using Microsoft.ML; using Microsoft.ML.Tokenizers; using System; using System.Collections.Generic; using System.IO; using System.Linq; using TorchSharp; var batch = 1; var bpe = new Bpe("vocab.json", "merges.txt", endOfWordSuffix: ""); var tokenier = new Tokenizer(bpe); var start_token = 49406; var end_token = 49407; var prompt = "a wild cute green cat"; var res = tokenier.Encode(prompt); var tokens = new[] { start_token }.Concat(res.Ids.Concat(Enumerable.Repeat(0, 75 - res.Ids.Count))).Concat(new[] { end_token }).ToList(); var uncontional_tokens = new[]{start_token, end_token}.Concat(Enumerable.Repeat(0, 75)).ToList(); var tokenTensor = torch.tensor(tokens.ToArray(), dtype: torch.ScalarType.Int64, device: device); tokenTensor = tokenTensor.repeat(batch, 1); var unconditional_tokenTensor = torch.tensor(uncontional_tokens.ToArray(), dtype: torch.ScalarType.Int64, device: device); unconditional_tokenTensor = unconditional_tokenTensor.repeat(batch, 1); torchvision.io.DefaultImager = new torchvision.io.SkiaImager(); var device = TorchSharp.torch.device("cuda:0"); var clipEncoder = new ClipEncoder("clip_encoder.ckpt", device); var img = torch.randn(batch, 4, 64, 64, dtype: torch.ScalarType.Float32, device: device); var t = torch.full(new[]{batch, 1L}, value: batch, dtype: torch.ScalarType.Int32, device: device); var condition = clipEncoder.Forward(tokenTensor); var unconditional_condition = clipEncoder.Forward(unconditional_tokenTensor); clipEncoder.Dispose(); var ddpm = new DDPM("ddim_v_sampler.ckpt", device); var ddimSampler = new DDIMSampler(ddpm); var ddim_steps = 50; img = ddimSampler.Sample(img, condition, unconditional_condition, ddim_steps); ddpm.Dispose(); var autoencoderKL = new AutoencoderKL("autoencoder_kl.ckpt", device); var decoded_images = (torch.Tensor)autoencoderKL.Forward(img); decoded_images = torch.clamp((decoded_images + 1.0) / 2.0, 0.0, 1.0); for(int i = 0; i!= batch; ++i) { var image = decoded_images[i]; image = (image * 255.0).to(torch.ScalarType.Byte).cpu(); torchvision.io.write_image(image, $"{i}.png", torchvision.ImageFormat.Png); }