| Commit message (Collapse) | Author | Age |
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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
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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) :)
PiperOrigin-RevId: 215004892
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PiperOrigin-RevId: 214964988
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with associated stats_aggregator.
PiperOrigin-RevId: 214961678
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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.
PiperOrigin-RevId: 214940819
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PiperOrigin-RevId: 214824023
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they're moved to core. I overlooked this in the CL to move to core.
PiperOrigin-RevId: 214699544
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This patch introduces optimization that hoists RandomUniform out of map functions.
By doing it, we make function stateless, which is crucial for parallelization and vectorization.
PiperOrigin-RevId: 214623178
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it possible to apply static optimizations to input pipelines whose prefix contains the `set_stats_aggregator` transformation.
PiperOrigin-RevId: 214619583
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PiperOrigin-RevId: 214541221
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PiperOrigin-RevId: 214495925
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PiperOrigin-RevId: 214321627
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tf.contrib.data.
PiperOrigin-RevId: 214294955
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Fix for b/116169724
Only remove noops if they refer to const nodes.
PiperOrigin-RevId: 214199200
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PiperOrigin-RevId: 214173896
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thread to finish even if None is running.
PiperOrigin-RevId: 214040824
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scalar, if stats_aggregator is associated with dataset.
PiperOrigin-RevId: 213989745
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number of filtered elements to monitoring counter.
PiperOrigin-RevId: 213846793
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optimization
PiperOrigin-RevId: 213840320
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drop_remainder)`, which can be used for combining elements of input dataset into "windows". A window
is itself a finite dataset and, among other things, can be used for generalized batching (see https://github.com/tensorflow/community/pull/5 for details).
PiperOrigin-RevId: 213360134
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self.test_session() has been deprecated in 9962eb5e84b15e309410071b06c2ed2d6148ed44 as its name confuses readers of the test. Moving to cached_session() instead which is more explicit about:
* the fact that the session may be reused.
* the session is not closed even when doing a "with self.test_session()" statement.
PiperOrigin-RevId: 213326581
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`num_parallel_calls` argument of `tf.data.Dataset.map()`, `tf.data.Dataset.interleave()`, and `tf.contrib.data.map_and_batch()`.
When `tf.data.AUTOTUNE` is specified, the level of parallelism is determined at runtime. The underlying mechanism instruments the input pipeline to build a performance model and then uses the model to find the optimal values for the parallelism knobs.
PiperOrigin-RevId: 213283297
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Stateless MapDatasets can be paralellized by switching to ParallelMapDataset. We set `num_parallel_calls` to 2 for now, but in the future a special value will be used that result in the optimal value to be selected dynamically at runtime.
This patch also exposed a memory leak which was fixed.
PiperOrigin-RevId: 213015223
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`make_tf_record_dataset` default `prefetch` buffer size to auto-tune (from 1).
PiperOrigin-RevId: 212900920
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tf.decode_csv:
- Modify shape assertions so that both graph and eager accept rank 0 (scalar) and rank 1 tensors as `record_defaults`, and raise an error on other shapes.
- Make tests run in both graph and eager modes
Fixes #22030.
PiperOrigin-RevId: 212877058
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PiperOrigin-RevId: 212829466
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`bucket_by_sequence_length`.
PiperOrigin-RevId: 212684420
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correctly. Refactor MapDefunOp for correctness + better C++ hygiene
PiperOrigin-RevId: 212589285
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performance.
PiperOrigin-RevId: 212557406
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error message had multiple newline characters.
PiperOrigin-RevId: 212381070
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self.test_session() has been deprecated in 9962eb5e84b15e309410071b06c2ed2d6148ed44 as its name confuses readers of the test. Moving to cached_session() instead which is more explicit about:
* the fact that the session may be reused.
* the session is not closed even when doing a "with self.test_session()" statement.
PiperOrigin-RevId: 212338134
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self.test_session() has been deprecated in 9962eb5e84b15e309410071b06c2ed2d6148ed44 as its name confuses readers of the test. Moving to cached_session() instead which is more explicit about:
* the fact that the session may be reused.
* the session is not closed even when doing a "with self.test_session()" statement.
PiperOrigin-RevId: 212336464
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PiperOrigin-RevId: 212294062
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`tf.contrib.data.get_next_as_optional()`.
PiperOrigin-RevId: 212263849
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PiperOrigin-RevId: 212119773
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PiperOrigin-RevId: 212045006
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PiperOrigin-RevId: 212008865
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RELNOTES: n/a
PiperOrigin-RevId: 211995741
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`tf.data.Dataset.interleave`.
Unlike the `tf.data.contrib.parallel_interleave` whose parallelism is tied to the `cycle_length` argument, the newly introduced `num_parallel_calls` argument of `tf.data.Dataset.interleave` is decoupled from the `cycle_length` argument and identifies the degree of parallelism to use for fetching output elements.
PiperOrigin-RevId: 211886816
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individually and using consistent style for existing test names.
PiperOrigin-RevId: 211855926
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PiperOrigin-RevId: 211733735
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CancellationManagers for each run of the function.
PiperOrigin-RevId: 211717580
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implementations of the batch and padded batch reducers.
PiperOrigin-RevId: 211706766
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`MapDataset`.
PiperOrigin-RevId: 211520001
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optimization.
PiperOrigin-RevId: 211179990
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`tf.contrib.data.sample_from_datasets()`.
PiperOrigin-RevId: 210830214
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`features` and `feature-values` count statistics.
PiperOrigin-RevId: 210828171
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`make_batch_featured_dataset()` for extracting the label from the feature dictionaries. If label_key is provided, returned dataset will be a tuple of feature dictionaries and label.
PiperOrigin-RevId: 210766469
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PiperOrigin-RevId: 210626817
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PiperOrigin-RevId: 210559796
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