This PR adds handling of the numthreads attribute for compute shaders, as well as a general
infrastructure for returning attribute values from acceptAttributes, which may be needed in other
cases, e.g, unroll(x), or merely to know if some attribute without params was given.
A map of enum values from TAttributeType to TIntermAggregate nodes is built and returned. It
can be queried with operator[] on the map. In the future there may be a need to also handle
strings (e.g, for patchconstantfunc), and those can be easily added into the class if needed.
New test is in hlsl.numthreads.comp.
- add optional callback to handle mapping of uniform variables in linking phase
- if no resolver is provided, it uses the internal default resolver with all shifts and auto bind settings
Change-Id: Icfe38a9eabe8bfc8f8bb6d8150c06f7ed38bb762
This PR only changes a few lines of code, but is subtle.
In HLSL, comparison operators (<,>,<=,>=,==,!=) operate component-wise
when given a vector operand. If a whole vector equality or inequality is
desired, then all() or any() can be used on the resulting bool vector.
This PR enables this change. Existing shape conversion is used when
one of the two arguments is a vector and one is a scalar.
Some existing HLSL tests had assumed == and != meant vector-wise
instead of component-wise comparisons. These tests have been changed
to add an explicit any() or all() to the test source. This verifably
does not change the final SPIR-V binary relative to the old behavior
for == and !=. The AST does change for the (now explicit, formerly
implicit) any() and all(). Also, a few tests changes where they
previously had the return type wrong, e.g, from a vec < vec comparison
in hlsl.shapeConv.frag.
Promotion of comparison opcodes to vector forms
(EOpEqual->EOpVectorEqual) is handled in promoteBinary(), as is setting
the proper vector type of the result.
EOpVectorEqual and EOpVectorNotEqual are now accepted as either
aggregate or binary nodes, similar to how the other operators are
handled. Partial support already existed for this: it has been
fleshed out in the printing functions in intermOut.cpp.
There is an existing defect around shape conversion with 1-vectors, but
that is orthogonal to this PR and not addressed by it.
I happened upon numArgs while hunting for unused variables. I suspect
the intent was to apply it as shown in this patch. However, I am not a
compiler dude. Someone more appropriate should grok this change.
HLSL holds the compare value in a separate intrinsic arg, but the AST wants
a vector including the cmp val, except in the 4-dim coord case, where it
doesn't fit and is in fact a separate AST parameter. This is awkward but
necessary, given AST semantics. In the process, a new vector is constructed
for the combined result, but this vector was not being given the correct
TType, so was causing some downstream troubles.
Now it is. A similar defect existed in OpTextureBias, and has also been
fixed.
A need arose to use capabilities from TIntermediate during
node promotion. These methods have been moved from virtual
methods on the TIntermUnary and TIntermBinary nodes to methods
on TIntermediate, so it is easy for them construct new nodes
and so on.
This is done as a separate commit to verify that no test results
are changed as a result.
This fixes defects as follows:
1. handleLvalue could be called on a non-L-value, and it shouldn't be.
2. HLSL allows unary negation on non-bool values. TUnaryOperator::promote
can now promote other types (e.g, int, float) to bool for this op.
3. HLSL allows binary logical operations (&&, ||) on arbitrary types, similar
(2).
4. HLSL allows mod operation on arbitrary types, which will be promoted.
E.g, int % float -> float % float.
This PR sets the TQualifier layoutFormat according to the HLSL image type.
For instance:
RWTexture1D <float2> g_tTex1df2;
becomes ElfRg32f. Similar on Buffers, e.g, Buffer<float4> mybuffer;
The return type for image and buffer loads is now taken from the storage format.
Also, the qualifier for the return type is now (properly) a temp, not a global.
All the underpinnings are there; this just parses multiple array dimensions
and passes them through to the existing mechanisms.
Also, minor comment fixes, and add a new test for multi-dim arrays.
