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* Merge pull request #21958 from MattConley:CudaOccupancyGravatar TensorFlower Gardener2018-10-01
|\ | | | | | | PiperOrigin-RevId: 215331087
* | Add mode_override to the TPU embedding enqueue ops. This allows the mode to beGravatar A. Unique TensorFlower2018-10-01
| | | | | | | | | | | | | | overridden at runtime allowing dynamic switching between inference and training modes. Not fully implemented yet. PiperOrigin-RevId: 215325071
* | [XLA] Migrate from gtl::FlatSet to absl::flat_hash_setGravatar Benjamin Kramer2018-10-01
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* | Make Keras/TPU more robust to closed TF sessions.Gravatar Russell Power2018-10-01
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* | Merge pull request #21868 from kingofthebongo2008:upgrade_protobuf_to_v_3.6.1Gravatar TensorFlower Gardener2018-10-01
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* | | [XLA] Add kAllToAll and kCollectivePermute to ↵Gravatar A. Unique TensorFlower2018-10-01
| | | | | | | | | | | | | | | | | | EffectiveOperandPrecisionIsOutputPrecision list. PiperOrigin-RevId: 215311766
* | | [tf.data] Adding `tf.data.Options()`, `tf.data.Dataset.options()`, and ↵Gravatar Jiri Simsa2018-10-01
| | | | | | | | | | | | | | | | | | `tf.data.Dataset.with_options()` to make it possible to respectively represent, get, and set options, such as optimization configuration, of a tf.data input pipeline. PiperOrigin-RevId: 215310764
* | | Merge pull request #22519 from jayfurmanek:nccl2_configureGravatar TensorFlower Gardener2018-10-01
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* | | | [tf.data] More robust solution for input pipeline <--> performance model ↵Gravatar Jiri Simsa2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | coordination. PiperOrigin-RevId: 215309735
* | | | Mark bfloat16 as supported for ExponentialMovingAverage.Gravatar A. Unique TensorFlower2018-10-01
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* | | | [tf.data] Deprecate `tf.contrib.data` and introduce `tf.data.experimental` ↵Gravatar Derek Murray2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | to replace it. This change prepares `tf.data` for TensorFlow 2.0, where `tf.contrib` will no longer exist. It retains the pre-existing endpoints in `tf.contrib.data` with deprecation warnings. Note there are some exceptions to the move: * Deprecated symbols in `tf.contrib.data` have not been moved to `tf.data.experimental`, because replacements already exist. * `tf.contrib.data.LMDBDataset` has not been moved, because we plan to move it to a SIG-maintained repository. * `tf.contrib.data.assert_element_shape()` has not yet been moved, because it depends on functionality in `tf.contrib`, and it will move in a later change. * `tf.contrib.data.AUTOTUNE` has not yet been moved, because we have not yet determined how to `tf_export()` a Python integer. * The stats-related API endpoints have not yet appeared in a released version of TensorFlow, so these are moved to `tf.data.experimental` without retaining an endpoint in `tf.contrib.data`. In addition, this change includes some build rule and ApiDef refactoring: * Some of the "//third_party/tensorflow/python:training" dependencies had to be split in order to avoid a circular dependency. * The `tf.contrib.stateless` ops now have a private core library for the generated wrappers (and accordingly are hidden in their ApiDef) so that `tf.data.experimental.sample_from_datasets()` can depend on them. PiperOrigin-RevId: 215304249
* | | | Change semantics of DistributionStrategy.update() to make sure theGravatar A. Unique TensorFlower2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | output depends on the updates across all mirrors. Before this change, update() would return a Mirrored value that where each component was an update to a single mirror. This caused a problem since for reading purposes other DistributionStrategy methods would consider it okay to read any single component, and so if you for example did something like session.run(strategy.update(...)) it would only perform the update on one replica. The fix is to have the output be a Mirrored value that is actually the identity operation returning the output on that device, but that has a control dependency making sure that the update actually happens on all the replicas. This fix was already present in MirroredVariable._assign_func, this CL moves the fix into update() and generalizes it to multiple return values. To disable this new grouping behavior, you may now pass "grouped=False" to update(). For example, some callers (like Optimizer) are performing a lot of updates and they prefer to group all of them together at once for performance reasons. In this case, we still want to make sure the caller executes the update on all replicas, so we return an unwrapped value instead of a Mirrored value. This has the happy side effect of removing a bunch of unwrap calls in client code, since unwrapping was the only safe way to use the Mirrored value we used to return. PiperOrigin-RevId: 215301909
