/*! Generating SPIR-V for image operations. */ use super::{ selection::{MergeTuple, Selection}, Block, BlockContext, Error, IdGenerator, Instruction, LocalType, LookupType, }; 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, } /// 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. /// /// Ths 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, sample_id: Option, 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 { 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 // 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::Value { vector_size: Some(crate::VectorSize::Quad), kind: crate::ScalarKind::Float, width: 4, pointer_space: None, })) } _ => 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, sample_id: Option, 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.write_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, _sample_id: Option, 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<'w> BlockContext<'w> { /// 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, array_index: Option>, block: &mut Block, ) -> Result { 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_kind, size) = match *inner_ty { Ti::Scalar { kind, width: 4 } => (kind, Some(Vs::Bi)), Ti::Vector { kind, width: 4, size: Vs::Bi, } => (kind, Some(Vs::Tri)), Ti::Vector { kind, width: 4, size: Vs::Tri, } => (kind, Some(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_i32_id = self.cached[array_index]; let reconciled_array_index_id = if component_kind == crate::ScalarKind::Sint { array_index_i32_id } else { let component_type_id = self.get_type_id(LookupType::Local(LocalType::Value { vector_size: None, kind: component_kind, width: 4, pointer_space: None, })); let reconciled_id = self.gen_id(); block.body.push(Instruction::unary( spirv::Op::ConvertUToF, component_type_id, reconciled_id, array_index_i32_id, )); reconciled_id }; // Find the SPIR-V type for the combined coordinates/index vector. let type_id = self.get_type_id(LookupType::Local(LocalType::Value { vector_size: size, kind: component_kind, width: 4, pointer_space: None, })); // 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, }) } fn get_image_id(&mut self, expr_handle: Handle) -> Word { let id = match self.ir_function.expressions[expr_handle] { crate::Expression::GlobalVariable(handle) => { self.writer.global_variables[handle.index()].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 { 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 { 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, 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, sample_id: Option, block: &mut Block, ) -> Result<(Word, Option, Option), 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::Value { vector_size: None, kind: crate::ScalarKind::Sint, width: 4, pointer_space: None, })); // 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( &mut self, image_id: Word, coordinates: ImageCoordinates, level_id: Option, sample_id: Option, block: &mut Block, access: &A, ) -> Result { 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::Value { vector_size: None, kind: crate::ScalarKind::Sint, width: 4, pointer_space: None, })); 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_bool_type_id = self.get_type_id(LookupType::Local(LocalType::Value { vector_size: coordinates.size, kind: crate::ScalarKind::Bool, width: 1, pointer_space: None, })); 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, coordinate: Handle, array_index: Option>, level: Option>, sample: Option>, block: &mut Block, ) -> Result { let image_id = self.get_image_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 { 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, sampler: Handle, gather: Option, coordinate: Handle, array_index: Option>, offset: Option>, level: crate::SampleLevel, depth_ref: Option>, block: &mut Block, ) -> Result { use super::instructions::SampleLod; // image let image_id = self.get_image_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`, 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::Value { vector_size: Some(crate::VectorSize::Quad), kind: crate::ScalarKind::Float, width: 4, pointer_space: None, })) } 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_image_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::ScalarValue::Float(0.0), 4); 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 lod_id = self.cached[lod_handle]; 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.index()]; 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, query: crate::ImageQuery, block: &mut Block, ) -> Result { use crate::{ImageClass as Ic, ImageDimension as Id, ImageQuery as Iq}; let image_id = self.get_image_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 extended_size_type_id = { let array_coords = if arrayed { 1 } else { 0 }; let vector_size = match dim_coords + array_coords { 2 => Some(crate::VectorSize::Bi), 3 => Some(crate::VectorSize::Tri), 4 => Some(crate::VectorSize::Quad), _ => None, }; self.get_type_id(LookupType::Local(LocalType::Value { vector_size, kind: crate::ScalarKind::Sint, width: 4, pointer_space: None, })) }; 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 id = self.gen_id(); block.body.push(Instruction::image_query( spirv::Op::ImageQueryLevels, result_type_id, id, image_id, )); 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::Value { vector_size: Some(vec_size), kind: crate::ScalarKind::Sint, width: 4, pointer_space: None, })); 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 id = self.gen_id(); block.body.push(Instruction::composite_extract( result_type_id, id, id_extended, &[vec_size as u32 - 1], )); id } Iq::NumSamples => { let id = self.gen_id(); block.body.push(Instruction::image_query( spirv::Op::ImageQuerySamples, result_type_id, id, image_id, )); id } }; Ok(id) } pub(super) fn write_image_store( &mut self, image: Handle, coordinate: Handle, array_index: Option>, value: Handle, block: &mut Block, ) -> Result<(), Error> { let image_id = self.get_image_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.writer.bounds_check_policies.image { crate::proc::BoundsCheckPolicy::Restrict => { let (coords, _, _) = self.write_restricted_coordinates(image_id, coordinates, None, None, block)?; write.generate(&mut self.writer.id_gen, coords, None, None, block); } crate::proc::BoundsCheckPolicy::ReadZeroSkipWrite => { self.write_conditional_image_access( image_id, coordinates, None, None, block, &write, )?; } crate::proc::BoundsCheckPolicy::Unchecked => { write.generate( &mut self.writer.id_gen, coordinates.value_id, None, None, block, ); } } Ok(()) } }