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//! This file has been automatically generated by `objc2`'s `header-translator`.
//! DO NOT EDIT
use core::ffi::*;
use core::ptr::NonNull;
use objc2::__framework_prelude::*;
use objc2_foundation::*;
use crate::*;
extern_class!(
/// Description for a machine learning pipeline state.
///
/// See also [Apple's documentation](https://developer.apple.com/documentation/metal/mtl4machinelearningpipelinedescriptor?language=objc)
#[unsafe(super(MTL4PipelineDescriptor, NSObject))]
#[derive(Debug, PartialEq, Eq, Hash)]
#[cfg(feature = "MTL4PipelineState")]
pub struct MTL4MachineLearningPipelineDescriptor;
);
#[cfg(feature = "MTL4PipelineState")]
extern_conformance!(
unsafe impl NSCopying for MTL4MachineLearningPipelineDescriptor {}
);
#[cfg(feature = "MTL4PipelineState")]
unsafe impl CopyingHelper for MTL4MachineLearningPipelineDescriptor {
type Result = Self;
}
#[cfg(feature = "MTL4PipelineState")]
extern_conformance!(
unsafe impl NSObjectProtocol for MTL4MachineLearningPipelineDescriptor {}
);
#[cfg(feature = "MTL4PipelineState")]
impl MTL4MachineLearningPipelineDescriptor {
extern_methods!(
/// Assigns an optional string that helps identify pipeline states you create from this descriptor.
#[unsafe(method(label))]
#[unsafe(method_family = none)]
pub fn label(&self) -> Option<Retained<NSString>>;
/// Setter for [`label`][Self::label].
///
/// This is [copied][objc2_foundation::NSCopying::copy] when set.
#[unsafe(method(setLabel:))]
#[unsafe(method_family = none)]
pub fn setLabel(&self, label: Option<&NSString>);
#[cfg(feature = "MTL4FunctionDescriptor")]
/// Assigns the function that the machine learning pipeline you create from this descriptor executes.
#[unsafe(method(machineLearningFunctionDescriptor))]
#[unsafe(method_family = none)]
pub fn machineLearningFunctionDescriptor(&self)
-> Option<Retained<MTL4FunctionDescriptor>>;
#[cfg(feature = "MTL4FunctionDescriptor")]
/// Setter for [`machineLearningFunctionDescriptor`][Self::machineLearningFunctionDescriptor].
///
/// This is [copied][objc2_foundation::NSCopying::copy] when set.
#[unsafe(method(setMachineLearningFunctionDescriptor:))]
#[unsafe(method_family = none)]
pub fn setMachineLearningFunctionDescriptor(
&self,
machine_learning_function_descriptor: Option<&MTL4FunctionDescriptor>,
);
#[cfg(feature = "MTLTensor")]
/// Sets the dimension of an input tensor at a buffer index.
///
/// - Parameters:
/// - dimensions: the dimensions of the tensor.
/// - bufferIndex: Index of the tensor to modify.
///
/// # Safety
///
/// `bufferIndex` might not be bounds-checked.
#[unsafe(method(setInputDimensions:atBufferIndex:))]
#[unsafe(method_family = none)]
pub unsafe fn setInputDimensions_atBufferIndex(
&self,
dimensions: Option<&MTLTensorExtents>,
buffer_index: NSInteger,
);
#[cfg(feature = "MTLTensor")]
/// Sets the dimensions of multiple input tensors on a range of buffer bindings.
///
/// Use this method to specify the dimensions of multiple input tensors at a range of indices in a single call.
///
/// You can indicate that any tensors in the range have unspecified dimensions by providing `NSNull` at the their
/// corresponding index location in the array.
///
/// - Important: The range's length property needs to match the number of dimensions you provide. Specifically,
/// `range.length` needs to match `dimensions.count`.
///
/// - Parameters:
/// - dimensions: An array of tensor extents.
/// - range: The range of inputs of the `dimensions` argument.
/// The range's `length` needs to match the dimensions' `count` property.
///
/// # Safety
///
/// `range` might not be bounds-checked.
#[unsafe(method(setInputDimensions:withRange:))]
#[unsafe(method_family = none)]
pub unsafe fn setInputDimensions_withRange(
&self,
dimensions: &NSArray<MTLTensorExtents>,
range: NSRange,
);
#[cfg(feature = "MTLTensor")]
/// Obtains the dimensions of the input tensor at `bufferIndex` if set, `nil` otherwise.
