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/*!
Generating SPIR-V for image operations.
*/
use super::{
selection::{MergeTuple, Selection},
Block, BlockContext, Error, IdGenerator, Instruction, LocalType, LookupType, NumericType,
};
use crate::arena::Handle;
use spirv::Word;
/// Information about a vector of coordinates.
///
/// The coordinate vectors expected by SPIR-V `OpImageRead` and `OpImageFetch`
/// supply the array index for arrayed images as an additional component at
/// the end, whereas Naga's `ImageLoad`, `ImageStore`, and `ImageSample` carry
/// the array index as a separate field.
///
/// In the process of generating code to compute the combined vector, we also
/// produce SPIR-V types and vector lengths that are useful elsewhere. This
/// struct gathers that information into one place, with standard names.
struct ImageCoordinates {
/// The SPIR-V id of the combined coordinate/index vector value.
///
/// Note: when indexing a non-arrayed 1D image, this will be a scalar.
value_id: Word,
/// The SPIR-V id of the type of `value`.
type_id: Word,
/// The number of components in `value`, if it is a vector, or `None` if it
/// is a scalar.
size: Option<crate::VectorSize>,
}
/// A trait for image access (load or store) code generators.
///
/// Types implementing this trait hold information about an `ImageStore` or
/// `ImageLoad` operation that is not affected by the bounds check policy. The
/// `generate` method emits code for the access, given the results of bounds
/// checking.
///
/// The [`image`] bounds checks policy affects access coordinates, level of
/// detail, and sample index, but never the image id, result type (if any), or
/// the specific SPIR-V instruction used. Types that implement this trait gather
/// together the latter category, so we don't have to plumb them through the
/// bounds-checking code.
///
/// [`image`]: crate::proc::BoundsCheckPolicies::index
trait Access {
/// The Rust type that represents SPIR-V values and types for this access.
///
/// For operations like loads, this is `Word`. For operations like stores,
/// this is `()`.
///
/// For `ReadZeroSkipWrite`, this will be the type of the selection
/// construct that performs the bounds checks, so it must implement
/// `MergeTuple`.
type Output: MergeTuple + Copy + Clone;
/// Write an image access to `block`.
///
/// Access the texel at `coordinates_id`. The optional `level_id` indicates
/// the level of detail, and `sample_id` is the index of the sample to
/// access in a multisampled texel.
///
/// This method assumes that `coordinates_id` has already had the image array
/// index, if any, folded in, as done by `write_image_coordinates`.
///
/// Return the value id produced by the instruction, if any.
///
/// Use `id_gen` to generate SPIR-V ids as necessary.
fn generate(
&self,
id_gen: &mut IdGenerator,
coordinates_id: Word,
level_id: Option<Word>,
sample_id: Option<Word>,
block: &mut Block,
) -> Self::Output;
/// Return the SPIR-V type of the value produced by the code written by
/// `generate`. If the access does not produce a value, `Self::Output`
/// should be `()`.
fn result_type(&self) -> Self::Output;
/// Construct the SPIR-V 'zero' value to be returned for an out-of-bounds
/// access under the `ReadZeroSkipWrite` policy. If the access does not
/// produce a value, `Self::Output` should be `()`.
fn out_of_bounds_value(&self, ctx: &mut BlockContext<'_>) -> Self::Output;
}
/// Texel access information for an [`ImageLoad`] expression.
///
/// [`ImageLoad`]: crate::Expression::ImageLoad
struct Load {
/// The specific opcode we'll use to perform the fetch. Storage images
/// require `OpImageRead`, while sampled images require `OpImageFetch`.
opcode: spirv::Op,
/// The type id produced by the actual image access instruction.
type_id: Word,
/// The id of the image being accessed.
image_id: Word,
}
impl Load {
fn from_image_expr(
ctx: &mut BlockContext<'_>,
image_id: Word,
image_class: crate::ImageClass,
result_type_id: Word,
) -> Result<Load, Error> {
let opcode = match image_class {
crate::ImageClass::Storage { .. } => spirv::Op::ImageRead,
crate::ImageClass::Depth { .. } | crate::ImageClass::Sampled { .. } => {
spirv::Op::ImageFetch
}
};
// `OpImageRead` and `OpImageFetch` instructions produce vec4<f32>
// values. Most of the time, we can just use `result_type_id` for
// this. The exception is that `Expression::ImageLoad` from a depth
// image produces a scalar `f32`, so in that case we need to find
// the right SPIR-V type for the access instruction here.
