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