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https://github.com/invoke-ai/InvokeAI
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91565970c2
I'm using stable-diffusion on a 2022 Macbook M2 Air with 24 GB unified memory. I see this taking about 2.0s/it. I've moved many deps from pip to conda-forge, to take advantage of the precompiled binaries. Some notes for Mac users, since I've seen a lot of confusion about this: One doesn't need the `apple` channel to run this on a Mac-- that's only used by `tensorflow-deps`, required for running tensorflow-metal. For that, I have an example environment.yml here: https://developer.apple.com/forums/thread/711792?answerId=723276022#723276022 However, the `CONDA_ENV=osx-arm64` environment variable *is* needed to ensure that you do not run any Intel-specific packages such as `mkl`, which will fail with [cryptic errors](https://github.com/CompVis/stable-diffusion/issues/25#issuecomment-1226702274) on the ARM architecture and cause the environment to break. I've also added a comment in the env file about 3.10 not working yet. When it becomes possible to update, those commands run on an osx-arm64 machine should work to determine the new version set. Here's what a successful run of dream.py should look like: ``` $ python scripts/dream.py --full_precision SIGABRT(6) ↵ 08:42:59 * Initializing, be patient... Loading model from models/ldm/stable-diffusion-v1/model.ckpt LatentDiffusion: Running in eps-prediction mode DiffusionWrapper has 859.52 M params. making attention of type 'vanilla' with 512 in_channels Working with z of shape (1, 4, 32, 32) = 4096 dimensions. making attention of type 'vanilla' with 512 in_channels Using slower but more accurate full-precision math (--full_precision) >> Setting Sampler to k_lms model loaded in 6.12s * Initialization done! Awaiting your command (-h for help, 'q' to quit) dream> "an astronaut riding a horse" Generating: 0%| | 0/1 [00:00<?, ?it/s]/Users/corajr/Documents/lstein/ldm/modules/embedding_manager.py:152: UserWarning: The operator 'aten::nonzero' is not currently supported on the MPS backend and will fall back to run on the CPU. This may have performance implications. (Triggered internally at /Users/runner/work/_temp/anaconda/conda-bld/pytorch_1662016319283/work/aten/src/ATen/mps/MPSFallback.mm:11.) placeholder_idx = torch.where( 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [01:37<00:00, 1.95s/it] Generating: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [01:38<00:00, 98.55s/it] Usage stats: 1 image(s) generated in 98.60s Max VRAM used for this generation: 0.00G Outputs: outputs/img-samples/000001.1525943180.png: "an astronaut riding a horse" -s50 -W512 -H512 -C7.5 -Ak_lms -F -S1525943180 ``` |
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| .. | ||
| data | ||
| dream | ||
| gfpgan | ||
| models | ||
| modules | ||
| lr_scheduler.py | ||
| simplet2i.py | ||
| util.py | ||