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* Correct a couple of format stringsHEADmasterGravatar Benjamin Barenblat2018-10-10
| | | | | | | Change a couple of fscanf-style format strings to use the format macro constants defined in cinttypes. This quashes -Wformat. PiperOrigin-RevId: 216545604
* [Grappler] Add RemoveStackStridedSliceSameAxis optimizer.Gravatar Eugene Brevdo2018-10-10
| | | | | | | | | | | | | | | | // Replace operations of the form: // x = stack((a_0, a_1, ..., a_{n-1}), axis=k)[:,...,i,...] // with // a_i // when the strided slice index `i` is applied in the k'th axis. // // Similarly, replace operations of the form: // x = stack((a_0, a_1, ..., a_{n-1}), axis=k)[:,...,i:i+1,...] // with // expand_dims(a_i, axis=k) // PiperOrigin-RevId: 216535346
* Allow the executor type for a function to be specified as an attr on a function.Gravatar Derek Murray2018-10-10
| | | | | | | | | | | This change complements the existing `InstantiateOptions::executor_type` option, which takes precedence over the attr if both are provided. It enables the choice of executor to be separated from both the calling op implementation and the function definition, which simplifies the use of custom executors in operations that take a function as an attr (e.g.) `tf.data` and the functional control-flow ops. PiperOrigin-RevId: 216532778
* Automated rollback of commit 950cf87104bfee28e2165fe368f66337b8a1336dGravatar A. Unique TensorFlower2018-10-10
| | | | PiperOrigin-RevId: 216500702
* Add support for modeling fast memory close to the processor/gpuGravatar A. Unique TensorFlower2018-10-09
| | | | PiperOrigin-RevId: 216453979
* Update ops-related pbtxt files.Gravatar A. Unique TensorFlower2018-10-09
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* Add 'remove' operation to MutableHashTable and MutableDenseHashTable.Gravatar A. Unique TensorFlower2018-10-09
| | | | PiperOrigin-RevId: 216443201
* [tf.data vectorization] Add vectorizer for `Add` opGravatar Rachel Lim2018-10-09
| | | | PiperOrigin-RevId: 216424512
* Update ops-related pbtxt files.Gravatar A. Unique TensorFlower2018-10-09
| | | | PiperOrigin-RevId: 216410913
* Add RaggedTensors to tf.core. Moving the RaggedGather op kernel.Gravatar A. Unique TensorFlower2018-10-09
| | | | PiperOrigin-RevId: 216400726
* [tf.data] NUMA-aware MapAndBatch dataset.Gravatar Brennan Saeta2018-10-09
| | | | PiperOrigin-RevId: 216395709
* Update ops-related pbtxt files.Gravatar A. Unique TensorFlower2018-10-09
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* [tf.data vectorization] Handle captured inputs in MapVectorization optimizationGravatar Rachel Lim2018-10-09
| | | | PiperOrigin-RevId: 216381943
* Create SDCAOptimizerV2 op to fix the "adaptative" typo.Gravatar Yuefeng Zhou2018-10-09
| | | | PiperOrigin-RevId: 216370193
* Change LOG(WARNING) to VLOG(1) in utilsGravatar Peter Ma2018-10-09
| | | | PiperOrigin-RevId: 216369081
* Removed unused load statements from the core BUILD.Gravatar A. Unique TensorFlower2018-10-09
| | | | PiperOrigin-RevId: 216354906
* Automated rollback of commit 5f308cb408eb46ec9af0546be6b9ae1d5166b185Gravatar A. Unique TensorFlower2018-10-08
| | | | PiperOrigin-RevId: 216309111
* Refactor CalculateOutputSize() from VirtualScheduler protected member ↵Gravatar Peter Ma2018-10-08
| | | | | | function to utils; Refactor EstimateSize() from memory_optimizer.cc to utils; some small changes for readability improvement PiperOrigin-RevId: 216307257
* Automated rollback of commit 07df147ab20c4a5329148e5fb5f7f6b187cb73a4Gravatar Reed Wanderman-Milne2018-10-08
| | | | PiperOrigin-RevId: 216299809
* Add a tracing::ScopedActivity event to track the duration of a Session::Run()Gravatar A. Unique TensorFlower2018-10-08
| | | | | | | call for better xprof tracing. Also annotate synchronous op execution with the session-run id (or step_id) as metadata leveraging the support introduced in cl/215985561. This should enable highlighting the duration of a Session::Run and all the ops that ran in it for visualizing latency regressions in the case of CPU inference. PiperOrigin-RevId: 216284682
* Register int64 SUM GPU kernel.Gravatar James Qin2018-10-08
| | | | PiperOrigin-RevId: 216280913
* Fix the seeding for `Dataset.shuffle(..., reshuffle_each_iteration=False)`.Gravatar Derek Murray2018-10-08
