Add Availability Annotations (#18)

Author: nathantannar4

Package.swift

@@ -6,9 +6,9 @@ import PackageDescription
 let package = Package(
     name: "stable-diffusion",
     platforms: [
-        .macOS(.v13),
-        .iOS(.v16),
-       ],
+        .macOS(.v11),
+        .iOS(.v14),
+    ],
     products: [
         .library(
             name: "StableDiffusion",

swift/StableDiffusion/pipeline/Decoder.swift

@@ -6,6 +6,7 @@ import CoreML
 import Accelerate
 
 /// A decoder model which produces RGB images from latent samples
+@available(iOS 16.2, macOS 13.1, *)
 public struct Decoder: ResourceManaging {
 
     /// VAE decoder model

swift/StableDiffusion/pipeline/ManagedMLModel.swift

@@ -7,6 +7,7 @@ import CoreML
 ///
 /// It will automatically load a model into memory when needed or requested
 /// It allows one to request to unload the model from memory
+@available(iOS 16.2, macOS 13.1, *)
 public final class ManagedMLModel: ResourceManaging {
 
     /// The location of the model

swift/StableDiffusion/pipeline/Random.swift

@@ -9,6 +9,7 @@ import CoreML
 ///  This implementation matches:
 ///  [NumPy's older randomkit.c](https://github.com/numpy/numpy/blob/v1.0/numpy/random/mtrand/randomkit.c)
 ///
+@available(iOS 16.2, macOS 13.1, *)
 struct NumPyRandomSource: RandomNumberGenerator {
 
     struct State {

swift/StableDiffusion/pipeline/SafetyChecker.swift

@@ -6,6 +6,7 @@ import CoreML
 import Accelerate
 
 /// Image safety checking model
+@available(iOS 16.2, macOS 13.1, *)
 public struct SafetyChecker: ResourceManaging {
 
     /// Safety checking Core ML model

swift/StableDiffusion/pipeline/SampleTimer.swift

@@ -18,6 +18,7 @@ import Foundation
 /// print(String(format: "mean: %.2f, var: %.2f",
 ///              timer.mean, timer.variance))
 /// ```
+@available(iOS 16.2, macOS 13.1, *)
 public final class SampleTimer: Codable {
     var startTime: CFAbsoluteTime?
     var sum: Double = 0.0

swift/StableDiffusion/pipeline/Scheduler.swift

@@ -9,6 +9,7 @@ import CoreML
 ///  [Hugging Face Diffusers PNDMScheduler](https://github.com/huggingface/diffusers/blob/main/src/diffusers/schedulers/scheduling_pndm.py)
 ///
 /// It uses the pseudo linear multi-step (PLMS) method only, skipping pseudo Runge-Kutta (PRK) steps
+@available(iOS 16.2, macOS 13.1, *)
 public final class Scheduler {
     /// Number of diffusion steps performed during training
     public let trainStepCount: Int
@@ -224,6 +225,7 @@ public final class Scheduler {
     }
 }
 
+@available(iOS 16.2, macOS 13.1, *)
 extension Scheduler {
     /// How to map a beta range to a sequence of betas to step over
     public enum BetaSchedule {

swift/StableDiffusion/pipeline/StableDiffusionPipeline+Resources.swift

@@ -4,6 +4,7 @@
 import Foundation
 import CoreML
 
+@available(iOS 16.2, macOS 13.1, *)
 public extension StableDiffusionPipeline {
 
     struct ResourceURLs {

swift/StableDiffusion/pipeline/StableDiffusionPipeline.swift

@@ -10,6 +10,7 @@ import CoreGraphics
 ///
 /// This implementation matches:
 /// [Hugging Face Diffusers Pipeline](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py)
+@available(iOS 16.2, macOS 13.1, *)
 public struct StableDiffusionPipeline: ResourceManaging {
 
     /// Model to generate embeddings for tokenized input text
@@ -271,6 +272,7 @@ public struct StableDiffusionPipeline: ResourceManaging {
 
 }
 
+@available(iOS 16.2, macOS 13.1, *)
 extension StableDiffusionPipeline {
     /// Sampling progress details
     public struct Progress {

swift/StableDiffusion/pipeline/TextEncoder.swift

@@ -5,6 +5,7 @@ import Foundation
 import CoreML
 
 ///  A model for encoding text
+@available(iOS 16.2, macOS 13.1, *)
 public struct TextEncoder: ResourceManaging {
 
     /// Text tokenizer