* | | | Override implementation of log survival for Exponential distribution to ↵Gravatar A. Unique TensorFlower2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | better handle small values. PiperOrigin-RevId: 215299532
* | | | [TF/XLA] Optimize `Encapsulator::GetFunctionNameAttr()`.Gravatar Derek Murray2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | The previous version was hitting a very slow path in `GetNodeAttr()`, which is expensive when the named attr is not found. This change inlines the logic of finding the two relevant attrs inside `GetFunctionNameAttr()` and avoids constructing a status object with a serialized `NodeDef` when the attr can't be found. PiperOrigin-RevId: 215298411
* | | | Small tweaks to comments and documentation strings.Gravatar A. Unique TensorFlower2018-10-01
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* | | | Add email comment explicitly authorizing distributions/special_math.py be ↵Gravatar Joshua V. Dillon2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | released under Apache 2.0. PiperOrigin-RevId: 215296386
* | | | If keras_model_path is google storage url, provide util to download modelGravatar Zhenyu Tan2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | remotely. PiperOrigin-RevId: 215295504
* | | | Improve error message in transpose shape inference.Gravatar Tayo Oguntebi2018-10-01
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* | | | Clean up the build_xla_ops to use the generated C++ TF op wrappers.Gravatar Sanjoy Das2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | This cleanup will make the future CL implementing lazy compilation simpler. Includes some supporting changes: - Teach NewInternalScope to create a scope that doesn't do shape inference. We need this because we don't have a ShapeRefiner that has been run over the entire graph available in the build_xla_ops pass. - Add a WithAssignedDevice modifier to tensorflow::Scope. - Make cc_op_gen write out an Operation field for nodes which may not necessarily have any outputs. We already did this in most cases, but we weren't doing it for nodes that have possibly-empty list outputs. - Minor change renaming ops/xla_jit_op.cc to ops/xla_jit_ops.cc, now that we have more than one XLA JIT op. PiperOrigin-RevId: 215293817
* | | | Fix Android builds when using --define=with_tflite_flexGravatar Jared Duke2018-10-01
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* | | | Remove jemalloc build files and dead configuration options.Gravatar Ayush Dubey2018-10-01
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* | | | Added option (off by default) to enable a higher-performance variant of theGravatar A. Unique TensorFlower2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | Adam optimizer's variable update formula. PiperOrigin-RevId: 215290881
* | | | Don't generate backward function and delete when its not necessaryGravatar Akshay Modi2018-10-01
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* | | | Don't run initialize ops if it's empty. Fixes a bug when using the profiler.Gravatar Jonathan Hseu2018-10-01
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* | | | Drop external control dependencies in tfe.defun.Gravatar Alexandre Passos2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | They shouldn't help given the automatic control dependencies, and are tricky to capture in the general case. PiperOrigin-RevId: 215282837
* | | | internal changeGravatar Mark Daoust2018-10-01
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* | | | Fix benchmark regression.Gravatar Alexandre Passos2018-10-01
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* | | | Update keras_applications to 1.0.6 and keras_preprocessing to 1.0.5.Gravatar Francois Chollet2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | This removes the transitive keras and scipy dependencies in TensorFlow. PiperOrigin-RevId: 215277190
* | | | Disable async remote testsGravatar Akshay Modi2018-10-01
