wehub-resource-sync
120 lines
4.9 KiB
Swift
120 lines
4.9 KiB
Swift
// For licensing see accompanying LICENSE.md file.
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// Copyright (C) 2023 Apple Inc. All Rights Reserved.
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import Foundation
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import CoreML
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import NaturalLanguage
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@available(iOS 17.0, macOS 14.0, *)
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public extension StableDiffusionXLPipeline {
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struct ResourceURLs {
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public let textEncoderURL: URL
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public let textEncoder2URL: URL
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public let unetURL: URL
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public let unetChunk1URL: URL
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public let unetChunk2URL: URL
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public let unetRefinerURL: URL
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public let unetRefinerChunk1URL: URL
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public let unetRefinerChunk2URL: URL
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public let decoderURL: URL
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public let encoderURL: URL
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public let vocabURL: URL
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public let mergesURL: URL
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public init(resourcesAt baseURL: URL) {
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textEncoderURL = baseURL.appending(path: "TextEncoder.mlmodelc")
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textEncoder2URL = baseURL.appending(path: "TextEncoder2.mlmodelc")
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unetURL = baseURL.appending(path: "Unet.mlmodelc")
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unetChunk1URL = baseURL.appending(path: "UnetChunk1.mlmodelc")
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unetChunk2URL = baseURL.appending(path: "UnetChunk2.mlmodelc")
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unetRefinerURL = baseURL.appending(path: "UnetRefiner.mlmodelc")
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unetRefinerChunk1URL = baseURL.appending(path: "UnetRefinerChunk1.mlmodelc")
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unetRefinerChunk2URL = baseURL.appending(path: "UnetRefinerChunk2.mlmodelc")
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decoderURL = baseURL.appending(path: "VAEDecoder.mlmodelc")
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encoderURL = baseURL.appending(path: "VAEEncoder.mlmodelc")
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vocabURL = baseURL.appending(path: "vocab.json")
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mergesURL = baseURL.appending(path: "merges.txt")
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}
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}
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/// Create stable diffusion pipeline using model resources at a
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/// specified URL
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///
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/// - Parameters:
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/// - baseURL: URL pointing to directory holding all model and tokenization resources
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/// - configuration: The configuration to load model resources with
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/// - reduceMemory: Setup pipeline in reduced memory mode
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/// - Returns:
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/// Pipeline ready for image generation if all necessary resources loaded
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init(
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resourcesAt baseURL: URL,
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configuration config: MLModelConfiguration = .init(),
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reduceMemory: Bool = false
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) throws {
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/// Expect URL of each resource
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let urls = ResourceURLs(resourcesAt: baseURL)
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let tokenizer = try BPETokenizer(mergesAt: urls.mergesURL, vocabularyAt: urls.vocabURL)
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let textEncoder: TextEncoderXL?
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if FileManager.default.fileExists(atPath: urls.textEncoderURL.path) {
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textEncoder = TextEncoderXL(tokenizer: tokenizer, modelAt: urls.textEncoderURL, configuration: config)
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} else {
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textEncoder = nil
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}
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// padToken is different in the second XL text encoder
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let tokenizer2 = try BPETokenizer(mergesAt: urls.mergesURL, vocabularyAt: urls.vocabURL, padToken: "!")
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let textEncoder2 = TextEncoderXL(tokenizer: tokenizer2, modelAt: urls.textEncoder2URL, configuration: config)
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// Unet model
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let unet: Unet
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if FileManager.default.fileExists(atPath: urls.unetChunk1URL.path) &&
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FileManager.default.fileExists(atPath: urls.unetChunk2URL.path) {
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unet = Unet(chunksAt: [urls.unetChunk1URL, urls.unetChunk2URL],
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configuration: config)
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} else {
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unet = Unet(modelAt: urls.unetURL, configuration: config)
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}
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// Refiner Unet model
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let unetRefiner: Unet?
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if FileManager.default.fileExists(atPath: urls.unetRefinerChunk1URL.path) &&
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FileManager.default.fileExists(atPath: urls.unetRefinerChunk2URL.path) {
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unetRefiner = Unet(chunksAt: [urls.unetRefinerChunk1URL, urls.unetRefinerChunk2URL],
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configuration: config)
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} else if FileManager.default.fileExists(atPath: urls.unetRefinerURL.path) {
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unetRefiner = Unet(modelAt: urls.unetRefinerURL, configuration: config)
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} else {
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unetRefiner = nil
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}
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// Image Decoder
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// FIXME: Hardcoding to .cpuAndGPU since ANE doesn't support FLOAT32
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let vaeConfig = config.copy() as! MLModelConfiguration
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vaeConfig.computeUnits = .cpuAndGPU
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let decoder = Decoder(modelAt: urls.decoderURL, configuration: vaeConfig)
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// Optional Image Encoder
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let encoder: Encoder?
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if FileManager.default.fileExists(atPath: urls.encoderURL.path) {
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encoder = Encoder(modelAt: urls.encoderURL, configuration: vaeConfig)
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} else {
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encoder = nil
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}
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// Construct pipeline
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self.init(
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textEncoder: textEncoder,
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textEncoder2: textEncoder2,
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unet: unet,
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unetRefiner: unetRefiner,
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decoder: decoder,
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encoder: encoder,
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reduceMemory: reduceMemory
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)
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}
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}
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