| 7149a2e2e2f549035f23e21224ee41afe8df3876 |
|
30-Jan-2018 |
A. Unique TensorFlower <gardener@tensorflow.org> |
Cleanup: Ran clang-format on files in tensorflow/core/.../*.{cc,h}.
PiperOrigin-RevId: 183848459
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 20765b3e1ae3b718699592c98aa9805cb874b6d1 |
|
29-Dec-2017 |
Patrick Nguyen <drpng@google.com> |
Merge changes from github.
PiperOrigin-RevId: 180301735
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| d8425f553b5e67bc1fb008b8719dd3f59b3e0957 |
|
08-Dec-2017 |
Derek Murray <mrry@google.com> |
Add n=1 special case to the DeserializeSparse op.
This avoids excessive copying in the common case where the
sparse-format output of a `tf.data.Dataset` pipeline or the input to a
`Dataset.map()` or `Dataset.filter()` transformation contains a single
`tf.SparseTensor`.
As I was refactoring to add the special case, I ended up removing the
template parameter for the output values' tensor DataType, and
switching the sole reamining code that depends on it to use a `switch`
on the `"dtype"` attr. This will reduce the binary size for this op.
PiperOrigin-RevId: 178404305
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 90d6421c5e0898fb840197d9533c2f8ba1a7c651 |
|
11-Jul-2017 |
Shanqing Cai <cais@google.com> |
Merge changes from github.
END_PUBLIC
---
Commit d0f53f77f authored by Penghao Cen<scorpiocph@gmail.com>
Committed by Shanqing Cai<cais@google.com>:
Minor fix typo (#11323)
---
Commit 02fcf564e authored by Chris Song<sjhshy@gmail.com>
Committed by Chris Song<sjhshy@gmail.com>:
Fix misspells.
---
Commit 764c9b6b4 authored by Louis Tiao<ltiao@users.noreply.github.com>
Committed by GitHub<noreply@github.com>:
Fixed typo in docstring
---
Commit f8cd1283e authored by Shanqing Cai<cais@google.com>
Committed by Shanqing Cai<cais@google.com>:
Chaser
---
Commit 01383b946 authored by Shanqing Cai<cais@google.com>
Committed by Shanqing Cai<cais@google.com>:
Adapt TensorFlowTestCase.setUp() to new reset_default_graph() semantics
Avoid calling reset_default_graph() directly to prevent exceptions in
cases where test methods error out from within nested graph contexts,
which can leave _default_graph_stack non-empty in certain Python
versions.
---
Commit 0ffc37890 authored by Amit Patankar<amitpatankar@google.com>
Committed by Amit Patankar<amitpatankar@google.com>:
Removing second declaration of functions.
---
Commit f9c9cacb0 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Refactor ElementalIrEmitter's slice index finding code into
IrArray::Index::SourceIndexOfSlice().
PiperOrigin-RevId: 161140653
---
Commit ba297aec9 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Update ops-related pbtxt files.
PiperOrigin-RevId: 161138258
---
Commit 68d666737 authored by Alexandre Passos<apassos@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fixes a reentrant lock issue with tensors using ndarray memory which uses tensor memory.
PiperOrigin-RevId: 161137788
---
Commit a2ee8bca3 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Add support for int8 x int8 -> int32 matrix multiplication via cublasGemmEx to stream_executor.
PiperOrigin-RevId: 161137741
---
Commit 755fa7b50 authored by Mark Daoust<markdaoust@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Block generate_test, and docs generating from running in python3.
- Doc generation is currently unsupported in python3
- These both end in errors in python 3.5.1+
PiperOrigin-RevId: 161137467
---
Commit 97cbcac45 authored by Peter Hawkins<phawkins@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[TF:XLA] Fix failure in functionalize_control_flow rewrite for Enter nodes that are unused. Make sure we ignore such nodes without producing an error.
PiperOrigin-RevId: 161136545
---
Commit dabcb60bc authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
[XLA] Add reasonable error messages to Builder::Build for bad parameter numbers.
PiperOrigin-RevId: 161136262
---
Commit 0cbd249e8 authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Add complex tensors support to `matrix_determinant`.
PiperOrigin-RevId: 161132422
---
Commit 335f1f14d authored by A. Unique TensorFlower<gardener@tensorflow.org>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Extend static shape inference for SparseTensors with dense_shapes constructed using slicing.
PiperOrigin-RevId: 161132391
---
Commit 53604916e authored by Jianwei Xie<xiejw@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Fixed the missing labels test in TPUEstimator.