let type_id = match image_class {
crate::ImageClass::Depth { .. } => {
ctx.get_type_id(LookupType::Local(LocalType::Numeric(NumericType::Vector {
size: crate::VectorSize::Quad,
scalar: crate::Scalar::F32,
})))
}
_ => result_type_id,
};
Ok(Load {
opcode,
type_id,
image_id,
})
}
}
impl Access for Load {
type Output = Word;
/// Write an instruction to access a given texel of this image.
fn generate(
&self,
id_gen: &mut IdGenerator,
coordinates_id: Word,
level_id: Option<Word>,
sample_id: Option<Word>,
block: &mut Block,
) -> Word {
let texel_id = id_gen.next();
let mut instruction = Instruction::image_fetch_or_read(
self.opcode,
self.type_id,
texel_id,
self.image_id,
coordinates_id,
);
match (level_id, sample_id) {
(None, None) => {}
(Some(level_id), None) => {
instruction.add_operand(spirv::ImageOperands::LOD.bits());
instruction.add_operand(level_id);
}
(None, Some(sample_id)) => {
instruction.add_operand(spirv::ImageOperands::SAMPLE.bits());
instruction.add_operand(sample_id);
}
// There's no such thing as a multi-sampled mipmap.
(Some(_), Some(_)) => unreachable!(),
}
block.body.push(instruction);
texel_id
}
fn result_type(&self) -> Word {
self.type_id
}
fn out_of_bounds_value(&self, ctx: &mut BlockContext<'_>) -> Word {
ctx.writer.get_constant_null(self.type_id)
}
}
/// Texel access information for a [`Store`] statement.
///
/// [`Store`]: crate::Statement::Store
struct Store {
/// The id of the image being written to.
image_id: Word,
/// The value we're going to write to the texel.
value_id: Word,
}
impl Access for Store {
/// Stores don't generate any value.
type Output = ();
fn generate(
&self,
_id_gen: &mut IdGenerator,
coordinates_id: Word,
_level_id: Option<Word>,
_sample_id: Option<Word>,
block: &mut Block,
) {
block.body.push(Instruction::image_write(
self.image_id,
coordinates_id,
self.value_id,
));
}
/// Stores don't generate any value, so this just returns `()`.
fn result_type(&self) {}
/// Stores don't generate any value, so this just returns `()`.
fn out_of_bounds_value(&self, _ctx: &mut BlockContext<'_>) {}
}
impl BlockContext<'_> {
/// Extend image coordinates with an array index, if necessary.
///
/// Whereas [`Expression::ImageLoad`] and [`ImageSample`] treat the array
/// index as a separate operand from the coordinates, SPIR-V image access
/// instructions include the array index in the `coordinates` operand. This
/// function builds a SPIR-V coordinate vector from a Naga coordinate vector
/// and array index, if one is supplied, and returns a `ImageCoordinates`
/// struct describing what it built.
///
/// If `array_index` is `Some(expr)`, then this function constructs a new
/// vector that is `coordinates` with `array_index` concatenated onto the
/// end: a `vec2` becomes a `vec3`, a scalar becomes a `vec2`, and so on.
///
/// If `array_index` is `None`, then the return value uses `coordinates`
/// unchanged. Note that, when indexing a non-arrayed 1D image, this will be
/// a scalar value.
///
/// If needed, this function generates code to convert the array index,
/// always an integer scalar, to match the component type of `coordinates`.
/// Naga's `ImageLoad` and SPIR-V's `OpImageRead`, `OpImageFetch`, and
/// `OpImageWrite` all use integer coordinates, while Naga's `ImageSample`
/// and SPIR-V's `OpImageSample...` instructions all take floating-point
/// coordinate vectors.
///
/// [`Expression::ImageLoad`]: crate::Expression::ImageLoad
/// [`ImageSample`]: crate::Expression::ImageSample
fn write_image_coordinates(
&mut self,
coordinates: Handle<crate::Expression>,
array_index: Option<Handle<crate::Expression>>,
block: &mut Block,
) -> Result<ImageCoordinates, Error> {
use crate::TypeInner as Ti;
use crate::VectorSize as Vs;
let coordinates_id = self.cached[coordinates];
let ty = &self.fun_info[coordinates].ty;
let inner_ty = ty.inner_with(&self.ir_module.types);
// If there's no array index, the image coordinates are exactly the
// `coordinate` field of the `Expression::ImageLoad`. No work is needed.
