GitLab

Added use_keras_upsampling_2d flags to use keras upsampling layer instead of optimized custom spatial_transform_ops.

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This CL changes ResidualBlock and InvertedBottleneckBlock.

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For all modified calls to set_mixed_precision_policy(), the loss_scale argument was removed, as it cannot be passed if the nonexperimental API is used. For all such callers, the loss_scale is later used to explicitly create a LossScaleOptimizer, so removing the argument has no impact.

Switching to the non-experimental LossScaleOptimizer has no effect, as it has near identical behavior and all isinstance checks within the official models check for the non-experimental version.

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This has no functional impact since the default is currently True, but I plan on changing the default to False soon.

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The function `tf.train.experimental.enable_mixed_precision_graph_rewrite` will be removed from the TF2 namespace soon, at which point it will only be accessible under tf.compat.v1.

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The default is True, but I plan on changing it to False soon. After that, I plan on removing the argument and never using the experimental API.

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[core] Use the full model instead of checkpoint_items when constructing Checkpoint in multitask evaluator.

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[core] Update BestCheckpointExporter to support dictionary with arbitrary depth (possibly coming from multitask eval).
Also added best checkpointexporter support to multitask.

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