PiperOrigin-RevId: 161131282
---
Commit 9f57dc8dd authored by Bruno Rosa<bruno.rosa@eldorado.org.br>
Committed by Bruno Rosa<bruno.rosa@eldorado.org.br>:
Use mcpu instead of march for ppc64le
march is not support by gcc on ppc64le
---
Commit 7d5c74a9c authored by Skye Wanderman-Milne<skyewm@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Move duplicate detection logic from Graph to FunctionLibraryDefinition
Turns out this is more useful, since there are many function libraries
that don't belong to a graph. This will be used in a future
change. Note that this maintains the current behavior of Graph.
In addition, updates FunctionDefsEqual() to handle unset attr entries
(I ran into this when using this in said future change).
PiperOrigin-RevId: 161126628
---
Commit 2caec3af1 authored by Shanqing Cai<cais@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Disable more timeseries py tests failing in OSS PIP GPU builds
PiperOrigin-RevId: 161124799
---
Commit 0b5cce367 authored by Eugene Brevdo<ebrevdo@google.com>
Committed by TensorFlower Gardener<gardener@tensorflow.org>:
Get TopK op working on GPU again. Extend using cub's radix sort.
1. Undo rollback of Andreas Kirsch's initial implementation.
2. Use cub segmented radix sort if Andreas' heap-based impl
for large k and small num_cols (thresholds of k=100, n=1000
determined empirically).
3. Use cub segmented radix sort if k == num_cols (this case is always faster).
4. Added benchmarks.
Benchmarks show that the GPU implementation is up to 3x slower for small k but
can be 10x faster for large num_cols and k.
Benchmarks:
Benchmark: m_128_n_10_k_5_use_gpu_False wall_time: 0.000166 s Throughput: 0.0077 GB/s
Benchmark: m_128_n_10_k_5_use_gpu_True wall_time: 0.000796 s Throughput: 0.00161 GB/s
Benchmark: m_128_n_10_k_9_use_gpu_False wall_time: 0.00017 s Throughput: 0.00751 GB/s
Benchmark: m_128_n_10_k_9_use_gpu_True wall_time: 0.000796 s Throughput: 0.00161 GB/s
Benchmark: m_128_n_10_k_10_use_gpu_False wall_time: 0.00017 s Throughput: 0.00753 GB/s
Benchmark: m_128_n_10_k_10_use_gpu_True wall_time: 0.000775 s Throughput: 0.00165 GB/s
Benchmark: m_128_n_100_k_1_use_gpu_False wall_time: 0.000155 s Throughput: 0.0826 GB/s
Benchmark: m_128_n_100_k_1_use_gpu_True wall_time: 0.000796 s Throughput: 0.0161 GB/s
Benchmark: m_128_n_100_k_50_use_gpu_False wall_time: 0.000247 s Throughput: 0.0519 GB/s
Benchmark: m_128_n_100_k_50_use_gpu_True wall_time: 0.0008 s Throughput: 0.016 GB/s
Benchmark: m_128_n_100_k_99_use_gpu_False wall_time: 0.000261 s Throughput: 0.049 GB/s
Benchmark: m_128_n_100_k_99_use_gpu_True wall_time: 0.000794 s Throughput: 0.0161 GB/s
Benchmark: m_128_n_100_k_100_use_gpu_False wall_time: 0.000239 s Throughput: 0.0536 GB/s
Benchmark: m_128_n_100_k_100_use_gpu_True wall_time: 0.000777 s Throughput: 0.0165 GB/s
Benchmark: m_128_n_1000_k_1_use_gpu_False wall_time: 0.000324 s Throughput: 0.395 GB/s
Benchmark: m_128_n_1000_k_1_use_gpu_True wall_time: 0.000916 s Throughput: 0.14 GB/s
Benchmark: m_128_n_1000_k_10_use_gpu_False wall_time: 0.00042 s Throughput: 0.305 GB/s
Benchmark: m_128_n_1000_k_10_use_gpu_True wall_time: 0.000902 s Throughput: 0.142 GB/s
Benchmark: m_128_n_1000_k_500_use_gpu_False wall_time: 0.0011 s Throughput: 0.116 GB/s
Benchmark: m_128_n_1000_k_500_use_gpu_True wall_time: 0.00097 s Throughput: 0.132 GB/s
Benchmark: m_128_n_1000_k_990_use_gpu_False wall_time: 0.00133 s Throughput: 0.0962 GB/s