let array_index = match array_index {
None => {
let value_id = coordinates_id;
let type_id = self.get_expression_type_id(ty);
let size = match *inner_ty {
Ti::Scalar { .. } => None,
Ti::Vector { size, .. } => Some(size),
_ => return Err(Error::Validation("coordinate type")),
};
return Ok(ImageCoordinates {
value_id,
type_id,
size,
});
}
Some(ix) => ix,
};
// Find the component type of `coordinates`, and figure out the size the
// combined coordinate vector will have.
let (component_scalar, size) = match *inner_ty {
Ti::Scalar(scalar @ crate::Scalar { width: 4, .. }) => (scalar, Vs::Bi),
Ti::Vector {
scalar: scalar @ crate::Scalar { width: 4, .. },
size: Vs::Bi,
} => (scalar, Vs::Tri),
Ti::Vector {
scalar: scalar @ crate::Scalar { width: 4, .. },
size: Vs::Tri,
} => (scalar, Vs::Quad),
Ti::Vector { size: Vs::Quad, .. } => {
return Err(Error::Validation("extending vec4 coordinate"));
}
ref other => {
log::error!("wrong coordinate type {:?}", other);
return Err(Error::Validation("coordinate type"));
}
};
// Convert the index to the coordinate component type, if necessary.
let array_index_id = self.cached[array_index];
let ty = &self.fun_info[array_index].ty;
let inner_ty = ty.inner_with(&self.ir_module.types);
let array_index_scalar = match *inner_ty {
Ti::Scalar(
scalar @ crate::Scalar {
kind: crate::ScalarKind::Sint | crate::ScalarKind::Uint,
width: 4,
},
) => scalar,
_ => unreachable!("we only allow i32 and u32"),
};
let cast = match (component_scalar.kind, array_index_scalar.kind) {
(crate::ScalarKind::Sint, crate::ScalarKind::Sint)
| (crate::ScalarKind::Uint, crate::ScalarKind::Uint) => None,
(crate::ScalarKind::Sint, crate::ScalarKind::Uint)
| (crate::ScalarKind::Uint, crate::ScalarKind::Sint) => Some(spirv::Op::Bitcast),
(crate::ScalarKind::Float, crate::ScalarKind::Sint) => Some(spirv::Op::ConvertSToF),
(crate::ScalarKind::Float, crate::ScalarKind::Uint) => Some(spirv::Op::ConvertUToF),
(crate::ScalarKind::Bool, _) => unreachable!("we don't allow bool for component"),
(_, crate::ScalarKind::Bool | crate::ScalarKind::Float) => {
unreachable!("we don't allow bool or float for array index")
}
(crate::ScalarKind::AbstractInt | crate::ScalarKind::AbstractFloat, _)
| (_, crate::ScalarKind::AbstractInt | crate::ScalarKind::AbstractFloat) => {
unreachable!("abstract types should never reach backends")
}
};
let reconciled_array_index_id = if let Some(cast) = cast {
let component_ty_id = self.get_type_id(LookupType::Local(LocalType::Numeric(
NumericType::Scalar(component_scalar),
)));
let reconciled_id = self.gen_id();
block.body.push(Instruction::unary(
cast,
component_ty_id,
reconciled_id,
array_index_id,
));
reconciled_id
} else {
array_index_id
};
// Find the SPIR-V type for the combined coordinates/index vector.
let type_id =
self.get_type_id(LookupType::Local(LocalType::Numeric(NumericType::Vector {
size,
scalar: component_scalar,
})));
// Schmear the coordinates and index together.
let value_id = self.gen_id();
block.body.push(Instruction::composite_construct(
type_id,
value_id,
&[coordinates_id, reconciled_array_index_id],
));
Ok(ImageCoordinates {
value_id,
type_id,
size: Some(size),
})
}
pub(super) fn get_handle_id(&mut self, expr_handle: Handle<crate::Expression>) -> Word {
let id = match self.ir_function.expressions[expr_handle] {
crate::Expression::GlobalVariable(handle) => {
self.writer.global_variables[handle].handle_id
}
crate::Expression::FunctionArgument(i) => {
self.function.parameters[i as usize].handle_id
}
crate::Expression::Access { .. } | crate::Expression::AccessIndex { .. } => {
self.cached[expr_handle]
}
ref other => unreachable!("Unexpected image expression {:?}", other),
};
if id == 0 {
unreachable!(
"Image expression {:?} doesn't have a handle ID",
expr_handle
);
}
id
}
/// Generate a vector or scalar 'one' for arithmetic on `coordinates`.
///
/// If `coordinates` is a scalar, return a scalar one. Otherwise, return
/// a vector of ones.
fn write_coordinate_one(&mut self, coordinates: &ImageCoordinates) -> Result<Word, Error> {
let one = self.get_scope_constant(1);
match coordinates.size {
None => Ok(one),
Some(vector_size) => {
let ones = [one; 4];
let id = self.gen_id();
Instruction::constant_composite(
coordinates.type_id,
id,
&ones[..vector_size as usize],
)
.to_words(&mut self.writer.logical_layout.declarations);
Ok(id)
}
}
}
/// Generate code to restrict `input` to fall between zero and one less than
/// `size_id`.
///
/// Both must be 32-bit scalar integer values, whose type is given by
/// `type_id`. The computed value is also of type `type_id`.
fn restrict_scalar(
&mut self,
type_id: Word,
input_id: Word,
size_id: Word,
block: &mut Block,
) -> Result<Word, Error> {
let i32_one_id = self.get_scope_constant(1);
// Subtract one from `size` to get the largest valid value.
let limit_id = self.gen_id();
block.body.push(Instruction::binary(
spirv::Op::ISub,
type_id,
limit_id,
size_id,
i32_one_id,
));
// Use an unsigned minimum, to handle both positive out-of-range values
// and negative values in a single instruction: negative values of
// `input_id` get treated as very large positive values.
let restricted_id = self.gen_id();
block.body.push(Instruction::ext_inst(
self.writer.gl450_ext_inst_id,
spirv::GLOp::UMin,
type_id,
restricted_id,
&[input_id, limit_id],
));
Ok(restricted_id)
}
/// Write instructions to query the size of an image.
///
/// This takes care of selecting the right instruction depending on whether
/// a level of detail parameter is present.
fn write_coordinate_bounds(
&mut self,
type_id: Word,
image_id: Word,
level_id: Option<Word>,
block: &mut Block,
) -> Word {
let coordinate_bounds_id = self.gen_id();
match level_id {
Some(level_id) => {
// A level of detail was provided, so fetch the image size for
// that level.
let mut inst = Instruction::image_query(
spirv::Op::ImageQuerySizeLod,
type_id,
coordinate_bounds_id,
image_id,
);
inst.add_operand(level_id);
block.body.push(inst);
}
_ => {
// No level of detail was given.
block.body.push(Instruction::image_query(
spirv::Op::ImageQuerySize,
type_id,
coordinate_bounds_id,
image_id,
));
}
}
coordinate_bounds_id
}
/// Write code to restrict coordinates for an image reference.
///
/// First, clamp the level of detail or sample index to fall within bounds.
/// Then, obtain the image size, possibly using the clamped level of detail.
/// Finally, use an unsigned minimum instruction to force all coordinates
/// into range.
///
/// Return a triple `(COORDS, LEVEL, SAMPLE)`, where `COORDS` is a coordinate
/// vector (including the array index, if any), `LEVEL` is an optional level
/// of detail, and `SAMPLE` is an optional sample index, all guaranteed to
/// be in-bounds for `image_id`.
///
/// The result is usually a vector, but it is a scalar when indexing
/// non-arrayed 1D images.
fn write_restricted_coordinates(
&mut self,
image_id: Word,
coordinates: ImageCoordinates,
level_id: Option<Word>,
sample_id: Option<Word>,
block: &mut Block,
) -> Result<(Word, Option<Word>, Option<Word>), Error> {
self.writer.require_any(
"the `Restrict` image bounds check policy",
&[spirv::Capability::ImageQuery],
)?;
let i32_type_id = self.get_type_id(LookupType::Local(LocalType::Numeric(
NumericType::Scalar(crate::Scalar::I32),
)));
// If `level` is `Some`, clamp it to fall within bounds. This must
// happen first, because we'll use it to query the image size for
// clamping the actual coordinates.
let level_id = level_id
.map(|level_id| {
// Find the number of mipmap levels in this image.
let num_levels_id = self.gen_id();
block.body.push(Instruction::image_query(
spirv::Op::ImageQueryLevels,
i32_type_id,
num_levels_id,
image_id,
));
self.restrict_scalar(i32_type_id, level_id, num_levels_id, block)
})
.transpose()?;
// If `sample_id` is `Some`, clamp it to fall within bounds.
let sample_id = sample_id
.map(|sample_id| {
// Find the number of samples per texel.
let num_samples_id = self.gen_id();
block.body.push(Instruction::image_query(
spirv::Op::ImageQuerySamples,
i32_type_id,
num_samples_id,
image_id,
));
self.restrict_scalar(i32_type_id, sample_id, num_samples_id, block)
})
.transpose()?;
// Obtain the image bounds, including the array element count.
let coordinate_bounds_id =
self.write_coordinate_bounds(coordinates.type_id, image_id, level_id, block);
// Compute maximum valid values from the bounds.
let ones = self.write_coordinate_one(&coordinates)?;
let coordinate_limit_id = self.gen_id();
block.body.push(Instruction::binary(
spirv::Op::ISub,
coordinates.type_id,
coordinate_limit_id,
coordinate_bounds_id,
ones,
));
// Restrict the coordinates to fall within those bounds.
