Remove normalize_inputs and replace with parameter transform #431
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: Pull Request resolved: facebookresearch#431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
…earch#443) Summary: All parameters will have some options that will always be the same. We add a private function that unifies this. Differential Revision: D65695127
…#416) Summary: Instead of creating duplicate transforms whenever we need one, we create a single transform from the config and initialize the wrapped model and wrapped generators with that one transform. This passes the same transform object around and allows the transformations to learn parameters and still be synced up across wrapped objects. Differential Revision: D65155103
…kresearch#431) Summary: `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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…kresearch#431) Summary: `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Differential Revision: D65069497
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Summary: Pull Request resolved: #431 `normalize_inputs` (the one that min-max scales paraemters) is confusingly named (there's another `normalize_inputs` that concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening. This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index. Reviewed By: crasanders Differential Revision: D65069497 fbshipit-source-id: 88c27114c8fcf8126afe6c17b85f8beef8ee14c8
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Summary:
normalize_inputs(the one that min-max scales paraemters) is confusingly named (there's anothernormalize_inputsthat concatenates data and ensures they're all the right types) and is a hard-coded transformation that is applied to all parameters. This means that there's no way to turn the behavior off selectively nor is it obvious that it is happening.This diff removes the normalize_inputs method and replaces it with an parameter transform that will also allow selective application of the transform via an index.
Differential Revision: D65069497