Benchmark: m_128_n_1000_k_990_use_gpu_True wall_time: 0.000993 s Throughput: 0.129 GB/s
Benchmark: m_128_n_1000_k_1000_use_gpu_False wall_time: 0.00102 s Throughput: 0.126 GB/s
Benchmark: m_128_n_1000_k_1000_use_gpu_True wall_time: 0.000964 s Throughput: 0.133 GB/s
Benchmark: m_128_n_10000_k_10_use_gpu_False wall_time: 0.002 s Throughput: 0.64 GB/s
Benchmark: m_128_n_10000_k_10_use_gpu_True wall_time: 0.00288 s Throughput: 0.445 GB/s
Benchmark: m_128_n_10000_k_100_use_gpu_False wall_time: 0.00233 s Throughput: 0.549 GB/s
Benchmark: m_128_n_10000_k_100_use_gpu_True wall_time: 0.00325 s Throughput: 0.394 GB/s
Benchmark: m_128_n_10000_k_5000_use_gpu_False wall_time: 0.0127 s Throughput: 0.101 GB/s
Benchmark: m_128_n_10000_k_5000_use_gpu_True wall_time: 0.00381 s Throughput: 0.336 GB/s
Benchmark: m_128_n_10000_k_9900_use_gpu_False wall_time: 0.015 s Throughput: 0.0853 GB/s
Benchmark: m_128_n_10000_k_9900_use_gpu_True wall_time: 0.00438 s Throughput: 0.292 GB/s
Benchmark: m_128_n_10000_k_10000_use_gpu_False wall_time: 0.0104 s Throughput: 0.123 GB/s
Benchmark: m_128_n_10000_k_10000_use_gpu_True wall_time: 0.00427 s Throughput: 0.3 GB/s
Benchmark: m_128_n_100000_k_100_use_gpu_False wall_time: 0.0148 s Throughput: 0.865 GB/s
Benchmark: m_128_n_100000_k_100_use_gpu_True wall_time: 0.0262 s Throughput: 0.488 GB/s
Benchmark: m_128_n_100000_k_1000_use_gpu_False wall_time: 0.0201 s Throughput: 0.636 GB/s
Benchmark: m_128_n_100000_k_1000_use_gpu_True wall_time: 0.0263 s Throughput: 0.486 GB/s
Benchmark: m_128_n_100000_k_50000_use_gpu_False wall_time: 0.214 s Throughput: 0.0599 GB/s
Benchmark: m_128_n_100000_k_50000_use_gpu_True wall_time: 0.0322 s Throughput: 0.398 GB/s
Benchmark: m_128_n_100000_k_99000_use_gpu_False wall_time: 0.262 s Throughput: 0.0489 GB/s
Benchmark: m_128_n_100000_k_99000_use_gpu_True wall_time: 0.0377 s Throughput: 0.34 GB/s
Benchmark: m_128_n_100000_k_100000_use_gpu_False wall_time: 0.118 s Throughput: 0.108 GB/s
Benchmark: m_128_n_100000_k_100000_use_gpu_True wall_time: 0.0365 s Throughput: 0.351 GB/s
END_PUBLIC
BEGIN_PUBLIC
BEGIN_PUBLIC
Automated g4 rollback of changelist 157169178
PiperOrigin-RevId: 161476569
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| cade141580c76b41ba71bdc4b019722e674ab954 |
|
09-Jun-2017 |
Eugene Brevdo <ebrevdo@google.com> |
Update internal SparseTensor C++ implementation to use a vector of int64.
The current behavior, which relies on a TensorShape to store the dense shape,
can lead to CHECK failures if a SparseTensor is created with a dense_shape that is
too lare.
PiperOrigin-RevId: 158521473
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 1cb96893a64f59b7265f9def9968f7bed1e57662 |
|
09-Dec-2016 |
Andrew Harp <andrewharp@google.com> |
Merge changes from github.
Additionally:
- change single quotes to double quotes to make path rewriting easier
- guard windows lib reference with PLATFORM_WINDOWS
- fixed failing kmeans test
Change: 141515942
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| cab760f7dc7a1b425aba55ca9cd28de4360ce1dd |
|
10-Oct-2016 |
Eugene Brevdo <ebrevdo@google.com> |
Speed up SparseTensor::Concat by replacing Eigen slicing with for loops.
This turns out to be faster pretty much in all realistic cases.
Change: 135689005
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 1a295f88ecc387c03b9de28b4c948c1d2a2c331e |
|
27-Sep-2016 |
Eugene Brevdo <ebrevdo@google.com> |
Add benchmark for util/SparseTensor's SparseReorder, and optimize SparseTensor::Reorder.
