gemini-code-assist[bot] commented on code in PR #19890:
URL: https://github.com/apache/tvm/pull/19890#discussion_r3476220758
##########
src/relax/op/tensor/qdq.cc:
##########
@@ -69,9 +69,9 @@ Type InferTypeQuantize(const Call& call, const BlockBuilder&
ctx) {
TensorType input_ty = GetInputTensorType(call, ctx)[0];
TensorType scale_ty = GetInputTensorType(call, ctx)[1];
TensorType zp_ty = GetInputTensorType(call, ctx)[2];
- PrimType input_dtype = input_ty->dtype;
- PrimType scale_dtype = scale_ty->dtype;
- PrimType zp_dtype = zp_ty->dtype;
+ PrimType input_dtype = input_ty->dtype.value();
+ PrimType scale_dtype = scale_ty->dtype.value();
+ PrimType zp_dtype = zp_ty->dtype.value();
Review Comment:
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.
```suggestion
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();
```
##########
src/relax/op/tensor/qdq.cc:
##########
@@ -171,9 +171,9 @@ Type InferTypeDequantize(const Call& call, const
BlockBuilder& ctx) {
TensorType input_ty = GetInputTensorType(call, ctx)[0];
TensorType scale_ty = GetInputTensorType(call, ctx)[1];
TensorType zp_ty = GetInputTensorType(call, ctx)[2];
- PrimType input_dtype = input_ty->dtype;
- PrimType scale_dtype = scale_ty->dtype;
- PrimType zp_dtype = zp_ty->dtype;
+ PrimType input_dtype = input_ty->dtype.value();
+ PrimType scale_dtype = scale_ty->dtype.value();
+ PrimType zp_dtype = zp_ty->dtype.value();
Review Comment:
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.
```c
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();
```
##########
src/relax/op/op_common.h:
##########
@@ -198,16 +198,15 @@ std::tuple<ArgTypes...> GetArgType(const Call& call,
const BlockBuilder& ctx) {
template <bool require_float_dtype, typename FType>
inline Type InferTypeUnary(const Call& call, const BlockBuilder& ctx, FType
f_compute_out_dtype) {
TensorType input_ty = GetUnaryInputTensorType(call, ctx);
- PrimType input_dtype = input_ty->dtype;
if (require_float_dtype && !input_ty->IsUnknownDtype() &&
- !input_dtype.MatchesCode(DLDataTypeCode::kDLFloat,
DLDataTypeCode::kDLBfloat)) {
+ !input_ty->dtype.value().MatchesCode(DLDataTypeCode::kDLFloat,
DLDataTypeCode::kDLBfloat)) {
TVM_FFI_VISIT_THROW(TypeError, call)
<< call->op
<< " requires the input tensor to have float dtype. However, the given
input dtype is "
<< input_ty->dtype;
Review Comment:
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`).
```suggestion
<< input_ty->dtype.value();
```
##########
src/relax/transform/to_mixed_precision.cc:
##########
@@ -315,7 +315,7 @@ class ToMixedPrecisionRewriter : public ExprMutator {
if (NTypeEqual()(to[0], NTypeFrom(expr))) return expr;
// We only rewrite the expr if the dtype is fp16 or fp32, dtypes such as
int32, float64 is not
// supported to be rewritten
- DLDataType tensor_dtype = tensor->dtype->dtype;
+ DLDataType tensor_dtype = tensor->dtype.value()->dtype;
Review Comment:
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.
```suggestion
if (tensor->IsUnknownDtype()) return expr;
DLDataType tensor_dtype = tensor->dtype.value()->dtype;
```
##########
src/relax/utils.cc:
##########
@@ -183,7 +183,7 @@ bool IsBoolType(const Type& ty, bool permit_unknown_rank,
bool permit_unknown_dt
int ndim;
if (const auto* tensor = ty.as<TensorTypeNode>()) {
- dtype = tensor->dtype->dtype;
+ dtype = tensor->dtype.value()->dtype;
ndim = tensor->ndim;
Review Comment:
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.
```c
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;
```
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