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* | | | Minor speed improvements to defun.Gravatar Akshay Modi2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - EncodeArg in C instead of python. - Also caches parsed device specs, and device spec hashes - Adds a common way to register python types in C. - Fastpath canonicalize function inputs when no kwargs are passed - Set the func name attr directly instead of creating an op to wrap it. - Rewrite IsAttrsHelper without caching Before: entry { name: "MicroBenchmarks.benchmark_defun_matmul_2_by_2_CPU" iters: 30000 wall_time: 101.803263028 extras { key: "examples_per_sec" value { double_value: 9822.86785562 } } } After: entry { name: "MicroBenchmarks.benchmark_defun_matmul_2_by_2_CPU" iters: 30000 wall_time: 47.2899993261 extras { key: "examples_per_sec" value { double_value: 21146.1199884 } } } PiperOrigin-RevId: 215272962
* | | | [XLA] Migrate from gtl::FlatMap to absl::flat_hash_mapGravatar Benjamin Kramer2018-10-01
| | | | | | | | | | | | | | | | PiperOrigin-RevId: 215272497
* | | | Fix reported cuDNN default version during configuration.Gravatar A. Unique TensorFlower2018-10-01
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* | | | Make cond_v2 If op lowering work in a defun + eager.Gravatar Skye Wanderman-Milne2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | Prior to this change, the lowering pass assumed that the If op functions would be available in the If op's graph. If the If op is defined in a defun and then called via eager execution, the functions will be in the eager context, but not in the defun's graph. This change makes the lowering pass correctly use the function library passed in by the caller via GraphOptimizationPassOptions. PiperOrigin-RevId: 215271990
* | | | Fixes possible out-of-bounds access by strided slice.Gravatar Alexandre Passos2018-10-01
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* | | | Check in and refactor the OVIC detector benchmarker.Gravatar A. Unique TensorFlower2018-10-01
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* | | | Add option to initialize the TPU system.Gravatar A. Unique TensorFlower2018-10-01
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* | | | Internal build specification changeGravatar A. Unique TensorFlower2018-10-01
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* | | | Expose tpu_host_placement_function().Gravatar Youlong Cheng2018-10-01
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* | | | Merge pull request #22210 from dmitrievanthony:apache-ignite-datasetGravatar TensorFlower Gardener2018-10-01
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* | | | | Add new attributes for the defun forward/backward functions.Gravatar Scott Zhu2018-10-01
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* | | | | Automated rollback of commit cb98ceba9cff8c10ee3c7e89dc8925c88b28118eGravatar A. Unique TensorFlower2018-10-01
| | | | | | | | | | | | | | | | | | | | PiperOrigin-RevId: 215254762
* | | | | Updating function and class tf_export decorators for endpoints according toGravatar Anna R2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | https://github.com/tensorflow/community/pull/16. In addition to the changes in the doc, I made the following updates (these changes make sense to me and I didn't notice them when compiling the doc): * deprecate saved_model.builder.SavedModelBuilder - replaced with saved_model.SavedModelBuilder * deprecate python_io.tf_record_iterator - replaced with io.tf_record_iterator * deprecate python_io.TFRecordWriter - replaced with io.TFRecordWriter * move reduce_join to tf.string PiperOrigin-RevId: 215253944
* | | | | Allow zero number of inputs in XRT execute operation.Gravatar A. Unique TensorFlower2018-10-01
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* | | | | Add deprecation notice for BasicRNNCell, which will be replaced by ↵Gravatar Scott Zhu2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | keras.SimpleRNNCell. PiperOrigin-RevId: 215249611
* | | | | internal change onlyGravatar A. Unique TensorFlower2018-10-01
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* | | | | Automated rollback of commit 6a787235b95dd3040fc5ff7fb7104585e746c66aGravatar Christopher Olston2018-10-01
| | | | | | | | | | | | | | | | | | | | PiperOrigin-RevId: 215248737
* | | | | Fix typo.Gravatar Dan Moldovan2018-10-01
| | | | | | | | | | | | | | | | | | | | PiperOrigin-RevId: 215246174
* | | | | Make GCS filesystem/metadata lookup retries configurableGravatar Russell Power2018-10-01
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* | | | | Merge pull request #22122 from ↵Gravatar TensorFlower Gardener2018-10-01
|\ \ \ \ \ | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | yongtang:22115-tf.contrib.image.transform-float16-gpu PiperOrigin-RevId: 215240869
* | | | | | Automated rollback of commit 5f822d694af6e4aa57fe8a426032a91dc61e30d6Gravatar Alexandre Passos2018-10-01
| | | | | | | | | | | | | | | | | | | | | | | | PiperOrigin-RevId: 215239710
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