Change: 134425452
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 7c4b521c49199edf50137674302014c01db6eda5 |
|
12-Sep-2016 |
Jonathan Hseu <jhseu@google.com> |
Add a new SparseReduceSumSparse op that sums a SparseTensor with a SparseTensor
output.
Also add a SparseTensorReduceHelper function that generalizes reductions on
SparseTensors.
Change: 132883606
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| d278b7b12bffd4deb1dadb4ce8148e4bb8fc021a |
|
03-Sep-2016 |
Jonathan Hseu <jhseu@google.com> |
Support scalar SparseTensors. Scalar SparseTensors are useful for reduction ops
that return SparseTensors. Dimensions are removed, and the result can end up
being a scalar.
Change: 132111451
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| b0bdff4827f867a67f572ed99d85f9a847788326 |
|
26-Aug-2016 |
A. Unique TensorFlower <gardener@tensorflow.org> |
Merge changes from github.
Change: 131437429
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 5e463066b207cce27327f885f3f483c0ff7d2606 |
|
03-Aug-2016 |
A. Unique TensorFlower <gardener@tensorflow.org> |
Type fix in SparseTensor::PickDims.
Change: 129171357
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| c8b59c046895fa5b6d79f73e0b5817330fcfbfc1 |
|
02-Jun-2016 |
A. Unique TensorFlower <nobody@tensorflow.org> |
Update copyright for 3p/tf/core.
Change: 123900938
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| b3b58fc059e0355664998dad1f313f109b322f06 |
|
19-Apr-2016 |
Zongheng Yang <zongheng.y@gmail.com> |
Introduce tf.sparse_reduce_sum() and a CPU kernel.
Change: 120183287
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| fd535e00fce5963f066b60b4a1e8822d4be92793 |
|
15-Apr-2016 |
A. Unique TensorFlower <nobody@tensorflow.org> |
Add shape and order asserts in SparseTensor constructor.
Add const to SparseTensor.group.
Overload == on GroupIterable.IteratorStep.
Change: 119897767
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 2ce60da7d2ece5d23b0843bce42123c7b5633c71 |
|
16-Mar-2016 |
David G. Andersen <dga@google.com> |
Forcing copy of input tensor, switching to use FastBoundsCheck
Change: 117384840
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 8d7f58d44d9e3d2d82066cc5c286d6d433079621 |
|
26-Feb-2016 |
Geoffrey Irving <geoffreyi@google.com> |
Make sparse index error messages more informative
They now say what the index is and give the required bounds for out of bounds
errors. Example (slightly paraphrased):
Index 0 is out of bounds, foolish user.
vs.
indices[0] = [0,128] is out of bounds: need 0 <= index < [64,10]
Change: 115705692
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 73d557cc88ee86834917088416e5ce8783d11798 |
|
25-Feb-2016 |
A. Unique TensorFlower <nobody@tensorflow.org> |
Fix an error message in tf.sparse_to_dense to include the possibility that indices are invalid because they are out of bounds.
Change: 115522264
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| a8d2f0983ecdea8ff2526c717d6a9b2f06f403d8 |
|
02-Feb-2016 |
Vijay Vasudevan <vrv@google.com> |
Minor formatting fixes.
Change: 113582098
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| dc8e9abc2ceb27c7f39c9316f849743520e7eee4 |
|
26-Jan-2016 |
Josh Levenberg <josh11b@tensorflow.org> |
Global search & replace to move to the new location for
tensorflow/core/ files and build targets.
Change: 113074952
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 9b70316263eb74476ab96b7c0f300c4d90223425 |
|
25-Jan-2016 |
Vijay Vasudevan <vrv@google.com> |
Running our linter on a lot of files.
Change: 112920860
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| b481783fe0e00a86f6feb20a8dcad5fc4fc936a4 |
|
21-Jan-2016 |
Josh Levenberg <josh11b@tensorflow.org> |
Move #include <vector> out of port.h to users of std::vector<>.
After this we can replace port.h with types.h.
Change: 112727463
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 0a21a38d4ef5b66177f407f74f14dd7b72232b36 |
|
11-Dec-2015 |
Vijay Vasudevan <vrv@google.com> |
TensorFlow: merge changes from internal
Change 110010103
Implementing SparseSplitOp.
