POC: enable to train at the double precision #207
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RaulPPelaez
reviewed
Jul 24, 2023
| @@ -37,7 +37,7 @@ def get_args(): | |||
| parser.add_argument('--ema-alpha-neg-dy', type=float, default=1.0, help='The amount of influence of new losses on the exponential moving average of dy') | |||
| parser.add_argument('--ngpus', type=int, default=-1, help='Number of GPUs, -1 use all available. Use CUDA_VISIBLE_DEVICES=1, to decide gpus') | |||
| parser.add_argument('--num-nodes', type=int, default=1, help='Number of nodes') | |||
| parser.add_argument('--precision', type=int, default=32, choices=[16, 32], help='Floating point precision') | |||
| parser.add_argument('--precision', type=int, default=32, choices=[16, 32, 64], help='Floating point precision') | |||
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oh wow I totally missed this argument when I implemented #182
RaulPPelaez
reviewed
Jul 24, 2023
| loss_y = loss_fn(y, batch.y) | ||
| # y | ||
| y_dtype = {16: torch.float16, 32: torch.float32, 64: torch.float64}[self.hparams.precision] | ||
| loss_y = loss_fn(y, batch.y.to(y_dtype)) |
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How come you need this here but not a few lines above for neg_dy?
RaulPPelaez
reviewed
Jul 24, 2023
| # Keep molecules with specific elements | ||
| if self.atomic_numbers: | ||
| if not set(z.numpy()).issubset(self.atomic_numbers): | ||
| continue |
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This got mixed from #206, right?
RaulPPelaez
reviewed
Jul 24, 2023
| y = pt.tensor(self.y_mm[idx], dtype=pt.float32).view( | ||
| 1, 1 | ||
| ) # It would be better to use float64, but the trainer complaints | ||
| y = pt.tensor(self.y_mm[idx], dtype=pt.float64).view(1, 1) |
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I would pass dtype as an argument to Ace here and store everything in the correct type. I do not see why store pos in float32 and y in float64.
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Obsolete |
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