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//
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// Pipeline.swift
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// Diffusion
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//
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// Created by Pedro Cuenca on December 2022.
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// See LICENSE at https://github.com/huggingface/swift-coreml-diffusers/LICENSE
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//
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import Foundation
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import CoreML
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import Combine
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import StableDiffusion
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typealias StableDiffusionProgress = StableDiffusionPipeline.Progress
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class Pipeline {
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let pipeline: StableDiffusionPipeline
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var progress: StableDiffusionProgress? = nil {
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didSet {
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progressPublisher.value = progress
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}
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}
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lazy private(set) var progressPublisher: CurrentValueSubject<StableDiffusionProgress?, Never> = CurrentValueSubject(progress)
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init(_ pipeline: StableDiffusionPipeline) {
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self.pipeline = pipeline
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}
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func generate(prompt: String, negativePrompt: String = "", scheduler: StableDiffusionScheduler, numInferenceSteps stepCount: Int = 50, seed: UInt32? = nil) throws -> (CGImage, TimeInterval) {
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let beginDate = Date()
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print("Generating...")
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let theSeed = seed ?? UInt32.random(in: 0..<UInt32.max)
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let images = try pipeline.generateImages(
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prompt: prompt,
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negativePrompt: negativePrompt,
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imageCount: 1,
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stepCount: stepCount,
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seed: theSeed,
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scheduler: scheduler
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) { progress in
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handleProgress(progress)
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return true
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}
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let interval = Date().timeIntervalSince(beginDate)
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print("Got images: \(images) in \(interval)")
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// unwrap the 1 image we asked for
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guard let image = images.compactMap({ $0 }).first else { throw "Generation failed" }
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return (image, interval)
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}
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func handleProgress(_ progress: StableDiffusionPipeline.Progress) {
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self.progress = progress
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}
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}
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