[Relax][Training] Loss functions #112
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This PR introduces loss functions for relax training and provides a tool `append_loss` which enables user to append a loss after a forward function. About the `append_loss`, some previous discussions can be found in #111. Currently support: - L1Loss - MSELoss - CrossEntropyLoss
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Thanks folks. Keep up with great works! |
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The pattern field of the match shape can define variables, as a result, we need to add DefEqual and Hash here. Added a regression testcase. Lesson: we would benefit from more testcases with check_save_roundtrip checks(like this one) for more relax example. Additional change: - Redirected TVMScript printer to be able to print relax fragements useful for debugging.
MasterJH5574
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This PR introduces loss functions for relax training and provides a tool `append_loss` which enables user to append a loss after a forward function. About the `append_loss`, some previous discussions can be found in #111. Currently support: - L1Loss - MSELoss - CrossEntropyLoss
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The pattern field of the match shape can define variables, as a result, we need to add DefEqual and Hash here. Added a regression testcase. Lesson: we would benefit from more testcases with check_save_roundtrip checks(like this one) for more relax example. Additional change: - Redirected TVMScript printer to be able to print relax fragements useful for debugging.
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This PR introduces loss functions for relax training and provides a tool `append_loss` which enables user to append a loss after a forward function. About the `append_loss`, some previous discussions can be found in #111. Currently support: - L1Loss - MSELoss - CrossEntropyLoss
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This PR introduces loss functions for relax training and provides a tool
append_losswhich enables user to append a loss after a forward function.About the
append_loss, some previous discussions can be found in #111.Currently support: