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https://github.com/invoke-ai/InvokeAI
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Merge branch 'development' into development
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commit
7647490617
@ -232,7 +232,12 @@ def main():
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print(f"reading prompts from {opt.from_file}")
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with open(opt.from_file, "r") as f:
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data = f.read().splitlines()
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data = list(chunk(data, batch_size))
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if (len(data) >= batch_size):
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data = list(chunk(data, batch_size))
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else:
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while (len(data) < batch_size):
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data.append(data[-1])
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data = [data]
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sample_path = os.path.join(outpath, "samples")
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os.makedirs(sample_path, exist_ok=True)
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@ -264,7 +269,7 @@ def main():
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prompts = list(prompts)
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c = model.get_learned_conditioning(prompts)
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shape = [opt.C, opt.H // opt.f, opt.W // opt.f]
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if not opt.klms:
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samples_ddim, _ = sampler.sample(S=opt.ddim_steps,
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conditioning=c,
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@ -284,7 +289,7 @@ def main():
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model_wrap_cfg = CFGDenoiser(model_wrap)
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extra_args = {'cond': c, 'uncond': uc, 'cond_scale': opt.scale}
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samples_ddim = K.sampling.sample_lms(model_wrap_cfg, x, sigmas, extra_args=extra_args)
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x_samples_ddim = model.decode_first_stage(samples_ddim)
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x_samples_ddim = torch.clamp((x_samples_ddim + 1.0) / 2.0, min=0.0, max=1.0)
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