///
/// # Safety
///
/// `bufferIndex` might not be bounds-checked.
#[unsafe(method(inputDimensionsAtBufferIndex:))]
#[unsafe(method_family = none)]
pub unsafe fn inputDimensionsAtBufferIndex(
&self,
buffer_index: NSInteger,
) -> Option<Retained<MTLTensorExtents>>;
/// Resets the descriptor to its default values.
#[unsafe(method(reset))]
#[unsafe(method_family = none)]
pub fn reset(&self);
);
}
/// Methods declared on superclass `NSObject`.
#[cfg(feature = "MTL4PipelineState")]
impl MTL4MachineLearningPipelineDescriptor {
extern_methods!(
#[unsafe(method(init))]
#[unsafe(method_family = init)]
pub fn init(this: Allocated<Self>) -> Retained<Self>;
#[unsafe(method(new))]
#[unsafe(method_family = new)]
pub fn new() -> Retained<Self>;
);
}
#[cfg(feature = "MTL4PipelineState")]
impl DefaultRetained for MTL4MachineLearningPipelineDescriptor {
#[inline]
fn default_retained() -> Retained<Self> {
Self::new()
}
}
extern_class!(
/// Represents reflection information for a machine learning pipeline state.
///
/// See also [Apple's documentation](https://developer.apple.com/documentation/metal/mtl4machinelearningpipelinereflection?language=objc)
#[unsafe(super(NSObject))]
#[derive(Debug, PartialEq, Eq, Hash)]
pub struct MTL4MachineLearningPipelineReflection;
);
unsafe impl Send for MTL4MachineLearningPipelineReflection {}
unsafe impl Sync for MTL4MachineLearningPipelineReflection {}
extern_conformance!(
unsafe impl NSObjectProtocol for MTL4MachineLearningPipelineReflection {}
);
impl MTL4MachineLearningPipelineReflection {
extern_methods!(
#[cfg(feature = "MTLArgument")]
/// Describes every input and output of the pipeline.
#[unsafe(method(bindings))]
#[unsafe(method_family = none)]
pub fn bindings(&self) -> Retained<NSArray<ProtocolObject<dyn MTLBinding>>>;
);
}
/// Methods declared on superclass `NSObject`.
impl MTL4MachineLearningPipelineReflection {
extern_methods!(
#[unsafe(method(init))]
#[unsafe(method_family = init)]
pub fn init(this: Allocated<Self>) -> Retained<Self>;
#[unsafe(method(new))]
#[unsafe(method_family = new)]
pub fn new() -> Retained<Self>;
);
}
impl DefaultRetained for MTL4MachineLearningPipelineReflection {
#[inline]
fn default_retained() -> Retained<Self> {
Self::new()
}
}
extern_protocol!(
/// A pipeline state that you can use with machine-learning encoder instances.
///
/// See ``MTL4MachineLearningCommandEncoder`` for more information.
///
/// See also [Apple's documentation](https://developer.apple.com/documentation/metal/mtl4machinelearningpipelinestate?language=objc)
#[cfg(feature = "MTLAllocation")]
pub unsafe trait MTL4MachineLearningPipelineState:
MTLAllocation + NSObjectProtocol + Send + Sync
{
/// Queries the string that helps identify this object.
#[unsafe(method(label))]
#[unsafe(method_family = none)]
fn label(&self) -> Option<Retained<NSString>>;
#[cfg(feature = "MTLDevice")]
/// Returns the device the pipeline state belongs to.
#[unsafe(method(device))]
#[unsafe(method_family = none)]
fn device(&self) -> Retained<ProtocolObject<dyn MTLDevice>>;
/// Returns reflection information for this machine learning pipeline state.
#[unsafe(method(reflection))]
#[unsafe(method_family = none)]
fn reflection(&self) -> Option<Retained<MTL4MachineLearningPipelineReflection>>;
/// Obtain the size of the heap, in bytes, this pipeline requires during the execution.
///
/// Use this value to allocate a ``MTLHeap`` instance of sufficient size that you can then provide to
/// ``MTL4MachineLearningCommandEncoder/dispatchNetworkWithIntermediatesHeap:``.
///
/// Metal uses this heap to store intermediate data as it executes the pipeline. It is your responsibility to provide
/// a heap at least as large as this property requests.
#[unsafe(method(intermediatesHeapSize))]
#[unsafe(method_family = none)]
fn intermediatesHeapSize(&self) -> NSUInteger;
}
);