[float8] Allow specifying arbitrary dtype for each tensor #1326
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lw
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ghstack-source-id: 7dabc91df68ce20e15551c5488071579e49c263c Pull Request resolved: #1326
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/1326
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ghstack-source-id: d9c0e023cb8667d6f13e2845e9b6845e1669f78a Pull Request resolved: #1326
lw
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ghstack-source-id: e86e1f6a42610d776bccd3f33044f23e311688eb Pull Request resolved: #1326
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ghstack-source-id: aa9f551c8d274f349c4298932fc95c88040abb09 Pull Request resolved: #1326
lw
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ghstack-source-id: c339ea060b7062871a5f57a939e8880e5f727de4 Pull Request resolved: #1326
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ghstack-source-id: 4b3a2f0007d74e3453cefde1307f2a9c5271e83e Pull Request resolved: #1326
vkuzo
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Nov 26, 2024
| @@ -62,6 +62,7 @@ class CastConfig: | |||
| scaling_type: ScalingType = ScalingType.DYNAMIC | |||
| scaling_granularity: ScalingGranularity = ScalingGranularity.TENSORWISE | |||
| static_scale: Optional[torch.Tensor] = None | |||
| dtype: Optional[torch.dtype] = None | |||
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nit:
- can we add a comment on what this is used for, and that
Nonemeans the default e4m3|e5m2 value will be used? - optional - thoughts about naming this in a more specific way such as
target_dtype,lowp_dtype, etc?dtypeis a bit ambiguous across torchao unfortunately :(
vkuzo
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Nov 26, 2024
| @@ -343,12 +367,14 @@ def recipe_name_to_linear_config( | |||
| cc_w = CastConfig(scaling_granularity=ScalingGranularity.AXISWISE) | |||
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| # grad_input_hp = grad_output_fp8_axiswise_dim0 @ weight_fp8_tensorwise | |||
| cc_go = CastConfig(scaling_granularity=ScalingGranularity.AXISWISE) | |||
| cc_go = CastConfig( | |||
| scaling_granularity=ScalingGranularity.AXISWISE, dtype=e4m3_dtype | |||
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nit: maybe we can also add some context in the comments on L353:L363 that it also uses e4m3 for grads?
vkuzo
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Nov 26, 2024
| NoopFwToFloat8E5M2BwDelayed, | ||
| NoopFwToFloat8E5M2BwDynamic, | ||
| NoopFwToFloat8E5M2BwStatic, | ||
| NoopFwToFloat8BwDelayed, |
vkuzo
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Nov 26, 2024
| @@ -303,13 +311,16 @@ def inner_func(): | |||
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| # Calculate the new scales from the updated history stacks | |||
| new_input_scales = amax_history_to_scale_stack( | |||
| fp8_input_amax_history_stack, e4m3_dtype, x_dtype, scale_fn_recipe | |||
| fp8_input_amax_history_stack, input_dtype, x_dtype, scale_fn_recipe | |||
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will likely have to rebase on top of #1329 which changed this line
vkuzo
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Nov 26, 2024
| @@ -62,6 +62,7 @@ class CastConfig: | |||
| scaling_type: ScalingType = ScalingType.DYNAMIC | |||
| scaling_granularity: ScalingGranularity = ScalingGranularity.TENSORWISE | |||
| static_scale: Optional[torch.Tensor] = None | |||
| dtype: Optional[torch.dtype] = None | |||
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| def short_str(self): | |||
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can we also add the dtype here, so it appears when we print an instance of Float8Linear? Float8Linear.__extra_repr__ calls this method.
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This is great! LGTM, had some comments but all are pretty nitty. CI is green - ship it! |
lw
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Dec 4, 2024
ghstack-source-id: d8300e2a07c087f3cd51b03e0e21125a83a29489 Pull Request resolved: #1326
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Superseded by #1378 |
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