//
// Use an unsigned minimum, to handle both positive out-of-range values
// and negative values in a single instruction: negative values of
// `coordinates` get treated as very large positive values.
let restricted_coordinates_id = self.gen_id();
block.body.push(Instruction::ext_inst(
self.writer.gl450_ext_inst_id,
spirv::GLOp::UMin,
coordinates.type_id,
restricted_coordinates_id,
&[coordinates.value_id, coordinate_limit_id],
));
Ok((restricted_coordinates_id, level_id, sample_id))
}
fn write_conditional_image_access<A: Access>(
&mut self,
image_id: Word,
coordinates: ImageCoordinates,
level_id: Option<Word>,
sample_id: Option<Word>,
block: &mut Block,
access: &A,
) -> Result<A::Output, Error> {
self.writer.require_any(
"the `ReadZeroSkipWrite` image bounds check policy",
&[spirv::Capability::ImageQuery],
)?;
let bool_type_id = self.writer.get_bool_type_id();
let i32_type_id = self.get_type_id(LookupType::Local(LocalType::Numeric(
NumericType::Scalar(crate::Scalar::I32),
)));
let null_id = access.out_of_bounds_value(self);
let mut selection = Selection::start(block, access.result_type());
// If `level_id` is `Some`, check whether it is within bounds. This must
// happen first, because we'll be supplying this as an argument when we
// query the image size.
if let Some(level_id) = level_id {
// Find the number of mipmap levels in this image.
let num_levels_id = self.gen_id();
selection.block().body.push(Instruction::image_query(
spirv::Op::ImageQueryLevels,
i32_type_id,
num_levels_id,
image_id,
));
let lod_cond_id = self.gen_id();
selection.block().body.push(Instruction::binary(
spirv::Op::ULessThan,
bool_type_id,
lod_cond_id,
level_id,
num_levels_id,
));
selection.if_true(self, lod_cond_id, null_id);
}
// If `sample_id` is `Some`, check whether it is in bounds.
if let Some(sample_id) = sample_id {
// Find the number of samples per texel.
let num_samples_id = self.gen_id();
selection.block().body.push(Instruction::image_query(
spirv::Op::ImageQuerySamples,
i32_type_id,
num_samples_id,
image_id,
));
let samples_cond_id = self.gen_id();
selection.block().body.push(Instruction::binary(
spirv::Op::ULessThan,
bool_type_id,
samples_cond_id,
sample_id,
num_samples_id,
));
selection.if_true(self, samples_cond_id, null_id);
}
// Obtain the image bounds, including any array element count.
let coordinate_bounds_id = self.write_coordinate_bounds(
coordinates.type_id,
image_id,
level_id,
selection.block(),
);
// Compare the coordinates against the bounds.
let coords_numeric_type = match coordinates.size {
Some(size) => NumericType::Vector {
size,
scalar: crate::Scalar::BOOL,
},
None => NumericType::Scalar(crate::Scalar::BOOL),
};
let coords_bool_type_id =
self.get_type_id(LookupType::Local(LocalType::Numeric(coords_numeric_type)));
let coords_conds_id = self.gen_id();
selection.block().body.push(Instruction::binary(
spirv::Op::ULessThan,
coords_bool_type_id,
coords_conds_id,
coordinates.value_id,
coordinate_bounds_id,
));
// If the comparison above was a vector comparison, then we need to
// check that all components of the comparison are true.
let coords_cond_id = if coords_bool_type_id != bool_type_id {
let id = self.gen_id();
selection.block().body.push(Instruction::relational(
spirv::Op::All,
bool_type_id,
id,
coords_conds_id,
));
id
} else {
coords_conds_id
};
selection.if_true(self, coords_cond_id, null_id);
// All conditions are met. We can carry out the access.
let texel_id = access.generate(
&mut self.writer.id_gen,
coordinates.value_id,
level_id,
sample_id,
selection.block(),
);
// This, then, is the value of the 'true' branch.
Ok(selection.finish(self, texel_id))
}
/// Generate code for an `ImageLoad` expression.