| | | | | | | | | Previously, we were passing the first (graph-level) seed for both the graph-level and op-level seeds when creating a C++ dataset. This change passes the op-level seed to the appropriate point, and adds a test for the behavior with graph-but-not-op-level seeds. PiperOrigin-RevId: 216280641
* Consolidate device parameter arguments into a shared DeviceInfo structGravatar A. Unique TensorFlower2018-10-08
| | | | PiperOrigin-RevId: 216280197
* Remove deprecations for some of the endpoints in ApiDef files. These changesGravatar Anna R2018-10-08
| | | | | | | | | | | | | | | are made according to https://github.com/tensorflow/community/pull/16. I am keeping a few symbols deprecated not mentioned in the doc: tf.diag - it seems best to keep it next to tf.linalg.diag, so that the two are easy to compare and decide which one to use. The plan is to rename tf.diag to tf.tensor_diag. tf.is_nan - similar to tf.is_inf, tf.is_finite, tf.is_numeric_tensor which are all getting deprecated and replaced by symbols in tf.debugging. tf.string_to_number - other string endpoints in root namespace are getting deprecated: for e.g. tf.substr, tf.string_join. tf.dequantize - all quantization ops should be under tf.quantize. I probably missed this one. tf.check_numerics - similar to other debugging ops that are getting moved to tf.debugging. tf.squared_difference - moved to tf.math namespace and not as popular as some other math ops such as tf.add to justify keeping endpoint in root. tf.decode_raw - similar to other ops such as tf.decode_csv that are getting moved to tf.io.decode_csv. PiperOrigin-RevId: 216278010
* Automated rollback of commit 13b47e6c4f9d7b295948b1057139bf676e394b6fGravatar Derek Murray2018-10-08
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* Automated rollback of commit 09b0fc199129e0f487a39741bdf674cf09035cbcGravatar Derek Murray2018-10-08
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* Merge pull request #22783 from Intel-tensorflow:sfu2/clean_mklmlGravatar TensorFlower Gardener2018-10-08
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* | [tf.data] Choose non-deterministic seed once per Python-level `Dataset` object.Gravatar Derek Murray2018-10-08
| | | | | | | | | | | | | | | | | | | | This changes the behavior of randomness-introducing datasets (`tf.data.Dataset.shuffle()`, `tf.data.experimental.shuffle_and_repeat()`, and `tf.data.experimental.RandomDataset`). Previously, when you used the same `tf.data.Dataset` object multiple times in a pipeline (e.g. by zipping two datasets derived from the same randomness-introducing dataset) *and* you did not specify an explicit `seed`, the implementation would choose different non-deterministic seeds for each use of the `Dataset` object. With this change, the seed will be chosen once per `Dataset` (technically, once per `Dataset`-`Graph` combination, due to the vagaries of capturing state in `Dataset.make_one_shot_iterator()`), which means that all uses of the same dataset object will observe the same sequence of values. This change also revealed a small bug in how `Dataset.shuffle(..., reshuffle_each_iteration=False)` is serialized when an explicit seed is specified. The op-level seed was dropped, which could lead to non-deterministic behavior. This change fixes that issue by forwarding the op-level seed to the appropriate place. PiperOrigin-RevId: 216248013
* | Automated rollback of commit 295b3c80555cc82d8d70faf96a47681e1d904b9cGravatar Derek Murray2018-10-08
| | | | | | | | PiperOrigin-RevId: 216247929
* | Partial support tfe.defun in tf.gradients.Gravatar Alexandre Passos2018-10-08
| | | | | | | | | | | | | | | | Doesn't attempt to deal with cases where we might have already generated the functiondef for the parent function as in that case we cannot easily modify the forward pass. PiperOrigin-RevId: 216243224
* | Add timeout mechanism to Grappler meta optimizer. This is only a best-effort ↵Gravatar A. Unique TensorFlower2018-10-08
| | | | | | | | | | | | mechanism, since the meta optimizer only checks if it has been cancelled before running each sub-optimizer. We can add cancellation to each sub-optimizer if necessary. PiperOrigin-RevId: 216234262
* | Update ops-related pbtxt files.Gravatar A. Unique TensorFlower2018-10-08
| | | | | | | | PiperOrigin-RevId: 216217887
* | Merge pull request #21658 from lowintelligence:masterGravatar TensorFlower Gardener2018-10-08
