| Commit message (Collapse) | Author | Age |
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{Lookup,Create,LookupOrCreate}Resource().
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PiperOrigin-RevId: 215005698
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core (and added that as a base class for all the contrib tests). Also changed the assertDatasetsEqual functions so they are both graph and eager compatible (took the code from CSVDatasetTest) :)
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PiperOrigin-RevId: 215003704
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Since we now have support for FeatureColumnV2 for both DNN and Linear models,
adding tests for the combined canned estimators as well.
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summaries are written at the correct interval for jobs with long-running
evaluations.
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the duration of a single RunInternal() call from RunHandlerPool. It is used for
running inter-op closures with a global scheduler (which in the future) to
improve both median and tail latency (for use-cases like CPU inference).
In the case that global pools aren't used, this change should be a no-op.
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PiperOrigin-RevId: 214989908
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Without this the default toolchain is used for a subset of the build and the
tests do not actually run on GPUs.
This uncovered a setup problem in the Docker image that needed fixing.
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PiperOrigin-RevId: 214983237
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Remove dead logical branch.
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Add a single test flag for enabling v2 control flow in tests since we do not plan to support v2 ops with legacy control flow.
We have 2 test decorators now:
@with_control_flow_v2: Enables all tests in a class to run with v2 control flow.
@disable_control_flow_v2: Disables a test function from running in v2. I have removed the skiptests to avoid setup/teardown overheads.
Enable tests in control_flow_ops_py_test that run with control_flow_v2.
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with associated stats_aggregator.
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We will re-enable it when it is more robust.
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dependency
only to the sparse operators that need it.
Automated rollback of commit 120620caf23a044b8aa2db6ba5984384ec936009
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Fixes an issue where losses created while executing eagerly were returned as unevaluated lambdas in a defun.
Lazily evaluates Layer losses by default when possible. Even when graph building this is generally a better thing to do (e.g. losses called in a while_loop).
Allows calls to Layer.add_loss when executing eagerly, but only for losses which are not conditional on inputs (no activity regularizers).
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function.
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Building binaries with XLA support does not enable it by default, it
simply makes it accessible via default binary builds.
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NOTE: All ops and kernels previously previously defined in
tensorflow/contrib/data have had their name prefixed with
"Experimental" to indicate that they are not (yet) stable, and thus
not subject to backwards or forwards compatibility guarantees.
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with the case when the background thread terminated because the iterator
finished and yet some other requests were coming in.
1. The GetNextFromShard would see an empty buffer and return cancelled instead
of OutOfRange errors
2. On shutdown, we weren't calling all the pending callbacks.
Tested with runs_per_test=5000
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Keras and DistributionStrategy
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for supported operating systems.
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distribution strategies. That is always the appropriate option.
In the existing code, we would set it to a partially specified "worker" name that was ambiguous and end up on the GPU.
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In subsequent change I'll change canned estimators to support FeatureColumn V2
and use this LinearModel.
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tpu_embedding_configuration_py, and tpu_embedding_output_layout_py.
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