///
/// The arguments are the components of an `Expression::ImageLoad` variant.
#[allow(clippy::too_many_arguments)]
pub(super) fn write_image_load(
&mut self,
result_type_id: Word,
image: Handle<crate::Expression>,
coordinate: Handle<crate::Expression>,
array_index: Option<Handle<crate::Expression>>,
level: Option<Handle<crate::Expression>>,
sample: Option<Handle<crate::Expression>>,
block: &mut Block,
) -> Result<Word, Error> {
let image_id = self.get_handle_id(image);
let image_type = self.fun_info[image].ty.inner_with(&self.ir_module.types);
let image_class = match *image_type {
crate::TypeInner::Image { class, .. } => class,
_ => return Err(Error::Validation("image type")),
};
let access = Load::from_image_expr(self, image_id, image_class, result_type_id)?;
let coordinates = self.write_image_coordinates(coordinate, array_index, block)?;
let level_id = level.map(|expr| self.cached[expr]);
let sample_id = sample.map(|expr| self.cached[expr]);
// Perform the access, according to the bounds check policy.
let access_id = match self.writer.bounds_check_policies.image_load {
crate::proc::BoundsCheckPolicy::Restrict => {
let (coords, level_id, sample_id) = self.write_restricted_coordinates(
image_id,
coordinates,
level_id,
sample_id,
block,
)?;
access.generate(&mut self.writer.id_gen, coords, level_id, sample_id, block)
}
crate::proc::BoundsCheckPolicy::ReadZeroSkipWrite => self
.write_conditional_image_access(
image_id,
coordinates,
level_id,
sample_id,
block,
&access,
)?,
crate::proc::BoundsCheckPolicy::Unchecked => access.generate(
&mut self.writer.id_gen,
coordinates.value_id,
level_id,
sample_id,
block,
),
};
// For depth images, `ImageLoad` expressions produce a single f32,
// whereas the SPIR-V instructions always produce a vec4. So we may have
// to pull out the component we need.
let result_id = if result_type_id == access.result_type() {
// The instruction produced the type we expected. We can use
// its result as-is.
access_id
} else {
// For `ImageClass::Depth` images, SPIR-V gave us four components,
// but we only want the first one.
let component_id = self.gen_id();
block.body.push(Instruction::composite_extract(
result_type_id,
component_id,
access_id,
&[0],
));
component_id
};
Ok(result_id)
}
/// Generate code for an `ImageSample` expression.
///
/// The arguments are the components of an `Expression::ImageSample` variant.
#[allow(clippy::too_many_arguments)]
pub(super) fn write_image_sample(
&mut self,
result_type_id: Word,
image: Handle<crate::Expression>,
sampler: Handle<crate::Expression>,
gather: Option<crate::SwizzleComponent>,
coordinate: Handle<crate::Expression>,
array_index: Option<Handle<crate::Expression>>,
offset: Option<Handle<crate::Expression>>,
level: crate::SampleLevel,
depth_ref: Option<Handle<crate::Expression>>,
block: &mut Block,
) -> Result<Word, Error> {
use super::instructions::SampleLod;
// image
let image_id = self.get_handle_id(image);
let image_type = self.fun_info[image].ty.handle().unwrap();
// SPIR-V doesn't know about our `Depth` class, and it returns
// `vec4<f32>`, so we need to grab the first component out of it.
let needs_sub_access = match self.ir_module.types[image_type].inner {
crate::TypeInner::Image {
class: crate::ImageClass::Depth { .. },
..
} => depth_ref.is_none() && gather.is_none(),
_ => false,
};
let sample_result_type_id = if needs_sub_access {
self.get_type_id(LookupType::Local(LocalType::Numeric(NumericType::Vector {
size: crate::VectorSize::Quad,
scalar: crate::Scalar::F32,
})))
} else {
result_type_id
};
// OpTypeSampledImage
let image_type_id = self.get_type_id(LookupType::Handle(image_type));
let sampled_image_type_id =
self.get_type_id(LookupType::Local(LocalType::SampledImage { image_type_id }));
let sampler_id = self.get_handle_id(sampler);
let coordinates_id = self
.write_image_coordinates(coordinate, array_index, block)?
.value_id;
let sampled_image_id = self.gen_id();
block.body.push(Instruction::sampled_image(
sampled_image_type_id,
sampled_image_id,
image_id,
sampler_id,
));
let id = self.gen_id();
let depth_id = depth_ref.map(|handle| self.cached[handle]);
let mut mask = spirv::ImageOperands::empty();
mask.set(spirv::ImageOperands::CONST_OFFSET, offset.is_some());
let mut main_instruction = match (level, gather) {
(_, Some(component)) => {
let component_id = self.get_index_constant(component as u32);
let mut inst = Instruction::image_gather(
sample_result_type_id,
id,
sampled_image_id,
coordinates_id,
component_id,
depth_id,
);
if !mask.is_empty() {
inst.add_operand(mask.bits());
}
inst
}
(crate::SampleLevel::Zero, None) => {
let mut inst = Instruction::image_sample(
sample_result_type_id,
id,
SampleLod::Explicit,
sampled_image_id,
coordinates_id,
depth_id,
);
let zero_id = self.writer.get_constant_scalar(crate::Literal::F32(0.0));
mask |= spirv::ImageOperands::LOD;
inst.add_operand(mask.bits());
inst.add_operand(zero_id);
inst
}
(crate::SampleLevel::Auto, None) => {
let mut inst = Instruction::image_sample(
sample_result_type_id,
id,
SampleLod::Implicit,
sampled_image_id,
coordinates_id,
depth_id,
);
if !mask.is_empty() {
inst.add_operand(mask.bits());
}
inst
}
(crate::SampleLevel::Exact(lod_handle), None) => {
let mut inst = Instruction::image_sample(
sample_result_type_id,
id,
SampleLod::Explicit,
sampled_image_id,
coordinates_id,
depth_id,
);
let mut lod_id = self.cached[lod_handle];
// SPIR-V expects the LOD to be a float for all image classes.
// lod_id, however, will be an integer for depth images,
// therefore we must do a conversion.
if matches!(
self.ir_module.types[image_type].inner,
crate::TypeInner::Image {
class: crate::ImageClass::Depth { .. },
..
}
) {
let lod_f32_id = self.gen_id();
let f32_type_id = self.get_type_id(LookupType::Local(LocalType::Numeric(
NumericType::Scalar(crate::Scalar::F32),
)));
let convert_op = match *self.fun_info[lod_handle]
.ty
.inner_with(&self.ir_module.types)
{
crate::TypeInner::Scalar(crate::Scalar {
kind: crate::ScalarKind::Uint,
width: 4,
}) => spirv::Op::ConvertUToF,
crate::TypeInner::Scalar(crate::Scalar {
kind: crate::ScalarKind::Sint,
width: 4,
}) => spirv::Op::ConvertSToF,
_ => unreachable!(),
};
block.body.push(Instruction::unary(
convert_op,
f32_type_id,
lod_f32_id,
lod_id,
));
lod_id = lod_f32_id;
}
mask |= spirv::ImageOperands::LOD;
inst.add_operand(mask.bits());
inst.add_operand(lod_id);
inst
}
(crate::SampleLevel::Bias(bias_handle), None) => {
let mut inst = Instruction::image_sample(
sample_result_type_id,
id,
SampleLod::Implicit,
sampled_image_id,
coordinates_id,
depth_id,
);
let bias_id = self.cached[bias_handle];
mask |= spirv::ImageOperands::BIAS;
inst.add_operand(mask.bits());
inst.add_operand(bias_id);
inst
}
(crate::SampleLevel::Gradient { x, y }, None) => {
let mut inst = Instruction::image_sample(
sample_result_type_id,
id,
SampleLod::Explicit,
sampled_image_id,
coordinates_id,
depth_id,
);
let x_id = self.cached[x];
let y_id = self.cached[y];
mask |= spirv::ImageOperands::GRAD;
inst.add_operand(mask.bits());
inst.add_operand(x_id);
inst.add_operand(y_id);
inst
}
};
if let Some(offset_const) = offset {
let offset_id = self.writer.constant_ids[offset_const];
main_instruction.add_operand(offset_id);
}
block.body.push(main_instruction);
let id = if needs_sub_access {
let sub_id = self.gen_id();
block.body.push(Instruction::composite_extract(
result_type_id,
sub_id,
id,
&[0],
));
sub_id
} else {
id
};
Ok(id)
}
/// Generate code for an `ImageQuery` expression.
