(model, shape, return_intermediates=True,
verbose=True,
make_prog_row=False)
| 51 | |
| 52 | |
| 53 | def convsample(model, shape, return_intermediates=True, |
| 54 | verbose=True, |
| 55 | make_prog_row=False): |
| 56 | |
| 57 | |
| 58 | if not make_prog_row: |
| 59 | return model.p_sample_loop(None, shape, |
| 60 | return_intermediates=return_intermediates, verbose=verbose) |
| 61 | else: |
| 62 | return model.progressive_denoising( |
| 63 | None, shape, verbose=True |
| 64 | ) |
| 65 | |
| 66 | |
| 67 | def convsample_ddim(model, steps, shape, eta=1.0 |
no test coverage detected