The op takes a sparse tensor (list, values and shape), split_dim and num_splits and produces a list of num_splits tensors where the shape of each tensor is the shape of the original tensor except split_dim = shape[split_dim +num_split - 1 / num_split]. in case if shape[split_dim] is not an integer multiple of num_split an extra one dimension get added to the slices starting from 0.
For example if the input shape is a [2, 10] split_dim = 1, num_split = 3
output shapes will be [[2, 4], [2, 4], [2, 2]].
The Op register shape to [Unknown, dim] for indices tensors and [Unknown] for the values tensor because shape can't be inferred without evaluate input tensors.
Base CL: 110012853
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| ddd4aaf5286de24ba70402ee0ec8b836d3aed8c7 |
|
08-Dec-2015 |
Vijay Vasudevan <vrv@google.com> |
TensorFlow: upstream changes to git.
Change 109695551
Update FAQ
Change 109694725
Add a gradient for resize_bilinear op.
Change 109694505
Don't mention variables module in docs
variables.Variable should be tf.Variable.
Change 109658848
Adding an option to create a new thread-pool for each session.
Change 109640570
Take the snapshot of stream-executor.
+ Expose an interface for scratch space allocation in the interface.
Change 109638559
Let image_summary accept uint8 input
This allows users to do their own normalization / scaling if the default
(very weird) behavior of image_summary is undesired.
This required a slight tweak to fake_input.cc to make polymorphically typed
fake inputs infer if their type attr is not set but has a default.
Unfortunately, adding a second valid type to image_summary *disables* automatic
implicit conversion from np.float64 to tf.float32, so this change is slightly
backwards incompatible.
Change 109636969
Add serialization operations for SparseTensor.
Change 109636644
Update generated Op docs.
Change 109634899
TensorFlow: add a markdown file for producing release notes for our
releases. Seed with 0.5.0 with a boring but accurate description.
Change 109634502
Let histogram_summary take any realnumbertype
It used to take only floats, not it understands ints.
Change 109634434
TensorFlow: update locations where we mention python 3 support, update
them to current truth.
Change 109632108
Move HSV <> RGB conversions, grayscale conversions, and adjust_* ops back to tensorflow
- make GPU-capable version of RGBToHSV and HSVToRGB, allows only float input/output
- change docs to reflect new size constraints
- change HSV format to be [0,1] for all components
- add automatic dtype conversion for all adjust_* and grayscale conversion ops
- fix up docs
Change 109631077
Improve optimizer exceptions
1. grads_and_vars is now a tuple, so must be wrapped when passed to format.
2. Use '%r' instead of '%s' for dtype formatting
Base CL: 109697989
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 9c3043ff3bf31a6a81810b4ce9e87ef936f1f529 |
|
20-Nov-2015 |
Manjunath Kudlur <keveman@gmail.com> |
TensorFlow: Improve performance of Alexnet
Changes:
* error message that refers to removed `DefaultSession` method.
* -Wnull-conversion warnings
* the "_start_time" attr for recvs when the flag "--brain_enable_scheduling_for_recvs" is set.
* typo in tutorial data download progress message.
* a typo ("however their installing"=>"however installing").
* typo, rename "TensorFlow Mechanics" to "How To" to be consistent with the website.
* a typo ("subtact"=>"subtract").
* protobuf examples in comments in tensorflow::Example.proto.
* formula formatting in MNIST beginner tutorial
* negative fraction-of-queue-full stats
* protobuf inclusion path so that Android demo will build under Blaze.
* small typo (moderatly > moderately)
* Session.run() to check that tensor arguments come from the session's graph.
* another six import
* seq2seq typo in bazel command
Base CL: 108349164
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| 56313def004795f75ef8281a0294c958d28f1e06 |
|
16-Nov-2015 |
Vijay Vasudevan <vrv@google.com> |
TensorFlow: Doc and linter fixes, some additional tests and
error handling, updates to website.
Changes:
- Removes redundant reshape from image models by @mrry
- Default TensorBoard to localhost by @danmane
- Reformatting of tensorflow/core by @josh11b
- Make tutorials backwards compatible to 0.5.0 by @girving
- Improve print documentation (md files not updated).
- Add proper scrolling to sitemap by @martinwicke
Base CL: 107956254
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|
| f41959ccb2d9d4c722fe8fc3351401d53bcf4900 |
|
07-Nov-2015 |
Manjunath Kudlur <keveman@gmail.com> |
TensorFlow: Initial commit of TensorFlow library.
TensorFlow is an open source software library for numerical computation
using data flow graphs.
Base CL: 107276108
/external/tensorflow/tensorflow/core/util/sparse/sparse_tensor.h
|