///
/// The arguments are the components of an `Expression::ImageQuery` variant.
pub(super) fn write_image_query(
&mut self,
result_type_id: Word,
image: Handle<crate::Expression>,
query: crate::ImageQuery,
block: &mut Block,
) -> Result<Word, Error> {
use crate::{ImageClass as Ic, ImageDimension as Id, ImageQuery as Iq};
let image_id = self.get_handle_id(image);
let image_type = self.fun_info[image].ty.handle().unwrap();
let (dim, arrayed, class) = match self.ir_module.types[image_type].inner {
crate::TypeInner::Image {
dim,
arrayed,
class,
} => (dim, arrayed, class),
_ => {
return Err(Error::Validation("image type"));
}
};
self.writer
.require_any("image queries", &[spirv::Capability::ImageQuery])?;
let id = match query {
Iq::Size { level } => {
let dim_coords = match dim {
Id::D1 => 1,
Id::D2 | Id::Cube => 2,
Id::D3 => 3,
};
let array_coords = usize::from(arrayed);
let vector_size = match dim_coords + array_coords {
2 => Some(crate::VectorSize::Bi),
3 => Some(crate::VectorSize::Tri),
4 => Some(crate::VectorSize::Quad),
_ => None,
};
let vector_numeric_type = match vector_size {
Some(size) => NumericType::Vector {
size,
scalar: crate::Scalar::U32,
},
None => NumericType::Scalar(crate::Scalar::U32),
};
let extended_size_type_id =
self.get_type_id(LookupType::Local(LocalType::Numeric(vector_numeric_type)));
let (query_op, level_id) = match class {
Ic::Sampled { multi: true, .. }
| Ic::Depth { multi: true }
| Ic::Storage { .. } => (spirv::Op::ImageQuerySize, None),
_ => {
let level_id = match level {
Some(expr) => self.cached[expr],
None => self.get_index_constant(0),
};
(spirv::Op::ImageQuerySizeLod, Some(level_id))
}
};
// The ID of the vector returned by SPIR-V, which contains the dimensions
// as well as the layer count.
let id_extended = self.gen_id();
let mut inst = Instruction::image_query(
query_op,
extended_size_type_id,
id_extended,
image_id,
);
if let Some(expr_id) = level_id {
inst.add_operand(expr_id);
}
block.body.push(inst);
if result_type_id != extended_size_type_id {
let id = self.gen_id();
let components = match dim {
// always pick the first component, and duplicate it for all 3 dimensions
Id::Cube => &[0u32, 0][..],
_ => &[0u32, 1, 2, 3][..dim_coords],
};
block.body.push(Instruction::vector_shuffle(
result_type_id,
id,
id_extended,
id_extended,
components,
));
id
} else {
id_extended
}
}
Iq::NumLevels => {
let query_id = self.gen_id();
block.body.push(Instruction::image_query(
spirv::Op::ImageQueryLevels,
result_type_id,
query_id,
image_id,
));
query_id
}
Iq::NumLayers => {
let vec_size = match dim {
Id::D1 => crate::VectorSize::Bi,
Id::D2 | Id::Cube => crate::VectorSize::Tri,
Id::D3 => crate::VectorSize::Quad,
};
let extended_size_type_id =
self.get_type_id(LookupType::Local(LocalType::Numeric(NumericType::Vector {
size: vec_size,
scalar: crate::Scalar::U32,
})));
let id_extended = self.gen_id();
let mut inst = Instruction::image_query(
spirv::Op::ImageQuerySizeLod,
extended_size_type_id,
id_extended,
image_id,
);
inst.add_operand(self.get_index_constant(0));
block.body.push(inst);
let extract_id = self.gen_id();
block.body.push(Instruction::composite_extract(
result_type_id,
extract_id,
id_extended,
&[vec_size as u32 - 1],
));
extract_id
}
Iq::NumSamples => {
let query_id = self.gen_id();
block.body.push(Instruction::image_query(
spirv::Op::ImageQuerySamples,
result_type_id,
query_id,
image_id,
));
query_id
}
};
Ok(id)
}
pub(super) fn write_image_store(
&mut self,
image: Handle<crate::Expression>,
coordinate: Handle<crate::Expression>,
array_index: Option<Handle<crate::Expression>>,
value: Handle<crate::Expression>,
block: &mut Block,
) -> Result<(), Error> {
let image_id = self.get_handle_id(image);
let coordinates = self.write_image_coordinates(coordinate, array_index, block)?;
let value_id = self.cached[value];
let write = Store { image_id, value_id };
match *self.fun_info[image].ty.inner_with(&self.ir_module.types) {
crate::TypeInner::Image {
class:
crate::ImageClass::Storage {
format: crate::StorageFormat::Bgra8Unorm,
..
},
..
} => self.writer.require_any(
"Bgra8Unorm storage write",
&[spirv::Capability::StorageImageWriteWithoutFormat],
)?,
_ => {}
}
write.generate(
&mut self.writer.id_gen,
coordinates.value_id,
None,
None,
block,
);
Ok(())
}
}