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* | | [tf.data] Adding specialization for `MapDataset`, `ParallelMapDataset`, and ↵Gravatar Jiri Simsa2018-10-08
| | | | | | | | | | | | | | | | | | `MapAndBatchDataset` whose user-provided functions have the property that each output argument take its value directly from an input argument (e.g. `lambda x, y: y, x`). This specialization can produce the result without having to schedule the function using the executor. PiperOrigin-RevId: 216206232
* | | Fix compilation in unique_op when Eigen::Index != int64.Gravatar A. Unique TensorFlower2018-10-08
| | | | | | | | | | | | PiperOrigin-RevId: 216205396
* | | Enable PinToHostOptimizer.Gravatar A. Unique TensorFlower2018-10-08
| | | | | | | | | | | | PiperOrigin-RevId: 216201732
* | | Optimize PinToHostOptimizer by adding cache, also add PinToHostOptimizer to ↵Gravatar A. Unique TensorFlower2018-10-08
| | | | | | | | | | | | | | | | | | | | | | | | | | | benchmarks. original runtime: 4.83492736816 secs w/ cache runtime: 2.19033999443 secs PiperOrigin-RevId: 216195286
* | | Make ExecutorState preserve the thread context.Gravatar A. Unique TensorFlower2018-10-08
| | | | | | | | | | | | PiperOrigin-RevId: 216187878
* | | Update ops-related pbtxt files.Gravatar A. Unique TensorFlower2018-10-05
| | | | | | | | | | | | PiperOrigin-RevId: 216000752
* | | Merge pull request #22386 from girving:statelessGravatar TensorFlower Gardener2018-10-05
|\ \ \ | | | | | | | | | | | | PiperOrigin-RevId: 215995215
* | | | [tf.data vectorization] Feed inputs to vectorizers with notion of stackednessGravatar Rachel Lim2018-10-05
| | | | | | | | | | | | | | | | PiperOrigin-RevId: 215989259
| * | | Expand stateless random generators to match their stateful cousinsGravatar Geoffrey Irving2018-10-05
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | stateless_random_uniform now take minval+maxval and handles ints, and stateless_normal/stateless_truncated_normal take mean+stddev. Additionally, all of the stateless functions now have proper doc strings. This is step one of moving stateless random numbers out of contrib.
* | | | Automated rollback of commit ae0bc6f006497cc04a2ee75166d4ec71c7154fd8Gravatar Jiri Simsa2018-10-05
| | | | | | | | | | | | | | | | PiperOrigin-RevId: 215969360
* | | | [tf.data] Adding specialization for `MapDataset`, `ParallelMapDataset`, and ↵Gravatar Jiri Simsa2018-10-05
| | | | | | | | | | | | | | | | | | | | | | | | `MapAndBatchDataset` whose user-provided functions have the property that each output argument take its value directly from an input argument (e.g. `lambda x, y: y, x`). This specialization can produce the result without having to schedule the function using the executor. PiperOrigin-RevId: 215957592
| | | * Clean up the code under INTEL_MKL_ML_ONLYGravatar shengfuintel2018-10-05
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* | | | Copy device from If op to the lowered ops.Gravatar Saurabh Saxena2018-10-05
| | | | | | | | | | | | | | | | | | | | | | | | Enable GPU tests for cond_v2. PiperOrigin-RevId: 215956220
* | | | Merge pull request #20476 from yongtang:06052018-bincount-shapeGravatar TensorFlower Gardener2018-10-05
|\ \ \ \ | | | | | | | | | | | | | | | PiperOrigin-RevId: 215947463
* | | | | Revert constant folding to previous state.Gravatar Tong Shen2018-10-05
| |_|_|/ |/| | | | | | | | | | | PiperOrigin-RevId: 215946205
* | | | Declare that stateless random ops are not differentiable in C++ code.Gravatar Tong Shen2018-10-05
| | | | | | | | | | | | | | | | PiperOrigin-RevId: 215935319
* | | | When running a native/builtin op via eager C API, automatically fill in defaultGravatar Mingsheng Hong2018-10-05
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | attr values that are not overridden e.g. transpose_a in the matmul op). This is required for backward compatibility (a binary built via an older version of TF should still run on a newer version of TF, where some ops may have added attrs). For non-eager graph building, the default attr values of graph ops are added by tensorflow::AddDefaultsToNodeDef(). We ran into this issue when running the same S4TF test cases via eager APIs -- some tests failed due to "missing attrs", but are fixed by this patch. PiperOrigin-RevId: 215927271
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