown dtype instead of crashing.

  if (input_ty->IsUnknownDtype() || scale_ty->IsUnknownDtype() || zp_ty->IsUnknownDtype()) {
    if (input_ty->shape.defined()) {
      return TensorType(input_ty->shape.value(), std::nullopt, input_ty->vdevice);
    } else {
      return TensorType(std::nullopt, input_ty->ndim, input_ty->vdevice);
    }
  }
  PrimType input_dtype = input_ty->dtype.value();
  PrimType scale_dtype = scale_ty->dtype.value();
  PrimType zp_dtype = zp_ty->dtype.value();

[gemini-code-assist]

If tensor->IsUnknownDtype() is true, calling tensor->dtype.value() will crash. We should check if the tensor has an unknown dtype and return the original expression early.

Suggested change

	DLDataType tensor_dtype = tensor->dtype.value()->dtype;
	if (tensor->IsUnknownDtype()) return expr;
	DLDataType tensor_dtype = tensor->dtype.value()->dtype;

[gemini-code-assist]

Since we have already verified that !input_ty->IsUnknownDtype(), we should print input_ty->dtype.value() instead of the optional wrapper input_ty->dtype to ensure the error message displays a clean concrete dtype (e.g., float32).

Suggested change

	<< input_ty->dtype;
	<< input_ty->dtype.value();